I want you to Read intensively papers and give me a summary for ever.pdf

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 biometric de-duplication. The goal is to develop a secure biometric
system.
Now Let us bring some idea of this from conference paper found in usinex.org,
We will talk more about Privacy-Aware Location Sensor Networks
Advances in sensor networking and location tracking technology enable location-based
applications but they also create significant privacy risks. Privacy is typically addressed through
privacy policies, which inform the user about a service provider's data handling practices and
serve as the basis for the user's decision to release data. However, privacy policies require user
interaction and offer little protection from malicious service providers.
This paper addresses privacy through a distributed anonymity algorithm that is applied in a
sensor network, before service providers gain access to the data. These mechanisms can provide
a high degree of privacy, save service users from dealing with service providers' privacy
policies, and reduce the service providers' requirements for safeguarding private information.
Introduction
Sensor network technology promises a vast increase in automatic data collection capabilities
through efficient deployment of tiny sensing devices. Arrays of sensors could be deployed
alongside roads to monitor traffic patterns or inside buildings to sense contextual information for
adaptive computing services. In particular, there is great interest in location tracking systems,
which determine the position of users for location-based services. We foresee that sensor
network technology decreases the cost of such systems by replacing cables with multi-hop radio
communications and allowing in-network processing of data. While these technologies offer
great benefits to users, they also exhibit significant potential for abuse. Particularly relevant are

privacy concerns, since sensor network technology provides greatly expanded data collection
capabilities. A common approach addresses privacy concerns at the database or location server
layer--after data has been collected.
For example, privacy policies govern who can use an individual's data for which purposes .
Furthermore, data perturbation or anonymity mechanism provide access to data without
disclosing privacy sensitive information. However, data is difficult to protect once it is stored on
a system.
In the past, private data has been inadvertently disclosed over the Internet and companies have
distributed data in violation of their own privacy policies. In addition, data theft and distribution
through company insiders poses a serious challenge. Such approaches also do not address the
risks that an adversary circumvents the location server and directly collects data from the
location tracking system. This paper leverages sensor nodes' data processing capabilities to
enhance privacy through distributed, in-network anonymity mechanisms. These mechanisms are
applied before data leaves the sensor network and can be stored in a location server; thus,
databases and locations servers are removed from the trusted computing base, meaning users
only need to trust the sensor network itself. A third party, independent from the data consumers,
could install and service the network to establish user trust. The paper concentrates on location
sensor networks, since location information is especially privacy sensitive and potentially
specific enough to reveal the identity of individuals. Specifically, the paper contributes the
following key ideas:
To achieve some secured solutions we can look on to the following approaches
A network is needed that provides near real-time location information with the properties that it
preserves k-anonymity with respect to the described attack model while still delivering useful
data. To achieve this goal, we take the following approach.
Approach
Data cloaking.
The sensor network perturbs the sensed location data so that it meets the k-anonymity criterion.
Ideally, the network applies only the minimum necessary perturbation so that the data retains its
usefulness for a large number of applications.
Hierarchical aggregation.
Network nodes organize distribution of sensed location data through a spanning tree. Multiple
nodes throughout the spanning tree, the coordination leaders (CL), cloak data so that no single
entity has a complete view of the original data. The hierarchy should reflect the spatial
characteristics of the area. For example, it could be organized into cubicles, rooms, floors, and
buildings.
Secure and unobservable communications.

