Darktrace Antigena is an automated response capability that allows organizations to respond to cyber threats without disrupting normal business operations. As a "digital antibody", Antigena detects threats uniquely identified by Darktrace and automatically takes measured and targeted responses. This includes terminating abnormal connections while leaving normal activities unaffected. Antigena's dynamic boundary enforces each user and device's normal "pattern of life" to combat threats faster than any security team.
This document summarizes the industrial cyber threat landscape as of September 2017. It outlines several high-profile cyber attacks on industrial control systems dating back to 2010, including Stuxnet, Shamoon, BlackEnergy, and CrashOverride. These attacks targeted critical infrastructure like power grids, water treatment plants, and an Iranian nuclear facility. The document also discusses the risks and costs of these incidents, which include physical damage, production shutdowns, and an estimated global cost of cybercrime reaching $6 trillion by 2021. Mitigation strategies are proposed, such as using gateways and managed remote access to block malware and unauthorized access to industrial control networks.
CRASHOVERRIDE Analysis of the Threat to Electric Grid Operations. Cyber-attac...
Dragos, Inc. was notified by the Slovak anti-virus firm ESET of an ICS tailored malware on June 8th, 2017. The Dragos team was able to use this notification to find samples of the malware, identify new functionality and impact scenarios, and confirm that this was the malware employed in the December 17th, 2016 cyber-attack on the Kiev, Ukraine transmission substation which resulted in electric grid operations impact. This report serves as an industry report to inform the electric sector and security community of the potential implications of this malware and the appropriate details to have a nuanced discussion
The document discusses the NetWitness network security platform. It provides situational awareness and deep visibility into network activity to detect advanced threats. When deployed, NetWitness immediately provides insight into what is happening on a network through its NextGen platform. This platform records all network data, filters it, and organizes it into a searchable framework to enable analysis, reporting, and visualization of network traffic. It uses various components and applications to interrogate the data, detect anomalies, and gain intelligence about security issues.
Toward Continuous Cybersecurity with Network Automation
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
SECURITY THREATS IN SENSOR NETWORK IN IOT: A SURVEY
In recent years, wireless sensor network (WSN) is used in several application areas resembling observance, tracking, and dominant in IoTs. for several applications of WSN, security is a crucial demand. However, security solutions in WSN disagree from ancient networks because of resource limitation and process constraints. This paper analyzes security solutions: TinySec, IEEE 802.15.4, SPINS, MiniSEC, LSec, LLSP, LISA, and LISP in WSN. This paper additionally presents characteristics, security needs, attacks, cryptography algorithms, and operation modes. This paper is taken into account to be helpful for security designers in WSNs.
The attackers used a spear phishing campaign targeting RSA employees to gain access to the RSA network. They sent emails appearing to come from a job site with a malicious Excel spreadsheet attachment exploiting Flash vulnerabilities. This allowed the attackers to install backdoors and remote access tools on the network. They were then able to escalate privileges and extract encrypted password-protected files containing user SecurID tokens. The stolen data was suspected to be used in an attempted attack on Lockheed Martin, though their security measures detected the threat. In response, RSA improved security including issuing new SecurID tokens and launching incident response services.
The Top 20 Cyberattacks on Industrial Control SystemsMuhammad FAHAD
Executive Summary
No industrial operation is free of risk, and different industrial enterprises may legitimately have different “appetites” for certain types of risks. Evaluating cyber risk in industrial control system (ICS) networks is difficult, considering their complex nature. For example, an evaluation can consider (explicitly or implicitly) up to hundreds of millions of branches of a complex attack tree modelling of cyberattacks interaction with cyber, physical, safety and protection equipment and processes. This paper was written to assist cyber professionals to understand and communicate the results of such risk assessments to non-technical business decision-makers.
This paper proposes that cyber risk be communicated as a Design Basis Threat (DBT) line drawn through a representative “Top 20” set of cyberattacks spread across a spectrum of attack sophistication. These Top 20 attacks have been selected to represent cyber threats to industrial sites across a wide range of circumstances, consequences and sophistication. Many industrial cyber risk practitioners will find the list useful as-is, while expert practitioners may choose to adapt the list to their more detailed understanding of their own sites’ circumstances.
