1. 1. J. B. S. Christensen and N. Beuschau, “Ransomware detection and mitigation tool.”
   2. An Efficient Ransomware Detection System.”
   3. S. B. Surati and G. I. Prajapati, “A Review on Ransomware Detection & Prevention,” Int. J. Res. Sci. Innov. |, vol. IV, 2017.
   4. D. Morato, E. Berrueta, E. Magaña, and M. Izal, “Ransomware early detection by the analysis of file sharing traffic,” J. Netw. Comput. Appl., vol. 124, pp. 14–32, Dec. 2018, doi: 10.1016/j.jnca.2018.09.013.
   5. S. Alsoghyer and I. Almomani, “Ransomware Detection System for Android Applications,” Electronics, vol. 8, no. 8, p. 868, Aug. 2019, doi: 10.3390/electronics8080868.
   6. E. Pazik, “Ransomware: Attack Vectors, Mitigation and Recovery,” 2017.
   7. M. Akbanov, V. G. Vassilakis, and M. D. Logothetis, “Ransomware detection and mitigation using softwaredefined networking: The case of WannaCry,” Comput. Electr. Eng., vol. 76, pp. 111–121, 2019, doi: 10.1016/j.compeleceng.2019.03.012.
   8. S. Saxena and H. K. Soni, “Strategies for ransomware removal and prevention,” in Proceedings of the 4th IEEE International Conference on Advances in Electrical and Electronics, Information, Communication and Bio-Informatics, AEEICB 2018, 2018, doi: 10.1109/AEEICB.2018.8480941.
   9. A., M. Poriye, and V. Kumar, “Ransomware Detection And Prevention,” Int. J. Comput. Sci. Eng., vol. 6, no. 5, pp. 900–905, 2018, doi: 10.26438/ijcse/v6i5.900905.
   10. H. J. Chittooparambil, B. Shanmugam, S. Azam, K. Kannoorpatti, M. Jonkman, and G. N. Samy, “A review of ransomware families and detection methods,” in Advances in Intelligent Systems and Computing, 2019, vol. 843, pp. 588–597, doi: 10.1007/978-3-319-99007- 1_55.
   11.  Y. Solanki, “Detection and Prevention for Ransomware using Machine Learning,” Int. J. Res. Appl. Sci. Eng. Technol., vol. 7, no. 6, pp. 632–635, 2019, doi: 10.22214/ijraset.2019.6110.
   12. Ishleen Kaur, Gagandeep Singh Narula, Ritika Wason, Vishal Jain and Anupam Baliyan, “Neuro Fuzzy— COCOMO II Model for Software Cost Estimation”, International Journal of Information Technology (BJIT), Volume 10, Issue 2, June 2018, page no. 181 to 187 having ISSN No. 2511-2104.
   13. Ishleen Kaur, Gagandeep Singh Narula, Vishal Jain, “Differential Analysis of Token Metric and Object Oriented Metrics for Fault Prediction”, International Journal of Information Technology (BJIT), Vol. 9, No. 1, Issue 17, March, 2017, page no. 93-100 having ISSN No. 2511-2104.
   14. Basant Ali Sayed Alia, Abeer Badr El Din Ahmedb, Alaa El Din Muhammad,El Ghazalic and Vishal Jain, "Incremental Learning Approach for Enhancing the Performance of Multi-Layer Perceptron for Determining the Stock Trend", International Journal of Sciences: Basic and Applied Research (IJSBAR), Jordan, page no. 15 to 23, having ISSN 2307-4531.
   15. RS Venkatesh, PK Reejeesh, S Balamurugan, S Charanyaa, “Further More Investigations on Evolution of Approaches for Cloud Security”, International Journal of Innovative Research in Computer and Communication Engineering , Vol. 3, Issue 1, January 2015
   16. K Deepika, N Naveen Prasad, S Balamurugan, S Charanyaa, “Survey on Security on Cloud Computing by Trusted Computer Strategy”, International Journal of Innovative Research in Computer and Communication Engineering, 2015
   17. P Durga, S Jeevitha, A Poomalai, M Sowmiya, S Balamurugan, “Aspect Oriented Strategy to model the Examination Management Systems”, International Journal of Innovative Research in Science, Engineering and Technology , Vol. 4, Issue 2, February 2015