NETWORK INTRUSION DETECTION SYSTEM USING MODIFIED BLOOM FILTER

Authors

  • K. Saravanan Assistant Professor, Department of Electronics and Communication Engineering, Nehru Institute of Technology, Coimbatore 641 105. Author
  • A. Yasmin Assistant Professor, Department of Electronics and Communication Engineering, Nehru Institute of Technology, Coimbatore 641 105. Author
  • A. Anitha Assistant Professor, Department of Electronics and Communication Engineering, Nehru Institute of Technology, Coimbatore 641 105. Author
  • Shreedharan M.D Associate Professor, Excel College of Architecture & Planning, Komarapalayam, Tamil Nadu. Author
  • Jeganathan M Assistant Professor, Department of Environment and Herbal Sciences, Tamil University, Thanjavur, Tamil Nadu Author

DOI:

https://doi.org/10.61841/0q4tg457

Keywords:

Bloom Filter, Network Intrusion Detection System.

Abstract

This paper presents an efficient implementation of the commonly used hash algorithm self- postulated in a modified bloom filter along with the details of standard bloom filter, with the counter bloom filter implementation. We have extended the report with a way of improvising the bloom filter in the network layer so that the threats are blocked in the network as well as to make the network safer.

A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Bloom filters allow false positives but the space savings often outweigh this drawback when the probability of an error is controlled. In this paper, we the architectural benefits of hybridizing the filter is clearly given, along with the way to construct it in an efficient manner. By future applications we mainly mean Network based intrusion detectors, which can help in controlling the advanced forms of intrusions threat detection. The aim of this report is to survey the ways in which Bloom filters have been used and modified in a variety of network problems, with the aim of providing a unified mathematical and practical framework for understanding them and stimulating their use in future applications.

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Published

30.06.2018

How to Cite

Saravanan, K., Yasmin, A., Anitha, A., M.D, S., & M, J. (2018). NETWORK INTRUSION DETECTION SYSTEM USING MODIFIED BLOOM FILTER. International Journal of Psychosocial Rehabilitation, 22(4), 1155-1168. https://doi.org/10.61841/0q4tg457