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Evaluation of Collaborative Intrusion Detection System Architectures in Mobile Edge Computing

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Mobile Edge Computing

Abstract

With the advent of 5th Generation (5G) of mobile networks, a diverse range of new computer networking technologies are being devised to meet the stringent demands of applications that require ultra-low latency, high bandwidth and geolocation-based services. Mobile Edge Computing (MEC) is a prominent example of such an emerging technology, which provides cloud computing services at the edge of the network using mobile base stations. This architectural shift of services from centralised cloud data centers to the network edge, helps reduce bandwidth usage and improve response time, meeting the ultra-low latency requirements laid out for 5G. However, MEC also inherits some of the vulnerabilities affecting traditional networks and cloud computing, such as coordinated attacks. Previous works have proposed the use of Intrusion Detection Systems (IDS), specifically Collaborative Intrusion Detection Systems (CIDS), which have proven to be effective in identifying distributed attacks. However, identifying the right CIDS model is not straightforward due to the tradeoff between different factors such as detection accuracy, network overhead, computation and memory overhead. In this chapter, we outline some of the characteristics relevant for evaluating CIDS deployment models and survey existing CIDS architectures in the context of MEC, while presenting novel strategies and architectures of our own.

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Author information

Authors and Affiliations

  1. School of Computing and Information Systems, The University of Melbourne, Melbourne, Australia

    Rahul Sharma & Christopher Leckie

  2. Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, Australia

    Chien Aun Chan

Authors
  1. Rahul Sharma
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  2. Chien Aun Chan
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  3. Christopher Leckie
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Corresponding author

Correspondence to Rahul Sharma .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Mahishadal Raj College, Mahishadal, West Bengal, India

    Anwesha Mukherjee

  2. Centre of Mobile Cloud Computing Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal, India

    Debashis De

  3. Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Kharagpur, Kharagpur, West Bengal, India

    Soumya K. Ghosh

  4. Cloud Computing and Distributed Systems (CLOUDS) Laboratory, School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, Australia

    Rajkumar Buyya

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Sharma, R., Chan, C.A., Leckie, C. (2021). Evaluation of Collaborative Intrusion Detection System Architectures in Mobile Edge Computing. In: Mukherjee, A., De, D., Ghosh, S.K., Buyya, R. (eds) Mobile Edge Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-69893-5_15

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  • DOI: https://doi.org/10.1007/978-3-030-69893-5_15

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