Biometric system is a system that uses the physical description of the persons to provide authentication. In this type of authentication system the scanning of the fingerprint or the scanning of the iris can be done for providing the authentication to the person for the access. The security measure in the biometric authentication is high. There are different types of biometric authentication that can be implemented. Some of these techniques are-
All these techniques have certain advantages and disadvantages.
Fingerprint: In the fingerprint authentication in the biometric the fingerprint of the person is scanned in order to provide the access (Galbally, Marcel & Fierrez, 2014). There are basically two functions in this type of biometrics- to scan the fingerprint of the user, to examine the scanned fingerprint with the pre scanned image of the fingerprint in the system. In case, if the two scanned images matched that person get the access else access would be denied.
Advantages of finger print authentication:
Disadvantages of the fingerprint authentication:
Hand geometry: Hand geometry is another biometric authentication process that scans the shape of the hand or palm for providing the authentication (Galbally, Marcel & Fierrez, 2014). The measurements of the hand along with the shape are scanned in the system. The scanned image is then compared with the pre scanned image in the system (Svoboda, Bronstein & Drahansky, 2015). In case, if both images are matched the person is provided with the access.
Advantages of hand geometry:
Disadvantages of hand geometry:
Iris recognition: Using of the iris scanning can be used in the biometric authentication. In this case, the iris of the eye of the user is scanned. The pattern of the iris is matched with the pre scanned image in the system (Ortiz et al.,2018). In case, if both the scanned pattern is matched, the user provides the access else the access is denied.
Advantage of the iris scan:
Disadvantages of the iris scan:
Privacy enhancing technology:
The use of internet is growing rapidly. The users are using the internet for various purposes. On the other hand the users are transferring the large amount of data over internet. The data and information are sometime confidential and sensitive. In this case, enhancing the privacy for using the internet is needed.
In order to maintain the privacy in the internet , privacy enhancing technology is needed to be use. The concept of the privacy enhancing technology for the internet is emerging; however, the application is effective for maintaining the security and privacy in the internet.
Three privacy enhancing technologies are-
The Anonymizer: initially this technology was a student project. It can be defined as the oldest privacy enhancing technology available for internet. The main objective of this technology is to solve the privacy problem. However, this technology is not concerned about the future issues and threats those can be occurred (Chelli, 2015). Using this technology the users can browse the without leaving the data in site. The privacy model of the Anonymizer treats data in a commercial way. This technique is not advanced however, it is able to provide the basic privacy and the security to the users using internet.
iPrivacy: iPrivacy provides the proxy server for users so that they can transfer the sensitive and confidential data in a secured manner. The analysis can be done only on the public information in this case. The concept of the iPrivacy is based on the concept the internet should be private in the offline world. However, the concept of the private world is not well defined (Choi et al.,2017). Apart from that it is not sure if the iPrivacy can access all the public data. However, this free software is suitable for the secured transaction of data which holds the information regarding the money transaction details and other bank details.
Incogno SafeZone:Incogo offers the similar service as iPrivacy, however, in iPrivacy the solution is protection to the transaction data, in Incogno is focused to the business which is privacy sensitive. This software is concern about the possible risks of the merchant when the security measure is right. The main advantage of this technology is that it provides the merchants to avail the tailor made security solutions while using the internet (Kumar, Jain & Barwal,2014). This technology works as the third party company which is responsible for managing the relationship between the client and server of the system or the process. Incogo stops the merchant sites to collect the information regarding the customers while they are doing the transaction. However, Incogno admits that the software can view the customer data.
Wireless Sensor Network is referred to the wireless network which has distributed devices for monitoring the sensors in the networking environment. It provides secured wireless network connectivity to the users. Different wireless network protocol can be used depending on the requirements of the application. Wireless sensor network can provide a lot of advantages over the wired network. However, flexible software architecture is needed to implement the wireless sensor network. One of the software architecture is NI LabVIEW graphical system design (Can & Sahingoz,2015) . Wireless Sensor Network follows the topology for the implementation. Generally Star topology is sued for the implementation of the wireless sensor network. Other topology those are used for the implementation of the wireless sensor network are cluster tree and mesh topology.