Nodes communicate with encrypted and authenticated data packets (e.g., using the SPINS
protocols to prevent eavesdropping and active attacks. In addition, data transmissions are
periodic and independent from sensor readings to protect against traffic analysis.
NOW 2nd TOPIC
Wireless and mobile security
Mobile security is the protection of smartphones, tablets, laptops and other portable computing
devices, and the networks they connect to, from threats and vulnerabilities associated with
wireless computing. Mobile security is also known as wireless security.
Securing mobile devices has become increasingly important in recent years as the numbers of the
devices in operation and the uses to which they are put have expanded dramatically. The problem
is compounded within the enterprise as the ongoing trend toward IT consumerization is resulting
in more and more employee-owned devices connecting to the corporate network.
SearchSecurity.com's 2012 enterprise mobile security survey polled 487 IT security
professionals and IT managers. The survey found the following top five mobile security
concerns:
1. Device loss was the top concern. If an employee leaves a tablet or smartphone in a taxi cab or
at a restaurant, for example, sensitive data, such as customer information or corporate intellectual
property, can be put at risk. According to Marcus Carey, a security researcher at Boston-based
compliance auditing firm Rapid7 Inc., such incidents have been behind many high-profile data
breaches.
2. Application security was the second-ranking concern. One problem is mobile apps that request
too many privileges, which allows them to access various data sources on the device. According
to Domingo Guerra, president and co-founder of San Francisco-based Appthority Inc., many
mobile apps are built with ties to advertising networks, which makes contacts, browsing history
and geolocation data extremely valuable to application developers. As Guerra put it,
"Developers want to monetize, consumers want free apps and then ad networks will pay
developers to get all of that juicy data from their users." According to survey respondents,
leaked corporate contacts, calendar items and even the location of certain executives could put
the company at a competitive disadvantage.
3. Device data leakage was the third-ranking mobile security issue. Nearly all of the chief
concerns identified in the mobile security survey, from data loss and theft to malicious
applications and mobile malware, are sources of data leakage. While most corporate access
privileges on mobile devices remain limited to calendar items and email, new mobile business
applications can tap into a variety of sources, if the enterprise accepts the risks, said mobile
security expert Lisa Phifer. Increased corporate data on devices increases the draw of
cybercriminals who can target both the device and the back-end systems they tap into with

mobile malware, Phifer said. "If you're going to put sensitive business applications on those
devices, then you would want to start taking that threat seriously."
4. Malware attacks were the fourth-ranking mobile security concern. A new report from Finland-
based antivirus vendor F-Secure Corp. found the vast majority of mobile malware to be SMS
Trojans, designed to charge device owners premium text messages. Experts say Android devices
face the biggest threat, but other platforms can attract financially motivated cybercriminals if
they adopt Near Field Communications and other mobile payment technologies.
5. Device theft was fifth on the list of top concerns. Smartphone theft is a common problem for
owners of highly coveted smartphones such as the iPhone or high-end Android devices. The
danger of corporate data, such as account credentials and access to email, falling into the hands
of a tech-savvy thief, makes the issue a major threat to the IT security pros who took the survey.
NOW 3rd TOPIC
FOG COMPUTING
Fog computing is also known as fogging, is a distributed computing infrastructure in which some
application services are handled at the network edge in a smart device and some application
services are handled in a remote data center in the cloud. The goal of fogging is to improve
efficiency and reduce the amount of data that needs to be transported to the cloud for data
processing, analysis and storage. This is often done for efficiency reasons, but it may also be
carried out for security and compliance reasons.
In a fog computing environment, much of the processing takes place in a data hub on a smart
mobile device or on the edge of the network in a smart router or other gateway device. This
distributed approach is growing in popularity because of the Internet of Things (IoT) and the
immense amount of data that sensors generate. It is simply inefficient to transmit all the data a
bundle of sensors creates to the cloud for processing and analysis; doing so requires a great deal
of bandwidth and all the back-and-forth communication between the sensors and the cloud can
negatively impact performance. Although latency may simply be annoying when the sensors are
part of a gaming application, delays in data transmission can be life-threatening if the sensors are
part of a vehicle-to-vehicle communication system or large-scale distributed control system for
rail travel.
The term fog computing is often associated with Cisco. "Cisco Fog Computing" is a registered
name; “fog computing” is open to the community at large. The choice of the word "fog" is
meant to convey the idea that the advantages of cloud computing can and should be brought
closer to the data source. (In meteorology, fog is simply a cloud that is close to the ground.)
NOW 4th TOPIC
MOBILE HEALTH AND SAFETY
Introduction

