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Context-Aware Conditional Probabilistic Hyper-exponential Reputation Technique for Mitigating Byzantine Attacks

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Smart Secure Systems – IoT and Analytics Perspective (ICIIT 2017)

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Abstract

Data delivery in ad hoc networks requires co-operation as the predominant factor for ensuring pause-less communication between the nodes due to their self-organizing nature. This decentralized feature of ad hoc networks enables adversaries to compromise nodes through Byzantine attacks and induce them to act maliciously for degrading the performance of the network. These Byzantine nodes degrade the performance by selectively dropping the packets, modifying the packets or dropping the packets without forwarding for the sake of conserving their own energy. In this paper, we propose a Context-aware Conditional Probabilistic Hyper-exponential Reputation Scheme (CCPHRT) for improving the efficiency and effectiveness in detecting byzantine nodes. This CCPHRT mitigates byzantine nodes based on Hyper-exponential Conditional Survivability Factor (HCSF) as each mobile node’s behavioural transition is hypo-exponentially distributed as the inter-transition time is independent and exponentially modeled. Extensive simulations are performed and the obtained results prove that CCPHRT is effective in improving the performance of the network than the compared techniques used for investigation. CCPHRT also facilitates a dynamic byzantine node isolation degree of 34% which is better than the baseline byzantine mitigation techniques used for study.

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Authors and Affiliations

  1. Pondicherry Engineering College, Puducherry, India

    Geetha Achuthan & Sreenath Niladuri

  2. College of Engineering, Anna University, Chennai, India

    A. G. Sareeka

Authors
  1. Geetha Achuthan
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  2. Sreenath Niladuri
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  3. A. G. Sareeka
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Correspondence to Geetha Achuthan .

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Editors and Affiliations

  1. George Washington University, Washington, District of Columbia, USA

    Guru Prasadh Venkataramani

  2. Intel Microarchitecture Research Lab, Santa Clara, California, USA

    Karthik Sankaranarayanan

  3. Anna University, Chennai, India

    Saswati Mukherjee

  4. Anna University, Chennai, India

    Kannan Arputharaj

  5. Anna University, Chennai, India

    Swamynathan Sankara Narayanan

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Achuthan, G., Niladuri, S., Sareeka, A.G. (2018). Context-Aware Conditional Probabilistic Hyper-exponential Reputation Technique for Mitigating Byzantine Attacks. In: Venkataramani, G., Sankaranarayanan, K., Mukherjee, S., Arputharaj, K., Sankara Narayanan, S. (eds) Smart Secure Systems – IoT and Analytics Perspective. ICIIT 2017. Communications in Computer and Information Science, vol 808. Springer, Singapore. https://doi.org/10.1007/978-981-10-7635-0_12

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  • DOI: https://doi.org/10.1007/978-981-10-7635-0_12

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