This document proposes a local security enhancement and intrusion prevention system for Android devices. It summarizes existing host-based intrusion detection systems and behavior-based intrusion prevention systems for Android smartphones. The proposed system uses net flow based clustering to identify anomalies and correlates with host-based features to detect malware intrusions. The goal is to provide versatile security for Android smartphones by detecting a wide range of attacks, including denial of service attacks and probing. The system aims to detect new attacks as well.
This document presents a proposed intrusion detection system using data mining techniques. It begins with an abstract that describes how internal intrusions are difficult to detect as internal users know the organization's information. It then discusses how anomaly detection can be used to create behavior profiles for each user and detect anomalous activities. The introduction provides background on intrusion detection systems and the need for more efficient and effective detection methods. It describes the proposed system which will use data mining techniques like k-means clustering to separate normal and abnormal network activities in order to detect internal attacks. It discusses the hardware and software requirements and specifications. Finally, it concludes that the proposed system can better detect anomalies in the network compared to other machine learning approaches.
A Modular Approach To Intrusion Detection in Homogenous Wireless Network
This document discusses a modular approach to intrusion detection in homogeneous wireless networks. It begins by introducing wireless networks and the need for intrusion detection systems (IDS) due to security vulnerabilities. It then discusses different types of IDS, including signature-based detection that identifies known attacks, and anomaly-based detection that identifies deviations from normal behavior but can result in high false positives. The document proposes a modular approach combining advantages of signature-based and anomaly-based detection for high detection rates and low false positives. Requirements for IDS in wireless networks are also outlined.
IRJET- Phishdect & Mitigator: SDN based Phishing Attack Detection
The document proposes a new system called PhishDect and Mitigator to detect and mitigate phishing attacks using software-defined networking (SDN). It uses deep packet inspection techniques and a convolutional neural network (CNN) to classify phishing signatures. Traffic is directed through either a "store and forward" or "forward and inspect" mode. In store and forward mode, packets are stored and inspected before forwarding. In forward and inspect mode, packets are forwarded first and then a copy is inspected. The system aims to overcome limitations of existing phishing detection methods.
The spread of information networks in communities and organizations have led to a daily huge volume of information exchange between different networks which, of course, has resulted in new threats to the national organizations. It can be said that information security has become today one of the most challenging areas. In other words, defects and disadvantages of computer network security address irreparable damage for enterprises. Therefore, identification of security threats and ways of dealing with them is essential. But the question raised in this regard is that what are the strategies and policies to deal with security threats that must be taken to ensure the security of computer networks? In this context, the present study intends to do a review of the literature by using earlier researches and library approach, to provide security solutions in the face of threats to their computer networks. The results of this research can lead to more understanding of security threats and ways to deal with them and help to implement a secure information platform.
A Study on Recent Trends and Developments in Intrusion Detection SystemIOSR Journals
This document discusses recent trends and developments in intrusion detection systems. It covers several topics:
- Artificial intelligence and machine learning techniques like neural networks, genetic algorithms, and fuzzy logic can be applied to intrusion detection to improve detection capabilities.
- There are different types of intrusion detection systems, including network-based, host-based, and wireless intrusion detection. Signature-based and anomaly-based detection are also discussed.
- Popular open source intrusion detection tools like Snort are discussed as alternatives to commercial intrusion prevention systems for some organizations.
- Intrusion prevention systems not only detect attacks but can also block attacks in real-time, providing an enhanced level of protection over intrusion
A Collaborative Intrusion Detection System for Cloud Computingijsrd.com
Cloud computing is a computing paradigm that shifts drastically from traditional computing architecture. Although this new computing paradigm brings many advantages like utility computing model but the design in not flawless and hence suffers from not only many known computer vulnerabilities but also introduces unique information confidentiality, integrity and availability risks as well due its inherent design paradigm. To provide secure and reliable services in cloud computing environment is an important issue. To counter a variety of attacks, especially large-scale coordinated attacks, a framework of Collaborative Intrusion Detection System (IDS) is proposed. The proposed system could reduce the impact of these kinds of attacks through providing timely notifications about new intrusions to Cloud users' systems. To provide such ability, IDSs in the cloud computing regions both correlate alerts from multiple elementary detectors and exchange knowledge of interconnected Clouds with each other.