Three kinds of threats and vulnerabilities in the wireless sensor network:
There are various security threats those can be happened in the wireless sensor network. Some of those security threats are-
Denial of service attack: Denial of service attack can interrupt the communication channel through making the interface in form of noise and collision in receiver’s side. In order to formulate the service the attackers are needed to reach to the server application, network access and the network infrastructure. The draining of the data can be done at the receiver’s side by transferring the unnecessary data (Heurix et al.,2015). In this way denial of service attack prevents the users to access the needful resources. The denial of service attack can be different in the different layer of the network. In physical layer the denial of service attack can be jamming of the signal, tampering. At data link layer the attack can be in form of collision, exhaustion. In transport layer the denial of service attack can be in form of flooding and desynchronization.
Prevention technique of denial of service attack:
The prevention of the denial of service attack includes the strong authentication in the access of the network resources along with identification of the malicious traffic.
Wormhole attack:In wormhole attack the attackers stores all the packets in one location of the network and then transfers the packets to another location. Through certain channels (Ziegeldorf, Morchon & Wehrle,2014). Selective transmissions of the bits are done in this case. Wormhole attack can be considered as the major threat to the wireless sensor network as this type of attack does not need the compromising of the sensor (Malina et al.,2016). The attack can be initiated easily during the launch of the network sensor.
Prevention technique of wormhole attack:
Some of the prevention methods for mitigation of the worm hole attack are-
Packet leashes: Packet leashes provide the assurance that the packets are not getting far away from their geographical sources. In this case, each of the nodes are equipped with GPS. In case of temporal leashes the clocks of the nodes are tightly synchronized. The transmission of the packets header is equipped with the timestamp.
Flooding attack: In this case, the packet is used to encourage the sensor in the network. The packets are sent to the number of sensors within the sensor network (Yang, 2014). The attackers gain control over the broadcasting network in this way. The malicious node with the interconnected network thus sends the packets to all the nodes and makes the whole wireless sensor network affected.
Prevention method for flooding attack:
Flooding attack can be prevented using the firewall in the system. The firewall will prevent unnecessary network traffics to enter in to the wireless sensor network.
References
Can, O., & Sahingoz, O. K. (2015, May). A survey of intrusion detection systems in wireless sensor networks. In Modeling, Simulation, and Applied Optimization (ICMSAO), 2015 6th International Conference on (pp. 1-6). IEEE.
Chelli, K. (2015, July). Security issues in wireless sensor networks: Attacks and countermeasures. In Proceedings of the World Congress on Engineering (Vol. 1, pp. 1-3).
Choi, J., Bang, J., Kim, L., Ahn, M., & Kwon, T. (2017). Location-based key management strong against insider threats in wireless sensor networks. IEEE System Journal, 1-9.
Galbally, J., Marcel, S., & Fierrez, J. (2014). Image quality assessment for fake biometric detection: Application to iris, fingerprint, and face recognition. IEEE transactions on image processing, 23(2), 710-724.
Galbally, J., Marcel, S., & Fierrez, J. (2014). Image quality assessment for fake biometric detection: Application to iris, fingerprint, and face recognition. IEEE transactions on image processing, 23(2), 710-724.
Heurix, J., Zimmermann, P., Neubauer, T., & Fenz, S. (2015). A taxonomy for privacy enhancing technologies. Computers & Security, 53, 1-17.
Kumar, V., Jain, A., & Barwal, P. N. (2014). Wireless sensor networks: security issues, challenges and solutions. International Journal of Information and Computation Technology (IJICT), 4(8), 859-868.
Malina, L., Hajny, J., Fujdiak, R., & Hosek, J. (2016). On perspective of security and privacy-preserving solutions in the internet of things. Computer Networks, 102, 83-95.
Ortiz, N., Hernández, R. D., Jimenez, R., Mauledeoux, M., & Avilés, O. (2018). Survey of Biometric Pattern Recognition via Machine Learning Techniques.
Svoboda, J., Bronstein, M. M., & Drahansky, M. (2015, May). Contactless biometric hand geometry recognition using a low-cost 3D camera. In Biometrics (ICB), 2015 International Conference on (pp. 452-457). IEEE.
Yang, K. (2014). Wireless sensor networks. Principles, Design and Applications.
Ziegeldorf, J. H., Morchon, O. G., & Wehrle, K. (2014). Privacy in the Internet of Things: threats and challenges. Security and Communication Networks, 7(12), 2728-2742.
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