Advanced Threats in the Enterprise: Finding an Evil in the HaystackEMC
This white paper describes the current advanced threat landscape, shortcomings of anti-virus, and how RSA ECAT fills the gap and helps organizations detect advanced malware.
Insight Brief: Security Analytics to Identify the 12 Indicators of Compromise21CT Inc.
In this security insight brief, 21CT researchers look at the malicious network behaviors that concern organizations the most, and how to use security analytics to find them before damage is done. Understanding these 12 indicators of compromise are critical to identifying a network breach.
This document summarizes the industrial cyber threat landscape as of September 2017. It outlines several high-profile cyber attacks on industrial control systems dating back to 2010, including Stuxnet, Shamoon, BlackEnergy, and CrashOverride. These attacks targeted critical infrastructure like power grids, water treatment plants, and an Iranian nuclear facility. The document also discusses the risks and costs of these incidents, which include physical damage, production shutdowns, and an estimated global cost of cybercrime reaching $6 trillion by 2021. Mitigation strategies are proposed, such as using gateways and managed remote access to block malware and unauthorized access to industrial control networks.
CRASHOVERRIDE Analysis of the Threat to Electric Grid Operations. Cyber-attac...Muhammad FAHAD
Dragos, Inc. was notified by the Slovak anti-virus firm ESET of an ICS tailored malware on June 8th, 2017. The Dragos team was able to use this notification to find samples of the malware, identify new functionality and impact scenarios, and confirm that this was the malware employed in the December 17th, 2016 cyber-attack on the Kiev, Ukraine transmission substation which resulted in electric grid operations impact. This report serves as an industry report to inform the electric sector and security community of the potential implications of this malware and the appropriate details to have a nuanced discussion
The document discusses the NetWitness network security platform. It provides situational awareness and deep visibility into network activity to detect advanced threats. When deployed, NetWitness immediately provides insight into what is happening on a network through its NextGen platform. This platform records all network data, filters it, and organizes it into a searchable framework to enable analysis, reporting, and visualization of network traffic. It uses various components and applications to interrogate the data, detect anomalies, and gain intelligence about security issues.
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
In recent years, wireless sensor network (WSN) is used in several application areas resembling observance, tracking, and dominant in IoTs. for several applications of WSN, security is a crucial demand. However, security solutions in WSN disagree from ancient networks because of resource limitation and process constraints. This paper analyzes security solutions: TinySec, IEEE 802.15.4, SPINS, MiniSEC, LSec, LLSP, LISA, and LISP in WSN. This paper additionally presents characteristics, security needs, attacks, cryptography algorithms, and operation modes. This paper is taken into account to be helpful for security designers in WSNs.
The attackers used a spear phishing campaign targeting RSA employees to gain access to the RSA network. They sent emails appearing to come from a job site with a malicious Excel spreadsheet attachment exploiting Flash vulnerabilities. This allowed the attackers to install backdoors and remote access tools on the network. They were then able to escalate privileges and extract encrypted password-protected files containing user SecurID tokens. The stolen data was suspected to be used in an attempted attack on Lockheed Martin, though their security measures detected the threat. In response, RSA improved security including issuing new SecurID tokens and launching incident response services.
Despite the amazing technologies available today in cybersecurity, organizations still struggle with the most fundamental challenge that has been around for decades: understanding all the devices, users, and cloud services they’re responsible for, and whether those assets are secure.
These slides—based on the webinar hosted by leading IT research firm EMA and Axonius—explain why solving asset management for cybersecurity is becoming increasingly important, and why something so fundamental has quickly risen to the top of CISOs priority lists.
Autonomic Anomaly Detection System in Computer Networksijsrd.com
This paper describes how you can protect your system from Intrusion, which is the method of Intrusion Prevention and Intrusion Detection .The underlying premise of our Intrusion detection system is to describe attack as instance of ontology and its first need is to detect attack. In this paper, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-governing: self-labeling, self-updating and self-adapting. Our structure employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies.
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
Current Studies On Intrusion Detection System, Genetic Algorithm And Fuzzy Logicijdpsjournal
This document summarizes a research paper on current studies of intrusion detection systems using genetic algorithms and fuzzy logic. The paper presents an overview of intrusion detection systems, including different techniques like misuse detection and anomaly detection. It discusses using genetic algorithms to generate fuzzy rules to characterize normal and abnormal network behavior in order to reduce false alarms. The paper also outlines the dataset, genetic algorithm approach, and use of fuzzy logic that are proposed for the intrusion detection system.