Intrusion Detection System using Data MiningIRJET Journal
This document presents a proposed intrusion detection system using data mining techniques. It begins with an abstract that describes how internal intrusions are difficult to detect as internal users know the organization's information. It then discusses how anomaly detection can be used to create behavior profiles for each user and detect anomalous activities. The introduction provides background on intrusion detection systems and the need for more efficient and effective detection methods. It describes the proposed system which will use data mining techniques like k-means clustering to separate normal and abnormal network activities in order to detect internal attacks. It discusses the hardware and software requirements and specifications. Finally, it concludes that the proposed system can better detect anomalies in the network compared to other machine learning approaches.
A Modular Approach To Intrusion Detection in Homogenous Wireless NetworkIOSR Journals
This document discusses a modular approach to intrusion detection in homogeneous wireless networks. It begins by introducing wireless networks and the need for intrusion detection systems (IDS) due to security vulnerabilities. It then discusses different types of IDS, including signature-based detection that identifies known attacks, and anomaly-based detection that identifies deviations from normal behavior but can result in high false positives. The document proposes a modular approach combining advantages of signature-based and anomaly-based detection for high detection rates and low false positives. Requirements for IDS in wireless networks are also outlined.
IRJET- Phishdect & Mitigator: SDN based Phishing Attack DetectionIRJET Journal
The document proposes a new system called PhishDect and Mitigator to detect and mitigate phishing attacks using software-defined networking (SDN). It uses deep packet inspection techniques and a convolutional neural network (CNN) to classify phishing signatures. Traffic is directed through either a "store and forward" or "forward and inspect" mode. In store and forward mode, packets are stored and inspected before forwarding. In forward and inspect mode, packets are forwarded first and then a copy is inspected. The system aims to overcome limitations of existing phishing detection methods.
Cyber Warfare is the current single greatest emerging threat to National Security. Network security has become an essential component of any computer network. As computer networks and systems become ever more fundamental to modern society, concerns about security has become increasingly important. There are a multitude of different applications open source and proprietary available for the protection +-system administrator, to decide on the most suitable format for their purpose requires knowledge of the available safety measures, their features and how they affect the quality of service, as well as the kind of data they will be allowing through un flagged. A majority of methods currently used to ensure the quality of a networks service are signature based. From this information, and details on the specifics of popular applications and their implementation methods, we have carried through the ideas, incorporating our own opinions, to formulate suggestions on how this could be done on a general level. The main objective was to design and develop an Intrusion Detection System. While the minor objectives were to; Design a port scanner to determine potential threats and mitigation techniques to withstand these attacks. Implement the system on a host and Run and test the designed IDS. In this project we set out to develop a Honey Pot IDS System. It would make it easy to listen on a range of ports and emulate a network protocol to track and identify any individuals trying to connect to your system. This IDS will use the following design approaches: Event correlation, Log analysis, Alerting, and policy enforcement. Intrusion Detection Systems (IDSs) attempt to identify unauthorized use, misuse, and abuse of computer systems. In response to the growth in the use and development of IDSs, we have developed a methodology for testing IDSs. The methodology consists of techniques from the field of software testing which we have adapted for the specific purpose of testing IDSs. In this paper, we identify a set of general IDS performance objectives which is the basis for the methodology. We present the details of the methodology, including strategies for test-case selection and specific testing procedures. We include quantitative results from testing experiments on the Network Security Monitor (NSM), an IDS developed at UC Davis. We present an overview of the software platform that we have used to create user-simulation scripts for testing experiments. The platform consists of the UNIX tool expect and enhancements that we have developed, including mechanisms for concurrent scripts and a record-and-replay feature. We also provide background information on intrusions and IDSs to motivate our work.
1. Cyber Ethics and Cyber Crime
2. Security in Social Media & Risk of Child Internet
3. Social media in Schools and photo privacy
4. Risk of OSNs and Security, Privacy of Facebook
5. Risk and Security of Social Networking site Facebook and Twitter
6. Risk analysis of Government and Online Transaction
This document discusses network intrusion detection systems (NIDS) and their ability to handle high-speed traffic. It introduces NIDS and their role in monitoring network traffic. The document presents an experiment that tests the open-source NIDS Snort under high-volume traffic. The experiment shows that Snort drops more packets as traffic speed and volume increases, demonstrating a weakness of NIDS in high-speed environments. It suggests using a parallel NIDS technique to help NIDS better handle high-speed network traffic and reduce packet dropping.
