TY - GEN
T1 - Secure Data Aggregation with Mean Field Extensive Game Theoretic Framework
AU - Chopra, Khyati
AU - Bose, Ranjan
AU - Joshi, Anupam
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/26
Y1 - 2018/9/26
N2 - In this paper, game theoretic framework is used as a mathematical tool to address security problems in mobile wireless sensor network (MWSN). In most of the existing works, only attacker and a defender are considered as the two players of the game. With the use of recent advancements made in the mean field game theory, we have proposed a novel extensive game with multiple players for MWSN security, such that the aggregator node can securely compute aggregation data even in the presence of an attack. The proposed scheme enables the aggregator node and an individual node in MWSN to strategically make defense decisions and hence, the confidential data could be faithfully transmitted to base station (BS) for security. Also, each node in this dynamic distributed network, knows the information about its own state and the information about the other nodes' aggregate effect in the MWSN. Optimal strategic equilibrium solution to our proposed mean field extensive game is given, such that the utility of each player is maximized in the game. Extensive game analysis and study shows that our proposed dynamic algorithm strategically outperforms existing static approach.
AB - In this paper, game theoretic framework is used as a mathematical tool to address security problems in mobile wireless sensor network (MWSN). In most of the existing works, only attacker and a defender are considered as the two players of the game. With the use of recent advancements made in the mean field game theory, we have proposed a novel extensive game with multiple players for MWSN security, such that the aggregator node can securely compute aggregation data even in the presence of an attack. The proposed scheme enables the aggregator node and an individual node in MWSN to strategically make defense decisions and hence, the confidential data could be faithfully transmitted to base station (BS) for security. Also, each node in this dynamic distributed network, knows the information about its own state and the information about the other nodes' aggregate effect in the MWSN. Optimal strategic equilibrium solution to our proposed mean field extensive game is given, such that the utility of each player is maximized in the game. Extensive game analysis and study shows that our proposed dynamic algorithm strategically outperforms existing static approach.
KW - data aggregation
KW - extensive game theory
KW - mobile wireless sensor networks (MWSNs)
KW - security
UR - http://www.scopus.com/inward/record.url?scp=85055450808&partnerID=8YFLogxK
U2 - 10.1109/SPIN.2018.8474175
DO - 10.1109/SPIN.2018.8474175
M3 - Conference contribution
AN - SCOPUS:85055450808
T3 - 2018 5th International Conference on Signal Processing and Integrated Networks, SPIN 2018
SP - 1
EP - 6
BT - 2018 5th International Conference on Signal Processing and Integrated Networks, SPIN 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Signal Processing and Integrated Networks, SPIN 2018
Y2 - 22 February 2018 through 23 February 2018
ER -