Panda Adaptive Defense 360 - Cyber Extortion GuidePanda Security
What is Cyber Extortion? How do cybercriminals use ransomware for attacks? What to do if you are a victim of cyber extortion?
Panda Security answers all these questions and gives you some recommendations and advises to prevent Cyberattacks in this Practical Security Guide to Prevent Cyber Extortion.
We, at Panda, have developed the first solution that guarantees continuous monitoring of all the active processes: Adaptive Defense 360
http://promo.pandasecurity.com/adaptive-defense/en/
Fortalecimiento de la seguridad combinando las capacidades de analíticos sobre logs y paquetes de red, además de las capacidades avanzadas de detección de malware,
REAL-TIME INTRUSION DETECTION SYSTEM FOR BIG DATAijp2p
The objective of the proposed system is to integrate the high volume of data along with the important
considerations like monitoring a wide array of heterogeneous security. When a real time cyber attack
occurred, the Intrusion Detection System automatically store the log in distributed environment and
monitor the log with existing intrusion dictionary. At the same time the system will check and categorize the
severity of the log to high, medium, and low respectively. After the categorization, the system will
automatically take necessary action against the user-unit with respect to the severity of the log. The
advantage of the system is that it utilize anomaly detection, evaluates data and issue alert message or
reports based on abnormal behaviour.
IRJET- Local Security Enhancement and Intrusion Prevention in Android Dev...IRJET Journal
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 provides guidance for lawyers on data security issues and how to help clients meet data security standards. It discusses how lack of security knowledge is common among both personal and enterprise computer users. Various threats like viruses, worms, Trojans, bots, and spyware/adware are described. Examples of data security risks include loss of portable devices containing personal information, insecure home networks that employees access for work, and insecure disposal of physical documents and digital media. The document advises evaluating security controls and investing in tools to detect breaches and audit compliance.
Part 3 ApplicationEnd-User Security Recommendations.docxdanhaley45372
Part 3: Application/End-User Security Recommendations
Introduction
A robust network security strategy is one that actively involves the entire stakeholders of the system. The network administrator has the responsibility of ensuring that best practices in information security management are implemented throughout the entirety of the system they oversee. Threats to a system exist both within and outside an organization. This necessitates the need for a comprehensive security strategy that can cover all those potential threats. Information security threats are of a dynamic nature and the network administrator should take this consideration to ensure that they are always on top of any emerging threats. System vulnerabilities should be sought and effectively sealed and this should be a regular task.
End User Security Recommendations
Best practice in network security will require that the users and the firm abide by the following:
• Training and awareness – all employees of the company should have a firm grasp of matters pertaining network security. This will come through the training that should be offered by the company. The training should involve how to spot and identify threats, how to combat them, and how to handle them should they occur. As new threats emerge, the firm will need to create a continuous awareness program to inform its employees on them.
• Effective monitoring program – even after training has been done, this is not reason enough to believe employees will adhere to the lessons learnt. As such, the IT personnel should be empowered to conduct random checks on the security behavior of the firm’s employees. This will help in identifying potential weak spots.
• Unique user credentials – each and every employee that has been granted use of computer resources should do so with their own unique username and a password that should not be shared with any other user. The password should be complex enough that no one could possibly guess. The user should avoid using passwords from familiar objects or people. A strong password should have a mix of alphanumeric and special characters. For every activity a user does on any computer, they will be required to use their own unique credentials. This should leave an audit that can be followed should there be an incident.
• Automatic logoff – it is possible that a user might leave a computer without logging out from their session. This opens the possibility that another user might access resources using the logged in credentials. This could be devastating should the unauthorized have malicious intent and the logged on credentials have advanced permissions. Automatic logoff should be set to happen after a given period of time. This should especially happen after the end of prescribed business hours.
• Regular event log audits – event logs are very important when it comes to monitoring the performance of a given system. They can also be used to spot any anomalies within the system. Event log.
CylancePROTECT is a next-generation antivirus product that leverages artificial intelligence to detect and prevent malware from executing in real time without requiring daily signature updates or an internet connection. It uses automated static code analysis and machine learning to evaluate files and determine if they are malicious within 100 milliseconds to control execution. This provides a more effective approach than traditional antivirus methods that rely on outdated signature-based detection and post-infection analysis.
