Analysis of Biometric Systems, Privacy Techniques, and WSN Security

This report delves into the multifaceted realm of risk management, encompassing biometric systems, privacy-enhancing techniques, and wireless sensor network (WSN) security. It begins by examining biometric systems, specifically face recognition, palm-print recognition, and gait recognition, outlining their advantages and disadvantages. The report then transitions to privacy-enhancing techniques, discussing email anonymity, interactive anonymity, and communication privacy systems such as SSL/TLS and off-the-record messaging. Finally, the report addresses the security challenges within WSNs, identifying threats like spoofing, Sybil attacks, and network flooding, while also proposing threat mitigation strategies. These strategies include node authentication, limiting request numbers, and the use of intrusion detection systems to ensure the secure and reliable operation of WSNs.

Running head: RISK MANAGEMENT
Risk Management
Name of the Student
Name of the University
Author Note

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Table of Contents
Answer 1..............................................................................................................................2
1.1. Face Recognition......................................................................................................2
1.2. Palm-print Recognition.............................................................................................3
1.3. Gait Recognition.......................................................................................................4
Answer 2..............................................................................................................................5
2.1. Email Anonymity......................................................................................................5
2.2. Interactive Anonymity..............................................................................................5
2.3. Communication Privacy Systems.............................................................................6
Answer 3..............................................................................................................................7
3.1. Threat Mitigation......................................................................................................8
References............................................................................................................................9

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Answer 1
Biometric system is a technology-based system that uses some distinct information of a
person to identify that person. These systems mainly rely on a specific data or biological traits of
a person. The statistical analysis of people’s physical and behavioral characteristics is used as an
identity of a person. These systems control the access of the restricted areas or systems by
allowing only the authorized person to access the system or the area. Biometric access control
systems ensure that right level of security is enforced within a specific system or place. The
components of the biometric system include a metal oxide semiconductor or a charged coupled
device for some particular systems (Banerjee & Woodard, 2012). A biometric access system
helps to transfer a biometric trait of a particular person in electrical signal that helps in
identifying a person. The biometric access control system is mainly of two types, physiological
and behavioral biometric system. The physiological biometric system consists of fingerprint
recognition, face recognition, iris recognition, voice recognition, palm print recognition, gait
recognition and so on. Out of these, face recognition, palm print recognition and gait recognition
are discussed in the next section.
1.1. Face Recognition
Face recognition captures the digital image of the person and verifies the identity of the
person by comparing and analyzing the different patterns of the image. This is one of the most
commonly used biometric systems for security (Beveridge et al., 2013). The data of the nodal
points of a digital image is captured, which is then used for verification. The advantages and
disadvantages of face recognition are as follows-
Advantages

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The advantages of using face recognition biometric system are as follows-
1. It is a user-friendly biometric recognition system
2. It is one of the most inexpensive techniques of verifying the identity of a person.
3. It is a non-contact technology, as cameras are used for collecting the necessary
information for identifying a person.
4. Offers high speed identification in comparison to other biometric system
Disadvantages
1. The working principle of the facial recognition algorithm is largely dependent on the
quality of the image.
2. The relative angle of the target’s face largely influences the recognition score.
3. It requires a significantly larger storage space.
1.2. Palm-print Recognition
Palm print recognition is another biometric access control system that makes use of a
scanning device to process an image data of a user’s palm and compare it with a stored record
(Cappelli, Ferrara & Maio, 2012). The advantages and disadvantages of palm print recognition
are as follows-
Advantages
The advantages of Palm print recognition are as follows-

