1.
a. Fingerprint- The Fingerprint technique is one of the most commonly used biometric identifiers as because of the fact that they are easy in acquisition, identification, verification and storage. It is used for security purposes and for criminal identifications (Jay, 2017). This type of bio-metric systems uses the digital imaging technology in order to obtain, store and to analyse the fingerprint data and information. The main advantage of fingerprint identification biometric system is that the patterns of fingerprints remain the same for an individual throughout his life. Hence, this makes it one of the infallible methods of human being identification (Jain & Nandakumar, 2015). Like, any other system, it also has its own disadvantage. It is to note that fingerprint recognition software only reads one section of the finger of a person and therefore, it is vulnerable to error. This type of system could be used in offices and other organisations for verifying, identifying and storing information and other data.
b. Hand Geometry- The technique used in this type of biometric system is that an individual needs to place his hard as per the pegs present in the surface of the device (Davis et al., 2015). The device would then capture the image of the hand by making use of ordinary digital cameras or document scanners. The main advantages of this type of system is that it is simple and is relatively easier to use. It also inexpensive as well. The data of Hand geometry is also easier to collect that fingerprint system. Also, the environmental factors like dry weather condition that causes drying of hand skin is also not an issues for hand geometry system. On the other hand, its disadvantages include- it is not idle for the growing children, it cannot be used in the identification systems. With the same, it is also to note that the size of data of the hand geometry biometrics is very large and is also not ideal for making use in the embedded systems. Hand geometry is basically used in the automated identification and in the data capture courses. It is also used for tracking the prisoners and is also used by the international banks.
c. Iris Recognition- This types of biometric system is the one and only biometric authentication technology that is designed for working in exhaustive search mode (Stefani & Ferrari, 2017). It makes use of techniques of mathematical pattern recognition on the video images of the iris or irises of a person’s eye as every individual have complex, unique and stable patterns. Some of its core advantages is that it is best known biometric modalities in regards of accuracy, scalability and stability. Also, unlike retina scanning, this system could be done from a normal distance. With the same, this technology is not at all intrusive as there is no need of direct contact in between the device and the camera (De Marsico et al., 2014). With the same, an individual could complete the process very faster than the other modalities. Furthermore, the decision making and encoding of the iris patters is traceable. On the other hand, its disadvantages includes the fact that it is very expensive and is that a person needs to be very steady in front of this device in order to be enrolled by the scanners. Also, Iris might deform the non-elasticity due to the fact that pupil might change its size because of medical or any other related conditions. One of the examples of such type of biometric system is in UK one can retrieve his money from his bank account by simply looking at his ATM machine.
2. Privacy-enhancing technologies (PETs) refers to the standard term which refers to the particular method that act as per the laws of the data protection. It allows the online users to protect the privacy of thier own personally identifiable data and information that are provided to and are handled by the applicants and services. The three PETS (Privacy-enhancing technologies) that can be used on the Internet are communication anonymizers, the shared bogus online accounts and Obfuscation.
a. Communication Anonymizers- It hides the real online identity like the IP address, e-mail address etc. and it replaces them with the non-traceable identity such as one-time email addresses etc. This type of PETs could be applied to P2P networking, email, instant messaging, Chat, web browsing and VoIP. An anonymizer refers to a proxy server which makes the Internet activity untraceable. Ananonymizer protects personally identifying the data and information by hiding the private information on the behalf of the user.
b. Shared bogus online accounts- In this technology, a person makes an account for the MSN, and provides bogus data and information for the name, the phone number, situation of life, preferences and address etc. He then publishes his user-ID as well as password on the internet as well. Hence, everyone could use this account with an ease. In this way, the user stays sure that there is absence of any kind of personal data about him in the profile of the account. Also, he is hence completely freed from the hassle of having to register at the very site all by himself.
c. Obfuscation- It refers to the so many practices of adding, deducting or misleading the data and information to a profile or a log that might be especially useful for the purpose of frustrating precision analytics after the data has already been disclosed or has been lost. The effectiveness of it against the humans is then questioned but it has much greater promise against the shallow algorithms.