Intrusion Detection Systems (IDSs) have become widely recognized as powerful tools for identifying, deterring and deflecting malicious attacks over the network. Intrusion detection systems (IDSs) are designed and installed to aid in deterring or mitigating the damage that can be caused by hacking, or breaking into sensitive IT systems. . The attacks can come from outsider attackers on the Internet, authorized insiders who misuse the privileges that have been given them and unauthorized insiders who attempt to gain unauthorized privileges. IDSs cannot be used in isolation, but must be part of a larger framework of IT security measures. Essential to almost every intrusion detection system is the ability to search through packets and identify content that matches known attacks. Space and time efficient string matching algorithms are therefore important for identifying these packets at line rate. In this paper we examine string matching algorithm and their use for Intrusion Detection. Keywords: System Design, Network Algorithm
Security Issues and Challenges in Internet of Things – A ReviewIJERA Editor
The Internet of Things (IoT) alludes to the continually developing system of physical articles that component an
IP address for web availability, and the correspondence that happens between these items and other Web
empowered gadgets and frameworks. The security issues of the Internet of Things (IoT) are straight forwardly
identified with the wide utilization of its framework. IoT securities and enhancing the design and several
elements of this work showcases various security issues with respect to IoT and thinks of solutions for the issues
under the advancements included. Here we are going to do a study of all the security issues existing in the
Internet of Things (IoT) alongside an examination of the protection issues that an end-client might confront as
an outcome of the spread of IoT. Most of the overview is centred around the security emerging out of the data
trade innovations utilized as a part of Internet of Things. As a piece of IoTs, genuine concerns are raised over
access of individual data relating to gadget and individual protection. This review tells about the security and
protection issues of IoT.
IoT Network Attack Detection using Supervised Machine LearningCSCJournals
The use of supervised learning algorithms to detect malicious traffic can be valuable in designing intrusion detection systems and ascertaining security risks. The Internet of things (IoT) refers to the billions of physical, electronic devices around the world that are often connected over the Internet. The growth of IoT systems comes at the risk of network attacks such as denial of service (DoS) and spoofing. In this research, we perform various supervised feature selection methods and employ three classifiers on IoT network data. The classifiers predict with high accuracy if the network traffic against the IoT device was malicious or benign. We compare the feature selection methods to arrive at the best that can be used for network intrusion prediction.
Augment Method for Intrusion Detection around KDD Cup 99 DatasetIRJET Journal
This document discusses augmenting methods for intrusion detection using the KDD Cup 99 dataset. It aims to improve detection accuracy and reduce false positives. The key points are:
- It analyzes detection precision and true positive rate (recall) for different attack classes in the KDD Cup 99 dataset to help improve dataset accuracy.
- Experimental results show the contribution of each attack class to recall and precision, which can help optimize the dataset to achieve highest accuracy with lowest false positives.
- The goal is to enhance testing of detection models and improve data quality to advance offline intrusion detection capabilities.
Mobile Ad hoc Networks (MANETs) are wireless networks consisted of mobile free nodes that can move anywhere at any time without the need to any fixed infrastructure or any centralized administration. In this category of networks existing nodes must rely on each other to play the role of routers or switches instead of using central ones. The self-organized nature of such environments made MANETs vulnerable against many security threats. As a result, providing security requirements in MANETs is one of the most interesting challenges in such a network. In this group of networks, the use of cryptographic solutions is one of the most interesting security issues. The importance of this scientific area in MANETs is more drastic by considering that mentioned schemes must be lightweight enough to be appropriate for resource constrained platforms in such environment. This paper has tried to represent the position of cryptographic issues in MANETs. Moreover, security issues in mobile Ad hoc networks beside of different classes of public key cryptosystems have been introduced.
1) The retail sector has been hit by a series of cyber attacks over the past few years that have compromised customer data at large companies like Target and Neiman Marcus.
2) Current cybersecurity approaches are too slow and reactive, focusing on malware after attacks occur rather than proactively detecting threats.
3) Behavioral cyber defense monitoring could have detected the abnormal behaviors of attackers on Target and Neiman Marcus' networks before data breaches occurred.
Enhanced method for intrusion detection over kdd cup 99 datasetijctet
This document discusses an enhanced method for intrusion detection using the KDD Cup 99 dataset. It aims to improve the accuracy of the dataset by analyzing the contribution of different attack classes to metrics like true positive rate and precision. The study examines these evaluation metrics for an intrusion detection system to identify which attack classes most impact recall and precision. The goal is to help improve the quality of the KDD Cup 99 dataset to achieve higher accuracy with lower false positives.
