Biometric System, Privacy-enhancing Technologies, And Wireless Sensor Networks

Fingerprint detection technology

Biometric system is a security system that is related to human characteristics. It is way through which authentication could be done by verifying the correct identity. It helps in identifying an individual under certain surveillance (Lallie,  Debattista & Bal, 2018). Biometric system can be considered as a reliable source for identification by using some knowledge based methods. The use of biometric system is increasing everyday with the purpose of enhancing security (Mattei, 2017). The data captured for verification of bio metric is unique for every individual thus it make sure that authentication is maintained over the network. The sole person of using biometric system is to ensure that information and operations are accessed by the valid user.

Different types of Bio-metrics system that will be discussed in this report are:

• Fingerprint detector
• Hand geometry
• Iris recognition

Finger point detection is an advanced form of biometric technology. It is gaining popularity as it assures that accuracy and reliability of system is improved. It is a live detector, in which any fake spooking is not possible as every individual as unique fingerprints. This technology works on series of steps, initially all the groves and ridges of fingers are scanned and then it is compared with the data stored in the database (Shropshire,  Warkentin & Sharma, 2015). If both the information is matched then only access is provided to the user.

(Source: https://www.apk4fun.com/apk/2195/)

It was one of the oldest biometric technologies that came in the market in 1980s. It identifies the user by the shape of the hand. It measures the dimension of users hand along with many other factors. Then the captured image is compared with the stored file. It was the first computerised security measure. It was basically used for time and attendance measurement along with access control. The accuracy of the system is high but the social acceptance is very low of hand geometry (Robinson,  Schildt, Goff & Corwin, 2017). This technology is used by various firms but it is not accepted as it is time consuming and is not accurate. It works on detecting the thickness, height, width of an individual’s hand. Thus this technology works on capturing the data by CCD process and then comparing it.

(Source: https://www.360biometrics.com/faq/Hand-Geometry-Biometrics.php)

The latest version of biometric system is iris recognition that has gained popularity and is used over all the ATMs and bank system. It uses pattern matching technique the pattern that is used in this method is duplication of a person eye. It is highly secure as compared to other methods as it work on the matching the highly resolved image. This technology is popular and solves all the drawbacks that re faced due to finger print or hand geometry (Farash, Turkanovi?, Kumari & Hölbl, 2016). The iris is an organ in a human body that remains constant and the chances of errors are very less in this technology. Thus, it is seen as one of the trusted way to perform authenticated operations. The time taken to identify the valid user is very less and this method is highly recommended to use as compared to other biometric methods.

Hand geometry

(Source: https://www.paychex.com/articles/payroll-taxes/iris-recognition-improves-time-and-attendance-tracking)

PET is an important technology as it assures that privacy of information is maintained. Privacy enhancing technology is a way of protecting the information by minimizing the chances of security breach (Fraschini,  Hillebrand, Demuru,  Didaci & Marcialis, 2015). The security threats are increasing which has increased the risk of data breaching. Thus, privacy enhancing technology offers laws and regulation to protect the data (Iapp, 2017). It is an approach that is used to achieve data protection. The motive behind this technology is to assure that confidentiality of personal data is maintained. By making sure that no invalid or unauthorised user gets the right to access the information.

Privacy enhancing technology is popular and is used by many firms so protect the data and enhance the security (Niu, Li,  Zhu,  Cao & Li, 2015). The main aim of this technology is to protect all the sensitive information so that it is not accessed by any unauthorised user. Some of the example that makes use of Privacy enhancing technology is shared bogus, online accounts, anonymizers and other methods to secure the data.  

Three PETs which can be used on the Internet are discussed below:

• Encryption- It is advancement in technology; in this the original data is encrypted so that it is not read by any unauthorised user (Niu, Li,  Zhu,  Cao & Li, 2015). It works on converting the data in a non-readable form so that data can be secured from all the cyber-attacks (Pawar & Agarwal, 2017). It is used to secure the telecommunication media by allowing user to transmit sensitive information from one location to another without the issue of data breach (Harborth & Pape, 2018).
• Security tools- One such tool is anonymity tool that allow user to interact with the customer uniquely by offering them unique IP address. One of the security tools that are popularly used, anonymity tool that eliminates the issue of hacking and data breaching. This process is an expensive process is offering a unique IP address is difficult (Pawar & Agarwal, 2017). There are various tools that can be used for managing all the assets and build autonomy enhancing.
• Data tracking- It is basically used to manage digital privacy of data by tracking the information that have been disclosed. This process assures that information is not accessed or disclosed to unauthorised user so that privacy is maintained. Data tracking on the other hand, offers benefit to user by maintaining transparency. It assures that information is secure and can be transmitted from one network to another, without the issue of data tracking (Harborth & Pape, 2018). It helps in building trust and loyalty in the customers by assuring that their sensitive information will remain confidential.

All these tools and technologies used by Privacy-Enhancing Technologies reduce the chances of cybercrimes. On the other hand, it makes sure that integrity, confidentiality and availability is maintained (Hoepman, 2014). Privacy-Enhancing Technologies protect the data from cybercrimes and also make sure that personal information remains confidential.

