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      2 Whenever it does so a machine learning model based on its ability to recognize patterns from the past would detect the presence of bots through active monitoring and predictive analysis.

      3 If detected, it would terminate the current process and send out an alert.

      4 If the bot is not present then it would continue the process and run the anti-virus software, in order to remove any other malicious files.

      5 The Disaster recovery plan in the end would ensure that any important data is not lost and is backed up.

      1.5.1 System Architecture

      1.5.2 Future Scope

      While we are embracing new ways of digital interaction and more of our critical infrastructure is going digital, the parameters of the transformation underway are not understood by most of us. A better understanding of the global cyberspace architecture is required.

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      2. Cerli and D. Ramamoorthy (2015), Intrusion Detection System by Combining Fuzzy Logic with Genetic Algorithm, Global Journal of Pure and Applied Mathematics (GJPAM), vol. 11, no. 1.

      3. L.S. Wijesinghe, L.N.B. De Silva, G.T.A. Abhayaratne, P. Krithika, S.M.D.R. Priyashan, DhishanDhammearatchi (2016), Combating Cyber Using Artificial Intelligence System, International Journal of Scientific and Research Publications, vol. 6, no. 4.

      4. Naveen Kumar, Prakarti Triwedi, Pramod Singh Rathore, “An Adaptive Approach for image adaptive watermarking using Elliptical curve cryptography (ECC)”, First International Conference on Information Technology and Knowledge Management pp. 89–92, ISSN 2300-5963 ACSIS, Vol. 14 DOI: 10.15439/2018KM19

      5. Pramod Singh Rathore, “An adaptive method for Edge Preserving Denoising,” International Conference on Communication and Electronics Systems, Institute of Electrical and Electronics Engineers & PPG Institute of Technology (2017). Proceedings of the 2nd International Conference on Communication and Electronics Systems (ICCES 2017): 19-20 October, 2017.

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      7. Onashoga, S. Adebukola, Ajayi, O. Bamidele and A. Taofik (2013), “A Simulated Multiagent-Based Architecture for Intrusion Detection System”, (IJARAI) International Journal of Advanced Research in Artificial Intelligence, vol. 2, no. 4.

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      9. S. Singh and S. Silakari (2009), A Survey of Cyber Attack Detection Systems, IJCSNS International Journal of Computer Science and Network Security, vol. 9, no. 5

      11. Dr. Ritu Bhargava, Pramod Singh Rathore, Rameshwar Sangwa, February 18 Volume 4 Issue 2, “An Contemplated Approach for Criminality Data using Mining Algorithm”, International Journal on Future Revolution in Computer Science & Communication Engineering (IJFRSCE), pp. 236–240.

      1 *Corresponding author: [email protected]

      2

      Privacy Preserving Using Data Mining

       Chitra Jalota* and Dr. Rashmi Agrawal

       Manav Rachna International Institute of Research and Studies, Faridabad, India

       Abstract

      On the one hand, data mining techniques are useful to extract hidden knowledge from a large pool of data but on the other hand a number of privacy threats can be introduced by these techniques. The main aim of this chapter is to discuss a few of these issues along with a comprehensive discussion on various data mining techniques and their applications for providing security. An effective classification technique is helpful to categorize the users as normal users or criminals on the basis of the actions which they perform on social networks. It guides users to distinguish among a normal website and a phishing website. It is the task of a classification technique to always alert users from implementing malicious codes by labelling them as malicious. Intrusion detection is the most important application of data mining by applying different data mining techniques to detect it effectively and report the same in actual time so that essential and required arrangements can be made to stop the efforts made by the trespasser.

      Keywords: Data mining, security, intrusion detection, anamoly detection, outlier detection, classification, privacy preserving data mining

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