| Title | Learning Automata Based Secure Multi Agent RFID Authentication System |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Kaul, Sonam Devgan, Hatzinakos, Dimitrios |
| Conference Name | 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT) |
| Date Published | jul |
| Keywords | authentication, automata based secure multiagent RFID authentication system, cryptographic protocols, data privacy, expertly transfer utility, Human Behavior, learning automata, long term benefit, Multi Agent, multi-agent systems, multiagent intelligent system, privacy, pubcrawl, radio frequency identification, radiofrequency identification, Resiliency, RFID, RFID scenario, RFID system, RFID tags, RFID technologies, RFIDs, Scyther, security, sensitive data, technological developments, telecommunication security, utility function |
| Abstract | Radio frequency identification wireless sensing technology widely adopted and developed from last decade and has been utilized for monitoring and autonomous identification of objects. However, wider utilization of RFID technologies has introduced challenges such as preserving security and privacy of sensitive data while maintaining the high quality of service. Thus, in this work, we will deliberately build up a RFID system by utilizing learning automata based multi agent intelligent system to greatly enhance and secure message transactions and to improve operational efficiency. The incorporation of these two advancements and technological developments will provide maximum benefit in terms of expertly and securely handle data in RFID scenario. In proposed work, learning automata inbuilt RFID tags or assumed players choose their optimal strategy via enlarging its own utility function to achieve long term benefit. This is possible if they transmit their utility securely to back end server and then correspondingly safely get new utility function from server to behave optimally in its environment. Hence, our proposed authentication protocol, expertly transfer utility from learning automata inbuilt tags to reader and then to server. Moreover, we verify the security and privacy of our proposed system by utilizing automatic formal prover Scyther tool. |
| DOI | 10.1109/ICCCNT45670.2019.8944800 |
| Citation Key | kaul_learning_2019 |
Learning Automata Based Secure Multi Agent RFID Authentication System