Intelligent Network Surveillance Technology for APT Attack DetectionsAM Publications,India
Recently, long-term, advanced cyber-attacks targeting a specific enterprise or organization have been occurring again. These attacks occur over a long period and bypass detection by security systems unlike the existing attack pattern. For such reason, they create problems such as delayed real-time response and detection after damages have already been incurred. This paper introduces the design of technology that applies real-time network traffic monitoring to detect unknown functional cyber-attack on the network. Specifically, the algorithm was verified and evaluated in terms of performance in an actual commercial environment. Cyber-attack detection performance is expected to be improved by enhancing the algorithm and processing large volumes of traffic
The document discusses authentication, authorization, and accounting (the three As) as a leading model for access control. It describes authentication as identifying users, usually with a username and password. Authorization gives users access to resources based on their identity. Accounting (also called auditing) tracks user activity like time spent and services accessed. The document provides details on different authentication methods like passwords, PINs, smart cards, and digital certificates. It emphasizes the importance of strong passwords and changing them regularly.
Darktrace detected a number of anomalies across various customer networks including remote access attacks linked to malware, anomalous data transfers, domain generation algorithms, malicious web drive-bys, suspicious file downloads, unauthorized access to administrator credentials, ransomware infections, bitcoin mining, and connections to advanced persistent threat groups. Darktrace was able to detect these threats using unsupervised machine learning to identify anomalous behaviors rather than relying on rules or signatures.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
IRJET- Security Risk Assessment on Social Media using Artificial Intellig...IRJET Journal
1. The document proposes using artificial intelligence to assess security risks on social media by detecting suspicious activity and malicious URLs.
2. It discusses drawbacks of existing intrusion detection systems, including complexity and vulnerabilities.
3. The proposed system would use AI techniques to automate intrusion detection, identify unknown threats, and learn over time to handle large volumes of data.
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORTIJMIT JOURNAL
This document proposes an intrusion detection system using customized rules for the Snort tool to improve security. The system uses Wireshark to scan network traffic for anomalies, Snort to detect attacks using customized rulesets for faster response times, and Wazuh and Splunk to analyze log files. Rules are created using the Snorpy tool and added to Snort to monitor for specific attacks like ICMP ping impersonation and authentication attempts. When attacks are attempted, the system successfully detects them and logs the alerts. The integration of these tools provides low-cost intrusion detection capabilities with automated threat identification and faster response compared to existing Snort configurations.
Intrusion Detection System using AI and Machine Learning AlgorithmIRJET Journal
This document discusses using artificial intelligence and machine learning algorithms to develop an intrusion detection system (IDS). It begins with an abstract that outlines using AI to act as a virtual analyst to concurrently monitor network traffic and defend against threats. It then provides background on IDS and the need for more effective automated threat detection. The document discusses classifying attacks, different types of IDS (host-based and network-based), and detection methods like signature-based and anomaly-based. It aims to develop an IDS using machine learning algorithms that can learn patterns to provide automatic intrusion detection without extensive manual maintenance.
A Study On Recent Trends And Developments In Intrusion Detection SystemLindsey Sais
This document discusses recent trends and developments in intrusion detection systems. It covers several topics:
- Artificial intelligence and machine learning techniques like neural networks, genetic algorithms, and fuzzy logic can be applied to intrusion detection to identify patterns and anomalies.
- There are different types of intrusion detection systems, including network-based, host-based, and wireless intrusion detection. Signature-based and anomaly-based detection are also discussed.
- Popular open source intrusion detection tools like Snort are discussed as alternatives to commercial intrusion prevention systems for some organizations.
- Intrusion prevention systems not only detect intrusions but can also automatically block attacks in real-time.
Network security is a dynamic art, with dangers appearing as fast as black hats can exploit vulnerabilities. While there are basic “golden rules” which can make life difficult for the bad guys, it remains a challenge to keep networks secure. John Chambers, Executive Chairman of Cisco, famously said “there are two types of companies: those that have been hacked, and those who don’t know they have been hacked”. The question for most organizations isn’t if they’re going to be breached, but how quickly they can isolate and mitigate the threat. In this paper, we’ll examine best practices for effective cybersecurity – from both a proactive (access hardening) and reactive (threat isolation and mitigation) perspective. We’ll address how network automation can help minimize cyberattacks by closing vulnerability gaps and how it can improve incident response times in the event of a cyberthreat. Finally, we’ll lay a vision for continuous network security, to explore how machine-to-machine automation may deliver an auto-securing and self-healing network.