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.
Cylance introduces CylancePROTECT as a next-generation antivirus (NGAV) that uses artificial intelligence and machine learning instead of traditional signature-based detection. CylancePROTECT analyzes millions of characteristics from files to determine if they are malicious in under 100 milliseconds, allowing it to prevent execution of bad files. It does not require daily updates like traditional antivirus and can operate autonomously without an internet connection. CylancePROTECT aims to significantly improve malware detection and protection compared to 30-year old antivirus technologies.
This document describes a proposed artificial neural network based intrusion detection system. It uses a multilayer perceptron neural network architecture trained on the KDD Cup 99 intrusion detection dataset. The system monitors network traffic in real-time, extracts features from network packets, and classifies the traffic into six categories using the neural network. It is able to detect both known and unknown attacks. The system aims to improve upon traditional signature-based intrusion detection systems.
Self-protection in a clustered distributed system refers to the system's ability to detect illegal behaviors and fight back against intrusions using countermeasures. This is based on structural knowledge of the cluster and applications. This knowledge allows detection of known and unknown attacks if an illegal communication channel is used. Any attempt to use an undeclared channel is trapped and an automatic recovery procedure is executed. Legal channels are calculated from the system architecture and used to generate protection rules forbidding unspecified channels. This minimizes system perturbation while providing fast reaction, and automates security configuration when the system evolves.
The document discusses network security and provides information on various types of network security measures. It defines network security as an organization's strategy to secure all network traffic and assets by managing access to the network. It also describes 14 common types of network security, including antivirus software, firewalls, email security, mobile device security, and network access control. The types are defined in 1-2 sentences each. The document aims to provide an overview of network security for organizations to protect their networks and reputation from increasing cyber threats.
Self-protection in a clustered distributed system refers to the system's ability to detect illegal behaviors and launch countermeasures against intrusions. It is based on structural knowledge of the cluster and applications to detect known and unknown attacks using unauthorized communication channels. As distributed systems have unavoidable security vulnerabilities, a promising approach is implementing self-protection capabilities. This involves automatically configuring security components as the system evolves, detecting deviations from legal communication channels, and isolating compromised machines in the cluster. The goal is to spot intruders targeting various protocols, trigger countermeasures to isolate resources when illegal behavior is found, and prevent further damage from silent attacks.
ForeScout CounterACT is a network access control platform that provides visibility, security, and productivity for networks. It identifies devices on the network, including managed and unmanaged devices, and enforces granular policies to automate control of network access. CounterACT is easy to deploy with no software or agents required, and it integrates with existing IT infrastructure. It offers comprehensive network visibility, security, and policy-based access control.
Tools and Mechanisms for Network Security in an Organization.
Physical Security, Administrative Security and Technical Security measures have been described.
Security Testing Tools are Nessus, THC Hydra, Kismet, Nikto, WireShark and NMAP.
1) A global ransomware attack called WannaCry spread to over 150 countries using hacking tools stolen from the NSA. It exploited a Windows vulnerability that Microsoft had already released a patch for.
2) The attack was well-coordinated and planned to spread quickly by searching for vulnerable systems within networks. Once it infected one system, it could spread laterally across the network.
3) Future attacks are expected to be even more sophisticated as hackers adapt their techniques. Companies need to ensure timely patching of systems and careful management of supply chain security to avoid falling victim.
The recent global cyber attack using WannaCry ransomware reminds us that proper information security hygiene and appropriate back-up management and software patching protocols are critical to attack prevention and loss minimization.
How To Learn The Network Security
Slide berikut merupakan slide yang berisikan dasar-dasar bagi kita dalam memahami konsep keamanan jaringan komputer, baik dari sisi inftrastruktur, teknologi dan paradigma bagi pengguna.
Materi yang diberikan sudah disusun oleh Pakar yang merupakan Trainer CEH dan memang berkompeten dibidang keamanan jaringan.
Slide ini saya dapatkan dari beliau saat mengikut training Certified Computer Security Officer (CCSO) dan Certified Computer Security Analyst (CCSA) dari beliau.
Semoga bermanfaat sebagai acuan bagi kita untuk belajar tentang keamanan jaringan komputer.