Since mobile phones started to become widely used in the 1990s, there have been some safety
concerns regarding the potential effects of the radio waves they produce.
These radio waves are a type of low energy 'non-ionising' radiation – a type of radiation that
also includes visible light, microwaves and infrared radiation – and concerns have been
expressed that prolonged or frequent exposure to this radiation may increase a person's risk of
health problems such as cancer.
Most current research suggests it is unlikely mobile phones or base stations increase the risk of
health problems, but it is acknowledged this evidence is based on use of mobile phones over the
last 20 years. There is still some uncertainty about possible health effects from using a phone for
longer than this.
Therefore as a precautionary measure, you may wish to follow some simple recommendations
for mobile phone safety to lower your exposure to radio waves if you have any concerns.
For now, using a mobile phone while driving is considered the biggest health risk posed by
mobile phones. It's estimated that you are around four times more likely to have an accident
when using a hand-held mobile phone, which is why it is now illegal to do so. It is also safer not
to use a hands-free phone while driving.
Read more about the risks of mobile phone use.
Mobile phone use in the UK
Ofcom, the independent regulator for the communication industry, says around 94% of adults in
the UK own or use a mobile phone.
Mobile phones are more than just a business tool. They are now a popular means of
communication, a safety aid and an essential part of many people's lives.
There are around 54,000 mobile phone base stations in the UK according to figures from 2011.
Base stations are transmitters (sometimes called masts) that use radio waves to communicate
with mobile phones.
What research has been done into their safety?
There has been a huge amount of scientific research into health effects of mobile phone use since
the 1990s.
Large reviews of published research by the Advisory Group on Non-Ionising Radiation (AGNIR;
part of Public Health England) and research carried out as part of the Mobile
Telecommunications and Health Research Programme (MTHR) have not found convincing
evidence that radio waves from mobile phones cause health problems.
However, further research is still needed as there is not currently enough evidence concerning
any potential health impact from long-term exposure (using a mobile phone for more than 20
years).
How safe are mobiles?

Concerns over the safety of mobile phones have been around for a number of years but, as yet,
there is no definitive evidence to prove that either using a mobile phone or that base stations
have any long term health effects. With mobile phones only being around for a short while it
may take some time before sufficient data is available to decide one way or another. Currently
(2012) the UK Health Protect Agency’s advice only extends to discouraging children for
“excessive use” of mobile phones.
Whilst people talk about mobile phones giving off radiation and quite naturally get concerned
with thoughts of nuclear reactors and weapons it is worth mentioning that, unlike these things,
mobile phones do not give off ionizing radiation, that is the kind of radiation that breakdowns
DNA and causes cancer. The type of radiation given off by mobiles is more like that from a
microwave oven and whilst they have their own safety aspects the food doesn’t come out
radioactive.
Recently the siting of base stations, especially near schools, has been an issue with both parents
and governors. However, this needs to be compared to the exposure from handheld mobiles
which is hundreds of times more powerful due to being used close to the body, with no proven ill
effects, than the emissions from a base station antenna high up on a mast or building.
NOW 5th TOPIC
Cognitive Radio Networking
Cognitive (or smart) radio networks like xG’s xMaxsystem are an innovative approach to
wireless engineering in which radios are designed with an unprecedented level of intelligence
and agility. This advanced technology enables radio devices to use spectrum (i.e., radio
frequencies) in entirely new and sophisticated ways. Cognitive radios have the ability to monitor,
sense, and detect the conditions of their operating environment, and dynamically reconfigure
their own characteristics to best match those conditions.
Using complex calculations, xMax cognitive radios can identify potential impairments to
communications quality, like interference, path loss, shadowing and multipath fading. They can
then adjust their transmitting parameters, such as power output, frequency, and modulation to
ensure an optimized communications experience for users.
According to NSF report 2009,
In the past ten years, we have witnessed a dramatic growth in wireless communication due to the
popularity of smart phones and other mobile devices. As a result, the demand for commercial
spectrum has been skyrocketing. For instance, AT&T projects a 5000% increase in data usage in
the next three years, Yankee Group predicts 29-fold increase in US mobile data traffic from 2009
to 2015, and CTIA estimates that U.S. cellular companies need at least 800MHz more spectrum
over the next 6 years. Clearly limited spectrum is a crucial impediment to continued growth of
commercial wireless services. Similarly, we are seeing increasing demand for unlicensed