Go to www.esgjrconsultinginc.com
Toward Continuous Cybersecurity With Network AutomationKen Flott
Network security is a dynamic art, with dangers appearing as
fast as black hats can exploit vulnerabilities. While there are
basic “golden rules” which can make life difficult for the bad
guys, it remains a challenge to keep networks secure. John
Chambers, Executive Chairman of Cisco, famously said “there
are two types of companies: those that have been hacked, and
those who don’t know they have been hacked”. The question
for most organizations isn’t if they’re going to be breached, but
how quickly they can isolate and mitigate the threat.
In this paper, we’ll examine best practices for effective
cybersecurity – from both a proactive (access hardening)
and reactive (threat isolation and mitigation) perspective.
We’ll address how network automation can help minimize
cyberattacks by closing vulnerability gaps and how it can
improve incident response times in the event of a cyberthreat.
Finally, we’ll lay a vision for continuous network security, to
explore how machine-to-machine automation may deliver an
auto-securing and self-healing network.
I want you to Read intensively papers and give me a summary for ever.pdfamitkhanna2070
I want you to Read intensively papers and give me a summary for every paper and the linghth for
each paper is 2 pages or more. In the summary, you need to provide some of your own ideas.
Research Interests: Privacy-Aware Computing,Wireless and Mobile Security,Fog
Computing,Mobile Health and Safety, Cognitive Radio Networking,Algorithm Design and
Analysis.
You should select papers from the following conferences:
IEEE INFOCOM, IEEE Symposium on security and privacy, ACM CCS, USENIX Security.
Solution
PRIVACY AWARE COMPUTING
Introduction
With the increasing public concerns of security and personal data privacy worldwide, security
and privacy become an important research area. This research area is very broad and covers
many application domains.
The security and privacy aware computing research group actually focuses on
(1) privacy-preserved computing,
(2) Video surveillance, and
(3) secure biometric system.
Now let us briefly discuss the above three groups.
Privacy-preserved Computing
Concerns on the data privacy have been increasing worldwide. For example, Apple was
reportedly fined by South Korea’s telecommunications regulator for allegedly collecting and
storing private location data of iPhone users. The privacy concerns raised by both end-users and
government authorities have been hindering the deployment of many valuable IT services, such
as data mining and analysis, data outsourcing, and mobile location-aware computing.
soo, in response to the growing necessity of protecting data privacy, our research group has been
focusing on developing innovative solutions towards information services --- to support these
services while preserving users’ personal privacy.
Video Surveillance
With the growing installation of surveillance video cameras in both private and public areas, the
closed-circuit TV (CCTV) has been evolved from a single camera system to a multiple camera
system; and has recently been extended to a large-scale network of cameras.
One of the objectives of a camera network is to monitor and understand security issues in the
area under surveillance. While the camera network hardware is generally well-designed and
roundly installed, the development of intelligent video analysis software lags far behind. As
such, our group has been focusing on developing video surveillance algorithms such as face
tracking, person re-identification, human action recognition.
Our goal is to develop an intelligent video surveillance system.
Secure Biometric System
With the growing use of biometrics, there is a rising concern about the security and privacy of
the biometric data. Recent studies show that simple attacks on a biometric system, such as hill
climbing, are able to recover the raw biometric data from stolen biometric template. Moreover,
the attacker may be able to make use of the stolen face template to access the system or cross-
match across databases. Our group has been working on face template protection, multimodality
template protection, and .
This document describes an Unconstrained Endpoint Security System (UEPtSS) that uses passive scanning via the BRO intrusion detection system to fingerprint and catalog unmanaged endpoints on an enterprise network. It analyzes network traffic logs to determine key details about unmanaged devices including operating system, open ports, applications, browsers, and historical malware infections to provide useful context for incident response. The system leverages BRO's scripting framework to detect this information from log files and build an inventory without active scanning. This passive approach avoids potential denial of service issues and works regardless of when devices connect to the network.
Modern information security management best practices dictate that an enterprise assumes full
configuration control of end user computer systems (laptops, deskside computers, etc.). The benefit of this
explicit control yields lower support costs since there are less variation of machines, operating systems,
and applications to provide support on, but more importantly today, dictating specifically what software,
hardware, and security configurations exist on an end user's machine can help reduce the occurrence of
infection by malicious software significantly. If the data pertaining to end user systems is organized and
catalogued as part of normal information security logging activities, an extended picture of what the end
system actually is may be available to the investigator at a moment's notice to enhance incident response
and mitigation. The purpose of this research is to provide a way of cataloguing this data by using and
augmenting existing tools and open source software deployed in an enterprise network.
an efficient spam detection technique for io t devices using machine learningVenkat Projects
The document proposes a machine learning framework to detect spam on IoT devices. It evaluates five machine learning models on a dataset of IoT device inputs and features to compute a "spamicity score" for each device. This score indicates how trustworthy a device is based on various parameters. The results show the proposed technique is effective at spam detection compared to existing approaches.