Terimakasih
Network security involves implementing multiple layers of defenses to protect a network from threats. It includes technologies like firewalls, antivirus software, and intrusion detection systems to manage access and detect malware and exploits. As networks increasingly face hacking threats, strong network security tools are essential for organizations to protect their systems, data, and reputation. Network security strategies aim to authorize only legitimate users while blocking malicious actors from harming the network.
Traps advanced endpoint protection from Palo Alto Networks prevents cyber breaches and ransomware attacks through a unique multi-method prevention approach. It blocks known and unknown malware, exploits, and zero-day threats before they can compromise systems using threat intelligence from WildFire and local machine learning analysis of files. Traps also prevents exploit techniques used by attacks and has received industry recognition for its effectiveness in replacing traditional antivirus solutions.
Cybersecurity Devices and Technologies.pptxAnanta Khare
There is no single security appliance or piece of technology that will solve all the network security needs in an organization.
We must consider what tools will be most effective as part of our security system.
IntroSpect User and Entity Behavior Analytics (UEBA) uses AI-based machine learning to spot changes in user behavior that often indicate inside attacks that have evaded perimeter defenses. Security teams are armed with insights into malicious, compromised or negligent users, systems and devices – cutting off the threat before it does damage.
2. 1
Introduction
As cyber-attackers use increasingly sophisticated technologies to penetrate and propagate within networks,
the need for automated response to combat these fast-moving adversaries has grown. Security teams cannot
keep up with a threat landscape that is evolving 24/7, and which includes automated attacks, like ransomware,
that can seriously jeopardize an organization’s infrastructure within as little as 20 minutes.
Darktrace Antigena is an automated response capability, which allows organizations to ‘fight back’ against
cyber-threats – without disruption to their day-to-day business activity. Working in conjunction with Darktrace’s
core detection technology, Antigena replicates the functions of antibodies in the human immune system by
intelligently locating and neutralizing threats.
As a ‘digital antibody’, Antigena completes the end-to-end functionality of the Enterprise Immune System by
automatically detecting and responding to threats that have been uniquely detected. Thanks to the nuanced
understanding of ‘normal’ and ‘abnormal’ behaviors, it is capable of taking measured and targeted
responses, disrupting threats without interrupting normal business processes, and allowing security teams
time
Benefits
Respond to threats faster than any
security team can
Take automated, measured, and targeted
action
No rules, no signatures
Does not disrupt day-to-day business
Frees up resources and people
Fully configurable
“It is our belief that [Antigena’s]
ability to drive security actions
based on observed behavior
is critical to protecting
organizations against
sophisticated threats. For
businesses where alerting
operations staff is too passive
and slow, the Antigena API allows
security teams to automate
responses via firewalls, endpoint
software and management
consoles.”
Eric Ogren, 451 Research Senior Analyst
3. 2
Normal ‘Pattern of Life’
The normal ‘pattern of life’ of devices and
users are known to Darktrace. The
historical actions of a device or user, and
those of its peers, are calculated and
used to determine a level of normality for
every connection made.
Anomalous Activity
Darktrace identifies highly anomalous
activity associated with a rare file
download from an unusual source and
subsequent beaconing to an external
machine. Unknown malware has been
downloaded and is reporting back to a
control center.
Enforced Containment
Antigena enforces the device’s ‘pattern of
life’. All connections outside of its normal
behavior are terminated. Normal activity
from the machine is left unaffected and
the user continues to work unaware that
preventative action has been placed on
their device.
90% 98% 90% 98%90% 98%
160%
146%
139%
Illustrative Example of Antigena Response
How Does Antigena Work?
Antigena works in conjunction with Darktrace (Core), which lies at the heart of the Enterprise Immune
System approach, and is powered by Darktrace’s proprietary mathematics and machine learning. As a result,
organizations must have a core Darktrace appliance or appliances installed within the network before activating
Antigena.
When Darktrace has identified activity that has been deemed threatening or highly anomalous, Darktrace
Antigena is triggered and generates a response to that activity in real time, which depends on the severity of
the incident.
Examples of actions taken by Antigena may include:
• Stopping or slowing down activity related to a specific threat
• Quarantining or semi-quarantining users, systems, and/or devices
• Marking specific pieces of content, such as email, for further investigation or tracking
The precision with which Antigena operates means that interruption to normal business processes is avoided.