A wireless sensor network is used to monitor all the physical and environmental conditions. Wireless technology makes sure that transmission of data from one location to another without the need of wires (Tuna, Kogias,  Gungor, Gezer, Ta?k?n & Ayday, 2017). Apart from that, wireless sensor network can be seen as a group of dispersed sensors that are monitored or tracked from a central location. In wireless sensor network each node is connected to another through radio network.  It is better than other as it offers ease of use, as implementation is quiet simple. It has higher resilience and can even work in harsh conditions (Romer & Mattern, 2014). It is used for security purpose and it can also be used for communicating though long distance. Some of the basic application of wireless sensor network is monitoring of water, asset tracking, building structures and controlling all the machines that may be located remotely. Wireless sensor network is used for monitoring all the devices or operations irrespective of their location (Li, Vishwamitra, Knijnenburg,  Hu & Caine, 2017).

Iris Recognition

The architecture of wireless sensor network as 5 layers along with 3 cross layer. The three cross layers is task management plane, power management plan, and mobility management plane and the five layer such as application layer, transport layer, network layer, data link layer, and physical layer.

Different type of threats that are faced due to WSNs

• Denial of Service- This attack violates the confidentiality of data as it prevents the valid user to access the data. Denial of service is denial a user to access to their service. This can be done by flooding the network by false request so those servers get overloaded (Li, Vishwamitra, Knijnenburg,  Hu & Caine, 2017). Denial of service attack prevents the user to access the information.
• Man in the middle attack–In this some third party user silently modifies or read the data. The confidential communication between two parties is leaked as third party access the information. The valid users are not aware that someone else is reading their communication. Man in the middle attack performs malicious activities so that they can read the confidential information (Suryadevara, Mukhopadhyay, Kelly & Gill, 2015).
• Flooding- It is a way in which false traffic is created over the network by broadcasting the information at a particular node (Tuna, Kogias,  Gungor, Gezer, Ta?k?n & Ayday, 2017). Flooding disallow the valid user to access the information by creating legitimate traffic.

To maintain the overall security of a network it is suggested that, all the data stored over the network should be encrypted. Encrypting the data assures that even if third party users access the data they are not able to read the information. Apart from that, all the software’s and applications need to be updated so that chances of errors penetrating in the system reduces. The other way to meet all the security constraints of wireless sensor network it is recommended to undertake the concept of cryptography. The data should be stored over cloud or proper backup should be taken regularly. So, that in case of failure all the information could be restored from the cloud.

References

Farash, M. S., Turkanovi?, M., Kumari, S., & Hölbl, M. (2016). An efficient user authentication and key agreement scheme for heterogeneous wireless sensor network tailored for the Internet of Things environment. Ad Hoc Networks, 36, 152-176.

Fraschini, M., Hillebrand, A., Demuru, M., Didaci, L., & Marcialis, G. L. (2015). An EEG-based biometric system using eigenvector centrality in resting state brain networks. IEEE Signal Processing Letters, 22(6), 666-670.

Harborth, D., & Pape, S. (2018). Examining Technology Use Factors of Privacy-Enhancing Technologies: The Role of Perceived Anonymity and Trust, 34-45.

Hoepman, J. H. (2014, June). Privacy design strategies. In IFIP International Information Security Conference (pp. 446-459). Springer, Berlin, Heidelberg.

Iapp. (2017). An Introduction to Privacy Enhancing Technologies. Retrieved from https://iapp.org/news/a/2008-05-introduction-to-privacy-enhancing-technologies/.

Lallie, H. S., Debattista, K., & Bal, J. (2018). An Empirical Evaluation of the Effectiveness of Attack Graphs and Fault Trees in Cyber-Attack Perception. IEEE Transactions on Information Forensics and Security, 13(5), 1110-1122.

Li, Y., Vishwamitra, N., Knijnenburg, B. P., Hu, H., & Caine, K. (2017). Effectiveness and users’ experience of obfuscation as a privacy-enhancing technology for sharing photos. Manuscript submitted for publication, 4.

Mattei, T. A. (2017). Privacy, Confidentiality, and Security of Health Care Information: Lessons from the Recent WannaCry Cyberattack. World neurosurgery, 104, 972-974.

Niu, B., Li, Q., Zhu, X., Cao, G., & Li, H. (2015, April). Enhancing privacy through caching in location-based services. In Computer Communications (INFOCOM), 2015 IEEE Conference on (pp. 1017-1025). IEEE.

Pawar, M., & Agarwal, J. (2017). A literature survey on security issues of WSN and different types of attacks in network.”. Indian Journal of Computer Science and Engineering, 8(2), 80-83.

Robinson, T. L., Schildt, B. R., Goff, T. V., & Corwin, D. J. (2017). U.S. Patent No. 9,544,309. Washington, DC: U.S. Patent and Trademark Office.

Romer, K., & Mattern, F. (2014). The design space of wireless sensor networks. IEEE wireless communications, 11(6), 54-61.

Shropshire, J., Warkentin, M., & Sharma, S. (2015). Personality, attitudes, and intentions: Predicting initial adoption of information security behavior. Computers & Security, 49, 177-191.

Suryadevara, N. K., Mukhopadhyay, S. C., Kelly, S. D. T., & Gill, S. P. S. (2015). WSN-based smart sensors and actuator for power management in intelligent buildings. IEEE/ASME transactions on mechatronics, 20(2), 564-571.

Tuna, G., Kogias, D. G., Gungor, V. C., Gezer, C., Ta?k?n, E., & Ayday, E. (2017). A survey on information security threats and solutions for Machine to Machine (M2M) communications. Journal of Parallel and Distributed Computing, 109, 142-154.

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