AN ISP BASED NOTIFICATION AND DETECTION SYSTEM TO MAXIMIZE EFFICIENCY OF CLIE...IJNSA Journal
End users are increasingly vulnerable to attacks directed at web browsers which make the most of popularity of today’s web services. While organizations deploy several layers of security to protect their systems and data against unauthorised access, surveys reveal that a large fraction of end users do not utilize and/or are not familiar with any security tools. End users’ hesitation and unfamiliarity with security products contribute vastly to the number of online DDoS attacks, malware and Spam distribution. This work on progress paper proposes a design focused on the notion of increased participation of internet service providers in protecting end users. The proposed design takes advantage of three different detection tools to identify the maliciousness of a website content and alerts users through utilising Internet Content Adaptation Protocol (ICAP) by an In-Browser cross-platform messaging system. The system also incorporates the users’ online behaviour analysis to minimize the scanning intervals of malicious websites database by client honeypots. Findings from our proof of concept design and other research indicate that such a design can provide a reliable hybrid detection mechanism while introducing low delay time into user browsing experience.
This document summarizes an international journal on information technology and management information systems. It discusses detecting and classifying attacks in a computer network. Existing approaches to intrusion detection include anomaly-based systems, host-based intrusion detection systems (HIDS), and network-based intrusion detection systems (NIDS). A multilayer perceptron (MLP) algorithm is commonly used for intrusion detection but has limitations. The paper proposes a modified apriori algorithm to generate rules for detecting and classifying attacks into categories and types to enable recommending appropriate responses.
This document summarizes an international journal on information technology and management information systems. It discusses detecting and classifying attacks in a computer network. Existing approaches to intrusion detection include anomaly-based systems, host-based intrusion detection systems (HIDS), and network-based intrusion detection systems (NIDS). A multilayer perceptron (MLP) algorithm is commonly used for intrusion detection but has limitations. The paper proposes a modified apriori algorithm to generate rules for detecting and classifying attacks into categories and types to enable recommending appropriate responses.
This document provides a comparative study of existing intrusion detection systems for smartphones. It discusses 5 different intrusion detection approaches: 1) a cloud-based anomaly detection system, 2) a signature-based host-based IDS, 3) a rule-based host-based IDS called AMOXID, 4) an anomaly-based behavioral detection framework called Andromaly, and 5) an anomaly-based cloud-based detection system. It provides an overview of each approach and compares them based on parameters like detection method, positioning, type of analysis, alerts, scalability, pros, and cons. The conclusion is that combining anomaly and signature-based detection could improve attack detection performance for smartphones.
When talk about intrusion, then it is pre- assume
that the intrusion is happened or it is stopped by the intrusion
detection system. This is all done through the process of collection
of network traffic information at certain point of networks in the
digital system. In this way the IDS perform their job to secure the
network. There are two types of Intrusion Detection: First is
Misuse based detection and second one is Anomaly based detection.
The detection which uses data set of known predefined set of
attacks is called Misuse - Based IDSs and Anomaly based IDSs are
capable of detecting new attacks which are not known to previous
data set of attacks and is based on some new heuristic methods. In
our hybrid IDS for computer network security we use Min-Min
algorithm with neural network in hybrid method for improving
performance of higher level of IDS in network. Data releasing is
the problem for privacy point of view, so we first evaluate training
for error from neural network regression state, after that we can get
outer sniffer by using Min length from source, so that we
hybridized as with Min – Min in neural network in hybrid system
which we proposed in our research paper
The document discusses securing industrial IoT (IIoT) applications and devices. It identifies three main attack surfaces: the application, the device, and the network. To secure the application, it recommends using secure APIs, complex passwords, limiting API calls, and continuous deployment. For devices, it suggests securing the SIM card, physical device, and device software through measures like embedded SIMs, firmware updates, and remote management. Finally, it advises limiting voice, SMS, and data services on networks to reduce vulnerabilities. Overall, the document stresses the importance of prioritizing security for IIoT given the increasing threats to connected industrial systems.
1. The document discusses intrusion detection systems and proposes a cluster-based intrusion detection system for wireless sensor networks.
2. It proposes a multi-level intrusion detection architecture with detection at both the cluster head and network-wide levels.