Instead, Antigena’s self-learning capability allows it to enforce the normal ‘pattern of life’ by slowing and
mitigating threats, giving security teams time to investigate the evolving situation and take further action.
Darktrace Antigena is fully configurable, allowing for varying degrees of automation, according to your
organization’s appetite. For example, users may choose to ‘validate’ Antigena responses, before they are put
into effect. This allows users to control and gain confidence in the judgements that Antigena makes, while
saving time on the investigation and contextualization of the threat.
4. 3
Darktrace Antigena Framework
The Darktrace Antigena Framework provides a layer of intelligent decision-making and response, according
to the known ‘pattern of life’ of the enterprise. Darktrace’s Enterprise Immune System upstreams the subtle
changes in behavior witnessed in anomalous activity to the Framework, enabling it to make targeted decisions
about the most appropriate way to respond to identified threats. Antigena is therefore capable of making precise
decisions that will return an anomalous user or device back to its normal behavior profile.
This methodology ensures that normal working activity is permitted, while potentially malicious actions are
prevented, effectively eliminating false positives. Antigena creates a dynamic boundary, which is automatically
personalized to each user and device on a network.
The Antigena Framework interacts with your network via one or more modular elements that can communicate
with aspects of your existing infrastructure. The Framework is self-aware, constructing its decision-making
process around its existing capabilities. In this way, Antigena is fully modularized, and can be expanded with
new abilities as your architecture develops.
Dynamic Boundary
Many traditional proactive security devices fail
because they rely on static restrictions of behavior
that apply to large groups of users and devices.
Security professionals are forced into making these
restrictions widely permissive to accommodate a few
individual users within the group. The administrative
overhead, cost, and time involved in tailoring policies
means that it is often easier to open permissions to
far more users than is required.
Antigena solves this problem by providing a dynamic
boundary to a user’s behavior. Just as no single user
is alike, no behavior profile is alike either.
Feedback Loop
Antigena monitors the actions that it produces to
better understand an organization’s threat surface
area.
Determined attackers or insider elements will not
stop at the first attempt. Malicious software often
has many fall back routines to run in the event that it
is prevented from functioning.
Antigena and its modules will send the results of
failed attempts back into the Darktrace Enterprise
Immune System, producing further insight into
anomalous activity. It enables Darktrace to learn,
not just from normal activity, but from activity that
has already been prevented. In this way, undesirable
behavior learned in one part of the network can
better inform the choices made across the entirety
of the network.
Darktrace Antigena Modules
The Antigena Framework interacts with your network via one or more modular elements that can communicate with
aspects of your existing infrastructure. These modules are Antigena Network, Antigena Internet, and Antigena Email.
Antigena
Internet
Antigena
Email
Antigena
Network
Regulates user and machine access
to the internet and beyond
Regulates machine and network
connectivity and user access
permissions
Regulates inbound and outbound
email behavior and content
5. 4
Antigena Internet regulates and controls user and
device internet connectivity in accordance with the
Antigena Framework and Darktrace’s behavioral
awareness of your network, users, and devices.
The Antigena Internet module exists as one or more
physical appliances that sits in-line with an internet
egress gateway or an element in an existing web
proxy infrastructure. Devices required to access
the internet can have their internet-bound traffic
transparently observed or be explicitly configured to
browse via Antigena Internet.
Darktrace will upstream detected anomalous
behaviors to the Antigena Framework, which may
instruct the Internet module to automatically provide
intelligent preventative actions on internet-bound
activity. The reactions can be produced based on
an internal machine’s general behavior – not just its
internet activity.
Use Cases:
• Stop malware from being accidentally or
intentionally downloaded from the internet
• Prevent the upload of sensitive data to the internet
• Block users from visiting dangerous or suspicious
websites
e Benefits
Dynamic boundary enforced for internet
usage
Enforces a user or device’s ‘pattern of life’
Optional SSL inspection provides
increased insight
Highly anomalous connections can be
blocked before they reach the end user
Can selectively operate in prompt mode
to seek user acknowledgement before
proceeding
Antigena Internet
6. 5
Antigena Network is a software component that
permits interaction between the core Antigena
Framework and elements within a protected network.
It is available for installation on existing Darktrace
devices and requires no additional hardware.