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1. The palm area is much larger and therefore it helps in capturing and analyzing the
features of human hand more distinctively as compared to a fingerprint.
2. Palm print recognition system can be easily integrated into other systems and devices.
Disadvantages
The disadvantage of palm print recognition is as follows-
1. The system requires a large surface area and therefore, the entire device becomes
larger in size. This increases the cost of the system as well.
1.3. Gait Recognition
This is a biometric method that deals with unique biological and behavioral
characteristics of a user such as fingerprint or face. It is s systemic study of human motion and
makes use of instruments in measuring the body movements and body mechanics. The
advantages and disadvantages of gait recognition are as follows-
Advantages
The advantages of gait recognition are as follows-
1. It is a contact less method as a gait recognition system can recognize a person from a
distance
2. Effective in use even in low-resolution image
3. It is a non-invasive biometric technology
Disadvantages

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The disadvantages of gait recognition are as follows-
1. It may not work properly if a person changes or modifies its style of motion
2. Even the surface of motion largely influences the gait recognition system.
Answer 2
Privacy enhancing techniques refers to standardized methods of protecting the privacy of
the stored data over internet. It considerably helps in protecting the privacy of the online users. It
enforces legal privacy principles for protecting and enhancing the privacy of the users (De
Cristofaro & Wright, 2013). The three different Privacy Enhancing Techniques that can be used
on internet are discussed below-
2.1. Email Anonymity
The email anonymity systems ensure that a particular email is sent without revealing the
personal information and identity of the user. Use of remailer is prominent in achieving the email
anonymity (Rainie et al., 2013). The working principle of the remailer is that, when a user sends
an email, it at first goes to the remailer. The remailer in turn strips off the identification
information of the user and re-mails the message to the intended recipient (Froomkin, 2015).
Type-III remailer is an advanced remailer that provides efficient protection against the replay
attacks.
2.2. Interactive Anonymity
With the advent of technology and internet, real time online interaction is increasing as
well. An attacker can intercept these communications thus leading to the information loss or
modification of the information (Larsson et al., 2012). An information can be modified during its

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transmission. Different internet applications such as, remote login and voice over IP posses
significant threat to data privacy. In order to eliminate such risks, different systems are
implemented over the years that provide practical security and privacy to the users. The
examples of different systems that maintains the privacy of the of the users data over internet
includes use of onion routing, freedom network, Java Anon Proxy, Tor and so on (Li et al.,
2013).
2.3. Communication Privacy Systems
The communication privacy systems ensure that the identity of a user communicating
over internet is kept private. The aim of this Privacy Enhancing Technique is to keep any
information flow private from the third parties. Different techniques are applied to protect the
information if a user wishes to keep the contents of a particular communication private (Wessels
et al., 2012). Examples of different communication privacy systems include use of SSL and TLS,
off the record messaging and so on.
SSL or secure socket layer protocol is a privacy enhancing technology in which the web
browser by default encrypts all the web requests while undergoing a communication with an SSL
web server. TLS is the later version of SSL, while its application is similar to SSL (Bhargavan et
al., 2013). One of the most striking features of SSL is that, no human intervention is needed for
encryption.
Off record messaging on the other hand, is a technology to protect the contents of the
instant messaging and communication over the internet. This PET system encrypts all the instant
messages so that no third party can access the information. Off record is used by many
communication applications such as iChat and Trillian.

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Apart from these, there are other different privacy enhancing techniques such as private
payments and use of anti phishing tools further helps in protecting the privacy of data over
internet.
Answer 3
Wireless sensor network can be termed as a network of the spatially distributed devices
that are interconnected with each other. It is used for providing a wireless connection to the
different devices. Sensors are used to monitor the physical and environmental conditions of the
sensors. WSN consists of different base stations and nodes or the wireless sensors. The different
layers of WSN protocol stack include application layer, transport layer, network layer, data link
layer and physical layer. The different types of threats on which the WSN network is exposed to
are as follows-
Spoofing Attack
Spoofing is one of the common attacks in the wireless sensor networks. It makes use of a
malicious program disguised as a legitimate program in order to gain an illegitimate advantage.
This as a result can corrupt the network traffic extensively (Singla & Sachdeva, 2013).
Furthermore, continuous alteration in messages can result in loss of data packet during its
transmission.
Sybil Attack
Sybil attack is another prominent attack in the wireless sensor network. There are cases
where the sensors of a particular network might need to work together. In such cases, the entire
task is distributed into a number of sub tasks (Venkatraman, Daniel & Murugaboopathi, 2013).

