A game-theoretic analysis of energy-depleting jamming attacks with a learning counterstrategy
| Autor: | Michele Zorzi, Andrea Zanella, Federico Chiariotti, Nicola Laurenti, Chiara Pielli |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Radio interference
Computer Networks and Communications Computer science Network packet Reliability (computer networking) Node (networking) 020208 electrical & electronic engineering Time synchronization Media access control Multichannel Wireless sensor networks 020206 networking & telecommunications Jamming 02 engineering and technology Computer security computer.software_genre Bayesian game Complete information 0202 electrical engineering electronic engineering information engineering Heuristics Wireless sensor network computer |
| Popis: | Jamming may become a serious threat in Internet of Things networks of battery-powered nodes, as attackers can disrupt packet delivery and significantly reduce the lifetime of the nodes. In this work, we model an active defense scenario in which an energy-limited node uses power control to defend itself from a malicious attacker, whose energy constraints may not be known to the defender. The interaction between the two nodes is modeled as an asymmetric Bayesian game where the victim has incomplete information about the attacker. We show how to derive the optimal Bayesian strategies for both the defender and the attacker, which may then serve as guidelines to develop and gauge efficient heuristics that are less computationally expensive than the optimal strategies. For example, we propose a neural-network-based learning method that allows the node to effectively defend itself from the jamming with a significantly reduced computational load. The outcomes of the ideal strategies highlight the tradeoff between node lifetime and communication reliability and the importance of an intelligent defense from jamming attacks. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|