From the main Darktrace appliance, the Antigena
Network module provides the ability to connect to
internal systems to perform defensive actions,
designed to maintain a normal ‘pattern of life’ on
devices with a high level of anomalous activity and
protect the network at large.
Darktrace’s unique understanding of ‘normal’
communication between machines is constantly
evolving, so the more information it sees, the better
understanding it has of what is anomalous.
If a device within an organization is seen to be
displaying sufficient levels of abnormality, Antigena
may elect to emit signals to that device that terminate
connections deemed to be highly unusual for the
device and its peer group in that specific context.
However, the immediate action is specific enough
that, while the abnormal connection is slowed or
terminated, other processes can continue, allowing
business proceedings to continue uninterrupted.
The actions that Antigena performs are all reported
in Darktrace’s Threat Visualizer and can be revoked
at any point by your security team or infrastructure.
Use Cases:
• Triggered by a suspicious connection to foreign IP
address (detected by Darktrace)
• Slow a known device downloading large amounts
of data it does not normally access
• Prevent a device from ' communicating' to an
unknown location
• Stop the transfer of secure files to an unauthorized
user
e Benefits
Actions are performed by the
administrative interface of an existing
Darktrace appliance or optionally by a
dedicated appliance
Connections can be terminated from
internal-to-internal and internal-to-external
communications
Creates Dynamic Boundary for inter-
machine networking
Network layer interactions frequently
require no integration within an
organization’s infrastructure
Available for a four-week Proof of Value
trial
Antigena Network
7. 6
Antigena Email is an appliance that sits at the border
of your email infrastructure. As such, it is capable of
interacting with inbound and outbound mail transit
and message content.
By progressive learning techniques, the Antigena
Email module will work with Darktrace’s Enterprise
Immune System to build up an understanding of
patterns of email communication and develop a
complex mesh of ‘likelihood of correspondence’
that identifies the fingerprints of legitimate email.
Each inbound email is compared against known
and frequent correspondence to establish a level of
trust. The Antigena Framework has the ability to flag
suspicious emails, as well as to sanitize attachments
and links as they pass through the Antigena Email
module, neutralizing any harmful content.
Use Cases:
• Prevent phishing or spear-phishing campaigns, by
preventing harmful links from reaching the target
• Stop confidential information from being
intentionally shared to recipients without clearance
• Block employees from sending sensitive
information to a personal account
e Benefits
Dynamic boundary enforced for
communications
Stop phishing based on mathematical
corre on en rofil ng
Feedback loop provides Darktrace with a
dynamic threat surface area unique to your
organization
Highly anomalous emails can be blocked
before they reach the end user
Sanitation of mail-borne content
Works in conjunction with your existing
mail server
Antigena Email
8. About Darktrace
Darktrace is a world-leading cyber-threat defense company. Its multi-award-winning Enterprise
Immune System technology automatically detects and responds to emerging threats, powered
by machine learning and mathematics developed by specialists from the University of Cambridge.
Without using rules or signatures, Darktrace models the ‘pattern of life’ of every device, user
and network within an organization, identifying and mitigating cyber-threats before damage is
done. Darktrace’s self-learning technology has been deployed globally and across all sectors,
including energy, retail, telecommunications, manufacturing, financial services and healthcare.
The company is headquartered in San Francisco and Cambridge, UK, with over 20 global offices
including London, New York, Milan, Mumbai, Paris, Singapore, Sydney, Tokyo and Toronto.
Contact Us
US: +1 (415) 243 3955
Europe: +44 (0) 1223 394 100
APAC: +65 6248 4516
info@darktrace.com
www.darktrace.com
Conclusion
It is becoming impossible to manually keep up with this new era of computer-speed threats, irrespective of how
large your security team is. Automated response is the next step in ensuring that cyber defense keeps pace with
these new attackers, and take preventative actions as threats develop.
By using unique machine learning and mathematics, Darktrace can detect in-progress threats without requiring
rules and signatures, which are proven to fail when faced with machine-on-machine attacks and sophisticated
hackers.
Antigena represents the first automated, self-defending system that allows the Enterprise Immune System to
take direct action against specific threats – without disrupting your organization. It reduces response time and
enables better, more efficient risk mitigation, irrespective of the type of threat encountered.
"We believe [Antigena] represents an important step in behavior analytics
evolving to an active defense that traditional systems cannot match.”
Eric Ogren, 451 Research Senior Analyst