3. The proposed system would detect intrusions through anomaly detection and has been evaluated through a survey of 50 experts in the field.
Deep Learning and Big Data technologies for IoT SecurityIRJET Journal
The document discusses using deep learning and big data technologies to improve security for Internet of Things (IoT) devices and networks. Specifically, it proposes using deep learning models to analyze large amounts of data from IoT sensors to better detect and classify security threats. This can help identify attacks like botnets and distributed denial-of-service (DDoS) attacks. The document also outlines some common IoT security challenges and how approaches like Apache Hadoop, Spark, and Storm can process large volumes of IoT data to improve real-time monitoring and threat prevention.
Today’s networks are larger and more complex than ever before, and
protecting them against malicious activity is a never-ending task.
Organizations seeking to safeguard their intellectual property, protect
their customer identities and avoid business disruptions need to do more
than monitor logs and network flow data; they need to leverage advanced
tools to detect these activities in a consumable manner.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
The document proposes a signature-based intrusion detection system using multithreading. It captures network packets and analyzes them for intrusions by comparing signatures to databases of known attacks. A multithreaded design is suggested to improve performance by processing packets in parallel threads. Agents would be deployed on the network with detection modules that use caching of frequent signatures to speed up analysis. An update module would transfer new frequent signatures to the caches.
Similar to IRJET- Local Security Enhancement and Intrusion Prevention in Android Devices (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
How to Manage Internal Notes in Odoo 17 POSCeline George
In this slide, we'll explore how to leverage internal notes within Odoo 17 POS to enhance communication and streamline operations. Internal notes provide a platform for staff to exchange crucial information regarding orders, customers, or specific tasks, all while remaining invisible to the customer. This fosters improved collaboration and ensures everyone on the team is on the same page.
20CDE09- INFORMATION DESIGN
UNIT I INCEPTION OF INFORMATION DESIGN
Introduction and Definition
History of Information Design
Need of Information Design
Types of Information Design
Identifying audience
Defining the audience and their needs
Inclusivity and Visual impairment
Case study.
Encontro anual da comunidade Splunk, onde discutimos todas as novidades apresentadas na conferência anual da Spunk, a .conf24 realizada em junho deste ano em Las Vegas.
Neste vídeo, trago os pontos chave do encontro, como:
- AI Assistant para uso junto com a SPL
- SPL2 para uso em Data Pipelines
- Ingest Processor
- Enterprise Security 8.0 (Maior atualização deste seu release)
- Federated Analytics
- Integração com Cisco XDR e Cisto Talos
- E muito mais.
Deixo ainda, alguns links com relatórios e conteúdo interessantes que podem ajudar no esclarecimento dos produtos e funções.
https://www.splunk.com/en_us/campaigns/the-hidden-costs-of-downtime.html
https://www.splunk.com/en_us/pdfs/gated/ebooks/building-a-leading-observability-practice.pdf
https://www.splunk.com/en_us/pdfs/gated/ebooks/building-a-modern-security-program.pdf
Nosso grupo oficial da Splunk:
https://usergroups.splunk.com/sao-paulo-splunk-user-group/
In May 2024, globally renowned natural diamond crafting company Shree Ramkrishna Exports Pvt. Ltd. (SRK) became the first company in the world to achieve GNFZ’s final net zero certification for existing buildings, for its two two flagship crafting facilities SRK House and SRK Empire. Initially targeting 2030 to reach net zero, SRK joined forces with the Global Network for Zero (GNFZ) to accelerate its target to 2024 — a trailblazing achievement toward emissions elimination.
Profiling of Cafe Business in Talavera, Nueva Ecija: A Basis for Development ...IJAEMSJORNAL
This study aimed to profile the coffee shops in Talavera, Nueva Ecija, to develop a standardized checklist for aspiring entrepreneurs. The researchers surveyed 10 coffee shop owners in the municipality of Talavera. Through surveys, the researchers delved into the Owner's Demographic, Business details, Financial Requirements, and other requirements needed to consider starting up a coffee shop. Furthermore, through accurate analysis, the data obtained from the coffee shop owners are arranged to derive key insights. By analyzing this data, the study identifies best practices associated with start-up coffee shops’ profitability in Talavera. These findings were translated into a standardized checklist outlining essential procedures including the lists of equipment needed, financial requirements, and the Traditional and Social Media Marketing techniques. This standardized checklist served as a valuable tool for aspiring and existing coffee shop owners in Talavera, streamlining operations, ensuring consistency, and contributing to business success.
