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    Game-theoretic approach to mitigate packet dropping in wireless Ad-hoc networks

    , Article 2011 IEEE Consumer Communications and Networking Conference, CCNC'2011, 8 January 2011 through 11 January 2011, Las Vegas, NV ; 2011 , Pages 163-165 ; 9781424487905 (ISBN) Tootaghaj, D. Z ; Farhat, F ; Pakravan, M. R ; Aref, M. R ; Sharif University of Technology
    2011
    Abstract
    Performance of routing is severely degraded when misbehaving nodes drop packets instead of properly forwarding them. In this paper, we propose a Game-Theoretic Adaptive Multipath Routing (GTAMR) protocol to detect and punish selfish or malicious nodes which try to drop information packets in routing phase and defend against collaborative attacks in which nodes try to disrupt communication or save their power. Our proposed algorithm outranks previous schemes because it is resilient against attacks in which more than one node coordinate their misbehavior and can be used in networks which wireless nodes use directional antennas. We then propose a game theoretic strategy, ERTFT, for nodes to... 

    Feature selection and intrusion detection in cloud environment based on machine learning algorithms

    , Article Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 ; 25 May , 2018 , Pages 1417-1421 ; 9781538637906 (ISBN) Javadpour, A ; Kazemi Abharian, S ; Wang, G ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    Characteristics and way of behavior of attacks and infiltrators on computer networks are usually very difficult and need an expert. In addition; the advancement of computer networks, the number of attacks and infiltrations is also increasing. In fact, the knowledge coming from expert will lose its value over time and must be updated and made available to the system and this makes the need for expert person always felt. In machine learning techniques, knowledge is extracted from the data itself which has diminished the role of the expert. Various methods used to detect intrusions, such as statistical models, safe system approach, neural networks, etc., all weaken the fact that it uses all the...