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A New and Secure Intrusion Detecting System for Detection of Anomalies Within the Big Data

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Cloud Computing for Geospatial Big Data Analytics

Part of the book series: Studies in Big Data ((SBD,volume 49))

Abstract

With the rapid growth of various technologies the level for the security has even become quite challenging and for the recognition frameworks in anomaly, several methods and methodology and actions region unit created to follow novel attacks on the frameworks or systems. Detection frameworks in anomaly upheld predefined set of instructions and protocols. It’s hard to mandate all strategies, to beat this countless machine learning plans and downside unit existing. Unique issue is Keyed Intrusion Detection System namely kids that are completely relying on key privacy and procedure used to produce the key. All through this algorithmic program, intruder only ready to recoup or improve key by communicating with the Intrusion Detection System and perspective the tip result after it and by abuse this theme can’t prepared to meet security norms. In this way supported learning we’d quite recently like the topic that can assist us with providing extra security on Data Storage. To reduce the attack risk, a dynamic key theory is bestowed and analyzed we’ve an inclination to face live about to planned theme for extra security that is ready to be secure delicate information of fluctuated domains like in consideration area enduring associated information like contact points of interest and antiquity.

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Acknowledgements

The authors would like to thank the management of Koneru Lakshmaiah Education Foundation (Deemed to be University) for their support throughout the completion of this project discussions and comments.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, 522502, Guntur, Andhra Pradesh, India

    Amara S. A. L. G. Gopal Gupta, G. Syam Prasad & Soumya Ranjan Nayak

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  1. Amara S. A. L. G. Gopal Gupta
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  2. G. Syam Prasad
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  3. Soumya Ranjan Nayak
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Corresponding author

Correspondence to Soumya Ranjan Nayak .

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Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India

    Himansu Das

  2. School of Computer Application, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India

    Rabindra K. Barik

  3. Center for Robust Speech Systems, University of Texas at Dallas, Richardson, TX, USA

    Harishchandra Dubey

  4. Department of Computer Science and Engineering, National Institute of Technology, Meghalaya, Shillong, Megalaya, India

    Diptendu Sinha Roy

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Gupta, A.S.A.L.G.G., Prasad, G.S., Nayak, S.R. (2019). A New and Secure Intrusion Detecting System for Detection of Anomalies Within the Big Data. In: Das, H., Barik, R., Dubey, H., Roy, D. (eds) Cloud Computing for Geospatial Big Data Analytics. Studies in Big Data, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-030-03359-0_8

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