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Detection of data integrity attacks by constructing an effective intrusion detection system

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Abstract

Network users are heavily targeted by data integrity attacks that affect the development of new security techniques. The main challenge in network security is to identify this kind of attack for the improvement of growing mechanisms. In this paper, a data integrity based effective intrusion detection system (DI-EIDS) is constructed to prevent the network with a high detection rate and low false alarm rates. It is classified into two phases; data sampling and selection of features. In the data sampling process, attacks are detected and inference based on the sample signatures. In this process, the Deviation forest (d-forest) is used to remove barriers; Grey Wolf Optimization (GWO) is used for sampling ratio optimization and Black forest (BF) classifier to obtain the best training data. To select the best features, GWO and BF are repeatedly used. Finally, DI-EIDS based on the black forest is constructed using the best training data set obtained by data sampling and feature selection. Rare Integrity attacks are detected in this technique when compared with other algorithms. Experimental results are analyzed using different datasets with a 22% sampling rate. The performance results show a higher rate of detection with low false-positive rates.

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Acknowledgment

This research work has been confidentially acknowledged by Anna University recognized research center lab at V V College of Engineering, Tisaiyanvilai, India.

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No funding source has been acknowledged.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, V V College of Engineering, Tisaiyanvilai, India

    R. B. Benisha & S. Raja Ratna

Authors
  1. R. B. Benisha
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  2. S. Raja Ratna
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Contributions

R.B.Benisha has published two SCI journals four International conference papers and one International journal paper. Dr.S.Raja Ratna has published Four SCI journals and five Scopus indexed journals. Her research interests include denial-of-service attacks, jamming attacks, secure routing algorithm and security in networks.

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Correspondence to R. B. Benisha.

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Conflict of interest

R. B. Benisha and Dr. S. Raja Ratna declares that they have no Competing interests.

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This article does not contain any studies with animal subjects performed by the any of the authors.

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Benisha, R.B., Ratna, S.R. Detection of data integrity attacks by constructing an effective intrusion detection system. J Ambient Intell Human Comput 11, 5233–5244 (2020). https://doi.org/10.1007/s12652-020-01850-1

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  • DOI: https://doi.org/10.1007/s12652-020-01850-1

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