3. WSN (Wireless sensor networks) needs very high level of security because of its harsh environment. It in turn leads to the survival requirements and intense security (Rawat et al., 2014). Wireless sensor networks face attacks of several types. The limited resources of sensors make the Wireless sensor networks face a high security challenges. The three types of threats and vulnerabilities that could be used for attacking the WSN (Wireless sensor networks) are:
a. Passive attacks- The process of listening and monitoring the channel of communication by means of unauthorized attackers are regarded as the passive attack. Some of the very common attacks that are against the wireless sensor network privacy areTraffic analysis and Camouflage adversaries.
b. Active Attack- The attackers who are unauthorized, monitors, listens as well as modifies the data stream in the channel of communication are termed as the active attacks (Bhiyan et al., 2015). The attacks that are active in nature are Routing Attacks in Sensor Networks, Black hole or Sinkhole Attack and Attacks on Information in transit etc.
c. Security Challenges in WSN (Wireless Security Networks)- The nature of large, ad-hoc, WSN (wireless sensor networks) sets the key challenges in the process of designing of the schemes of security. It is a very special network that has several constraint as compared to the traditional computer networks (Rault, Bouabdallah & Challal, 2014). Such type of security challenges include Wireless Medium, Immense Scale and Hostile Environment.
The wireless medium is very less secure due to the fact that its nature of broadcast makes the process of eavesdropping very simple. Any of the transmissions could be easily replayed, intercepted or replaced by any rival. Such a wireless medium enables an attacker to stop the plausible packets very easily as well as help in injecting the malicious ones easily as well (Akhtar & Rehmani, 2015). Although such issue is not new to the sensor networks but it should be ensured that traditional solutions are adapted for efficiently executing on the sensor networks (Jing et al., 2014). Furthermore, the scale of sensor networks that is proposed must poses an important challenge for the security mechanisms. The simple networking of ten to hundreds to thousands of nodes has been proved to be fundamental tasks. Moreover, the next demanding element is the antagonistic environment where the sensor nodes do functioning. It is also to note that motes undergoes the likelihood of capture and destruction by the attackers. The immensely antagonistic environment depicts a very vital and significant challenge for the security researchers.
References:
Akhtar, F., & Rehmani, M. H. (2015). Energy replenishment using renewable and traditional energy resources for sustainable wireless sensor networks: A review. Renewable and Sustainable Energy Reviews, 45, 769-784.
Bhuiyan, M. Z. A., Wang, G., Cao, J., & Wu, J. (2015). Deploying wireless sensor networks with fault-tolerance for structural health monitoring. IEEE Transactions on Computers, 64(2), 382-395.
Davis, J. W., Sharma, V., Tyagi, A., & Keck, M. (2015). Human Detection and Tracking. Encyclopedia of Biometrics, 882-887.
De Marsico, M., Galdi, C., Nappi, M., & Riccio, D. (2014). Firme: Face and iris recognition for mobile engagement. Image and Vision Computing, 32(12), 1161-1172.
Jain, A. K., & Nandakumar, K. (2015). Biometric System Design, Overview. In Encyclopedia of Biometrics (pp. 229-235). Springer, Boston, MA.
Jay, R. (2017). The transparent human: the new biometrics and the General Data Protection Regulation. Communications Law, 22(1), 5-10.
Jing, Q., Vasilakos, A. V., Wan, J., Lu, J., & Qiu, D. (2014). Security of the Internet of Things: perspectives and challenges. Wireless Networks, 20(8), 2481-2501.
Rault, T., Bouabdallah, A., & Challal, Y. (2014). Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks, 67, 104-122.
Rawat, P., Singh, K. D., Chaouchi, H., & Bonnin, J. M. (2014). Wireless sensor networks: a survey on recent developments and potential synergies. The Journal of supercomputing, 68(1), 1-48.
Stefani, E., & Ferrari, C. (2017). Design and Implementation of a Multi-Modal Biometric System for Company Access Control. Algorithms, 10(2), 61.
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