Mobile fog computing security: A user-oriented smart attack defense strategy based on DQL
| Autor: | Iftekhar Ahmad, Chin-Chen Chang, Meng Yuan, Muhammad Waqas, Anis Koubaa, Sadaqat Ur Rehman, Chengjie Shi, Zahid Halim, Muhammad Hanif, Shanshan Tu |
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| Přispěvatelé: | Repositório Científico do Instituto Politécnico do Porto |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Scheme (programming language)
Computer Networks and Communications Computer science 02 engineering and technology Computer security computer.software_genre Server Reinforcement learning 0202 electrical engineering electronic engineering information engineering Wireless Physical layer security Game theory computer.programming_language business.industry Node (networking) Physical layer 020206 networking & telecommunications Eavesdropping Mobile fog computing Smart attack 020201 artificial intelligence & image processing business Prospect theory computer |
| Zdroj: | Repositório Científico de Acesso Aberto de Portugal Repositório Científico de Acesso Aberto de Portugal (RCAAP) instacron:RCAAP |
| Popis: | Each fog node interacts with data from multiple end-users in mobile fog computing (MFC) networks. Malicious users can use a variety of programmable wireless devices to launch different modes of smart attacks such as impersonation attack, jamming attack, and eavesdropping attack between fog servers and legitimate users. The existing research in MFC lacks in the contributions of defense of smart attack and also requires in the discussions of subjective decision making by participants. Therefore, we propose a smart attack defense scheme for authorized users in MFC in this paper. First, we construct a static zero-sum game model between smart attackers and legitimate users based on prospect theory. Second, the double Q-learning (DQL) is proposed to restrain the attack motive of smart attackers in the dynamic environment. The proposed DQL method generates the optimum defense choice of legitimate users against smart attacks so that they can efficiently determine whether to use only physical layer security (PLS) to avoid those smart attacks. We use our scheme to contrast with the basic schemes, i.e., Q-learning scheme, the Sarsa scheme, and the greedy strategy. Experiment results prove that the proposed scheme can enhance the utility of legitimate users, restrain the attack motive of smart attackers, and further provide better security protection in the MFC environment. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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