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Presence of a malicious node in the network often tunnels the information or data to a complete
different location.
Network Flooding
It is often seen that a malicious code present in a WSN can generate a large number of
useless traffic thereby flooding the entire network. This causes congestion in the network leading
to the exhaustion of the nodes. This attack is much similar to denial of service attacks.
Apart from these, there are certain other threats and vulnerabilities in WSN. These
include sinkhole attack, node replication attack, wormhole attack and so on. The threat
mitigation techniques for these attack is discussed in the following section.
3.1. Threat Mitigation
The different thereat mitigation techniques that can be employed in order to ensure a safe
operation of wireless sensor network are as follows-
1. Only the authorized nodes are allowed to communicate over the network. The attack
can be avoided by verifying the identity of the different nodes of a WSN by a trust worthy node.
2. The flooding attack can be prevented by limiting the number of requests a node can
handle in a set amount of time.
3. Use of a proper intrusion detection system in the network can help in identifying the
presence of malicious nodes (Alrajeh, Khan & Shams, 2013).

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References
Alrajeh, N. A., Khan, S., & Shams, B. (2013). Intrusion detection systems in wireless sensor
networks: a review. International Journal of Distributed Sensor Networks, 9(5), 167575.
Banerjee, S. P., & Woodard, D. L. (2012). Biometric authentication and identification using
keystroke dynamics: A survey. Journal of Pattern Recognition Research, 7(1), 116-139.
Beveridge, J. R., Phillips, P. J., Bolme, D. S., Draper, B. A., Givens, G. H., Lui, Y. M., ... &
Flynn, P. J. (2013, September). The challenge of face recognition from digital point-and-
shoot cameras. In Biometrics: Theory, Applications and Systems (BTAS), 2013 IEEE
Sixth International Conference on (pp. 1-8). IEEE.
Bhargavan, K., Fournet, C., Kohlweiss, M., Pironti, A., & Strub, P. Y. (2013, May).
Implementing TLS with verified cryptographic security. In Security and Privacy (SP),
2013 IEEE Symposium on (pp. 445-459). IEEE.
Cappelli, R., Ferrara, M., & Maio, D. (2012). A fast and accurate palmprint recognition system
based on minutiae. IEEE Transactions on Systems, Man, and Cybernetics, Part B
(Cybernetics), 42(3), 956-962.
De Cristofaro, E., & Wright, M. (2013). Privacy enhancing technologies. In Proceedings of 13th
International Symposium, PETS.
Froomkin, A. M. (2015). From anonymity to identification. Browser Download This Paper.
Larsson, S., Svensson, M., De Kaminski, M., Rönkkö, K., & Alkan Olsson, J. (2012). Law,
norms, piracy and online anonymity: Practices of de-identification in the global file
sharing community. Journal of Research in Interactive Marketing, 6(4), 260-280.

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Li, B., Erdin, E., Gunes, M. H., Bebis, G., & Shipley, T. (2013). An overview of anonymity
technology usage. Computer Communications, 36(12), 1269-1283.
Rainie, L., Kiesler, S., Kang, R., Madden, M., Duggan, M., Brown, S., & Dabbish, L. (2013).
Anonymity, privacy, and security online. Pew Research Center, 5.
Singla, A., & Sachdeva, R. (2013). Review on security issues and attacks in wireless sensor
networks. International Journal of Advanced Research in Computer Science and
Software Engineering, 3(4).
Venkatraman, K., Daniel, J. V., & Murugaboopathi, G. (2013). Various attacks in wireless
sensor network: survey. International Journal of Soft Computing and Engineering, 3(1),
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Wessels, B. (2012). Identification and the practices of identity and privacy in everyday digital
communication. New Media & Society, 14(8), 1251-1268.