bandwidth, due to the continuing growth of as WiFi, and emergence of application domains,
such as sensor networks for safety applications, home automation, smart grid control, medical
wearable and embedded wireless devices, and entertainment systems.
Cognitive radios are widely viewed as the disruptive technology that can radically improve both
spectrum efficiency and utilization. Cognitive radios are fully programmable wireless devices
that can sense their environment and dynamically adapt their transmission waveform, channel
access method, spectrum use, and networking protocols as needed for good network and
application performance. One of the applications of cognitive radio is more efficient, flexible,
and aggressive dynamic spectrum access. The research community has made significant progress
in addressing the many research challenges associated with cognitive networks
Research Challenges
With the exception of unlicensed spectrum which tend to be more heterogeneous, most spectrum
bands are used in a fairly homogeneous fashion, i.e. the network uses a single (or close related)
technology and it is designed by a single organization. In contrast, cognitive networks are
inherently heterogeneous. This fundamental difference raises many significant challenges, as
identified in a recent NSF-sponsored workshop on “Future Directions in Cognitive Radio
Network Research”:
In a Nutshell
Cognitive networks offers the promise of significantly improving both spectrum efficiency and
utilization. In the last few years, significant research progress has been made in supporting the
key functions needed in a cognitive network and in the development of cognitive radios but
many challenges remain. This report identifies several critical research areas including cognitive
networking as a system, the interactions between technology and policy, and cognitive
networking.
We also found that we need new tools, including cognitive networking testbeds, that can be used
to evaluate the properties of cognitive networks. Finally, we identified some near term
opportunities for high-impact research, such as the unlicensed access to TV white spaces.
NOW LAST 6th TOPIC
Algorithm Design and Analysis
Algorithm design is a specific method to create a mathematical process in solving problems.
Applied algorithm design is algorithm engineering.
Algorithm design is identified and incorporated into many solution theories of operation
research, such as dynamic programming and divide-and-conquer. Techniques for designing and
implementing algorithm designs are algorithm design patterns,[1] such as template method
pattern and decorator pattern, and uses of data structures, and name and sort lists. Some current
day uses of algorithm design can be found in internet retrieval processes of web crawling, packet

routing and caching.
Mainframe programming languages such as ALGOL (for Algorithmic language), FORTRAN,
COBOL, PL/I, SAIL, and SNOBOL are computing tools to implement an "algorithm design"...
but, an "algorithm design" (a/d) is not a language. An a/d can be a hand written process, e.g. set
of equations, a series of mechanical processes done by hand, an analog piece of equipment, or a
digital process and/or processor.
One of the most important aspects of algorithm design is creating an algorithm that has an
efficient runtime, also known as its big Oh.
Steps in development of Algorithms
Let us discuss on this topic as per International Journal for Algorithm Design and
Analysis.Itfocuses on original research and practice driven application with relevance to
algorithms designs and analysis. All article included are peer-reviewed by scholars with colossal
experience in the same fields. Dynamic programming, amortized analysis and linear
programming are major focus areas.
Focus and Scope of the Journal
All contributions to the journal are rigorously refereed and are selected on the basis of quality
and originality of the work. The journal publishes the most significant new research papers or
any other original contribution in the form of reviews and reports on new concepts in all areas
pertaining to its scope and research being done in the world, thus ensuring its scientific priority
and significance.

I want you to Read intensively papers and give me a summary for ever.pdf

Related slideshows

More Related Content

I want you to Read intensively papers and give me a summary for ever.pdf