A brief introduction to quadcopter (drone) working. It provides an overview of flight stability, dynamics, general control system block diagram, and the electronic hardware.
Understanding Cybersecurity Breaches: Causes, Consequences, and PreventionBert Blevins
Cybersecurity breaches are a growing threat in today’s interconnected digital landscape, affecting individuals, businesses, and governments alike. These breaches compromise sensitive information and erode trust in online services and systems. Understanding the causes, consequences, and prevention strategies of cybersecurity breaches is crucial to protect against these pervasive risks.
Cybersecurity breaches refer to unauthorized access, manipulation, or destruction of digital information or systems. They can occur through various means such as malware, phishing attacks, insider threats, and vulnerabilities in software or hardware. Once a breach happens, cybercriminals can exploit the compromised data for financial gain, espionage, or sabotage. Causes of breaches include software and hardware vulnerabilities, phishing attacks, insider threats, weak passwords, and a lack of security awareness.
The consequences of cybersecurity breaches are severe. Financial loss is a significant impact, as organizations face theft of funds, legal fees, and repair costs. Breaches also damage reputations, leading to a loss of trust among customers, partners, and stakeholders. Regulatory penalties are another consequence, with hefty fines imposed for non-compliance with data protection regulations. Intellectual property theft undermines innovation and competitiveness, while disruptions of critical services like healthcare and utilities impact public safety and well-being.
Best Practices of Clothing Businesses in Talavera, Nueva Ecija, A Foundation ...IJAEMSJORNAL
This study primarily aimed to determine the best practices of clothing businesses to use it as a foundation of strategic business advancements. Moreover, the frequency with which the business's best practices are tracked, which best practices are the most targeted of the apparel firms to be retained, and how does best practices can be used as strategic business advancement. The respondents of the study is the owners of clothing businesses in Talavera, Nueva Ecija. Data were collected and analyzed using a quantitative approach and utilizing a descriptive research design. Unveiling best practices of clothing businesses as a foundation for strategic business advancement through statistical analysis: frequency and percentage, and weighted means analyzing the data in terms of identifying the most to the least important performance indicators of the businesses among all of the variables. Based on the survey conducted on clothing businesses in Talavera, Nueva Ecija, several best practices emerge across different areas of business operations. These practices are categorized into three main sections, section one being the Business Profile and Legal Requirements, followed by the tracking of indicators in terms of Product, Place, Promotion, and Price, and Key Performance Indicators (KPIs) covering finance, marketing, production, technical, and distribution aspects. The research study delved into identifying the core best practices of clothing businesses, serving as a strategic guide for their advancement. Through meticulous analysis, several key findings emerged. Firstly, prioritizing product factors, such as maintaining optimal stock levels and maximizing customer satisfaction, was deemed essential for driving sales and fostering loyalty. Additionally, selecting the right store location was crucial for visibility and accessibility, directly impacting footfall and sales. Vigilance towards competitors and demographic shifts was highlighted as essential for maintaining relevance. Understanding the relationship between marketing spend and customer acquisition proved pivotal for optimizing budgets and achieving a higher ROI. Strategic analysis of profit margins across clothing items emerged as crucial for maximizing profitability and revenue. Creating a positive customer experience, investing in employee training, and implementing effective inventory management practices were also identified as critical success factors. In essence, these findings underscored the holistic approach needed for sustainable growth in the clothing business, emphasizing the importance of product management, marketing strategies, customer experience, and operational efficiency.
Exploring Deep Learning Models for Image Recognition: A Comparative Reviewsipij
Image recognition, which comes under Artificial Intelligence (AI) is a critical aspect of computer vision,
enabling computers or other computing devices to identify and categorize objects within images. Among
numerous fields of life, food processing is an important area, in which image processing plays a vital role,
both for producers and consumers. This study focuses on the binary classification of strawberries, where
images are sorted into one of two categories. We Utilized a dataset of strawberry images for this study; we
aim to determine the effectiveness of different models in identifying whether an image contains
strawberries. This research has practical applications in fields such as agriculture and quality control. We
compared various popular deep learning models, including MobileNetV2, Convolutional Neural Networks
(CNN), and DenseNet121, for binary classification of strawberry images. The accuracy achieved by
MobileNetV2 is 96.7%, CNN is 99.8%, and DenseNet121 is 93.6%. Through rigorous testing and analysis,
our results demonstrate that CNN outperforms the other models in this task. In the future, the deep
learning models can be evaluated on a richer and larger number of images (datasets) for better/improved
results.