| Title | Secure Wireless Sensor Network Energy Optimization Model with Game Theory and Deep Learning Algorithm |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | AnishFathima, B., Mahaboob, M., Kumar, S.Gokul, Jabakumar, A.Kingsly |
| Conference Name | 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS) |
| Keywords | Adversarial network algorithm, Cyberspace, Data security, Deep Learning, Energy efficiency, Energy optimization, energy resources, game theoretic security, game theory, Games, Human Behavior, human factors, mathematical models, Metrics, pubcrawl, Scalability, Wireless sensor networks |
| Abstract | Rational and smart decision making by means of strategic interaction and mathematical modelling is the key aspect of Game theory. Security games based on game theory are used extensively in cyberspace for various levels of security. The contemporary security issues can be modelled and analyzed using game theory as a robust mathematical framework. The attackers, defenders and the adversarial as well as defensive interactions can be captured using game theory. The security games equilibrium evaluation can help understand the attackers' strategies and potential threats at a deeper level for efficient defense. Wireless sensor network (WSN) designs are greatly benefitted by game theory. A deep learning adversarial network algorithm is used in combination with game theory enabling energy efficiency, optimal data delivery and security in a WSN. The trade-off between energy resource utilization and security is balanced using this technique. |
| Notes | ISSN: 2575-7288 |
| DOI | 10.1109/ICACCS54159.2022.9785348 |
| Citation Key | anishfathima_secure_2022 |
Secure Wireless Sensor Network Energy Optimization Model with Game Theory and Deep Learning Algorithm