Optimization of dynamic resistance against malicious attacks & collusion through enhanced authentication schemes in application to smartcard

Smart card accelerates and harmonizes the usage in development of day to day activities. The message authentication during the transaction with valid digit codes prevails in systematic higher end secured level of authentication. However, several message authentication schemes have been experimented to protect messages but these authentication schemes have the limitations of high computational and communication overhead, lack of scalability, resilience to node compromise attacks and threshold problem. The enhanced resistance against collusion and malicious attacks on wireless sensor network is presented in this paper. Conventional methods experimented to mitigate the false data and observe the system behavior at the cost of decrease in efficiency. In this paper, a novel filtering system and interleaved hop-by-hop authentication system is developed that effectively localize the mitigation of injected false data. Design of filtering system is tested with well known bench mark of false data mitigation created by the user. Quantitative analysis is performed to enrich the efficiency of the designed system. Furthermore, this approach envisages for the identification of malicious attacks, false packet detection and removal effectively by this authentication scheme which delivers higher order of security.

[1]  Jonathan Katz,et al.  Attacking cryptographic schemes based on "perturbation polynomials" , 2009, CCS.

[2]  Ran Canetti,et al.  Efficient authentication and signing of multicast streams over lossy channels , 2000, Proceeding 2000 IEEE Symposium on Security and Privacy. S&P 2000.

[3]  Panayiotis Kotzanikolaou,et al.  SecMR - a secure multipath routing protocol for ad hoc networks , 2007, Ad Hoc Networks.

[4]  Adrian Perrig,et al.  Security and Privacy in Sensor Networks , 2003, Computer.

[5]  Ahmad Khonsari,et al.  Misbehavior resilient multi-path data transmission in mobile ad-hoc networks , 2006, SASN '06.

[6]  Ajay K. Gupta,et al.  DPDSN : Detection of packet-dropping attacks for wireless sensor networks , 2005 .

[7]  Haiyun Luo,et al.  Statistical en-route filtering of injected false data in sensor networks , 2004, IEEE INFOCOM 2004.

[8]  Haiyun Luo,et al.  Statistical en-route filtering of injected false data in sensor networks , 2005, IEEE J. Sel. Areas Commun..

[9]  Michael K. Reiter,et al.  Crowds: anonymity for Web transactions , 1998, TSEC.

[10]  Sushil Jajodia,et al.  An interleaved hop-by-hop authentication scheme for filtering of injected false data in sensor networks , 2004, IEEE Symposium on Security and Privacy, 2004. Proceedings. 2004.

[11]  C. Karlof,et al.  Secure routing in wireless sensor networks: attacks and countermeasures , 2003, Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, 2003..

[12]  Jacques Stern,et al.  Security Arguments for Digital Signatures and Blind Signatures , 2015, Journal of Cryptology.

[13]  Guiling Wang,et al.  Lightweight and Compromise-Resilient Message Authentication in Sensor Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.