Devendra Chaphekar, Minal Chaphekar, Mahendra Dwivedi
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Devendra Chaphekar1, Minal Chaphekar2, Mahendra Dwivedi3
1Department of Computer Science, Seth Phoolchand Agrawal Smriti Mahavidyalaya Nawapara.
2Department of Computer Science Govt. D.B. PG Girls College Raipur.
3Department of Computer Science Seth Phoolchand College, Nawapara.
Volume - 11,
Issue - 2,
Year - 2020
The information from social networks is useful for security agencies know about the terrorist group online activities. Automated forecasting methods can be of use for anticipating future workload of the human analyst and rescanning text documents. Brutal extremists have become proficient in using the internet and social media to propagate their ideologies, radicalize and recruit a generation that is active online. A brutal extremist uses brutal means to disrupt legitimate authority and spread brutalism. Brutal extremist is the organization that the speed ideology of hatred and instigate violence. A radical group organizing a peaceful protest is also considered as extremists, but not brutal extremists. Many modern groups, like the Westborough Baptist Church, have radical religious views, but these beliefs are not sufficient to classify them as brutal extremists. In this work algorithm, LDA has been used that provides loads of the complete brutal data dictionary pair from the dataset also the calculation of the result will be done by using JAVA in NetBeans IDE. Thus, the proposed algorithm is quite helpful in detecting the VE. Finally a perspective on the brutalism security annexes is discussed and here we analyzed the causes of brutalism and will overcome by applying the proposed algorithm.
Cite this article:
Devendra Chaphekar, Minal Chaphekar, Mahendra Dwivedi. A Survey Paper On: Cyber Security, Extremist Violation and Challenges Over Internet Communication. Research J. Engineering and Tech. 2020;11(2):98-102. doi: 10.5958/2321-581X.2020.00017.3
Devendra Chaphekar, Minal Chaphekar, Mahendra Dwivedi. A Survey Paper On: Cyber Security, Extremist Violation and Challenges Over Internet Communication. Research J. Engineering and Tech. 2020;11(2):98-102. doi: 10.5958/2321-581X.2020.00017.3 Available on: https://www.ijersonline.org/AbstractView.aspx?PID=2020-11-2-13
1. L. A. Overbey, G. McKoy, J. Gordon, and S. McKitrick, “Automated sensing and social network analysis in virtual worlds,” in Proc. IEEE Int. Conf. Intell. Secure. Inform. (ISI), Vancouver, BC, Canada, May 2010, pp. 179–184.
2. R. Torok, “‘Make a bomb in your mum's kitchen’: Cyber recruiting and socialization of ‘White Moors’ and homegrown Jihadists,” in Proc. 1st Austral. Counter Terrorism Conf., Nov. 2010, pp. 54–61.
3. W. V. Fitzgerald. (Jun. 2010). Interview With Westboro Baptist Church: Hate Name God. [Online]. Available: http://www.digitaljournal. com/article/2933642470 IEEE transactions on information forensics and security, VOL. 10, NO. 11, November 2015
4. M. Rogers, “The psychology of cyber-terrorism,” in Terrorists, Victims, and Society: Psychological Perspectives on Terrorism and Its Consequences. Chichester, U.K.: Wiley, 2003, pp. 77–92.
5. Conway, M., Khawaja, M., Lakhani, S., Reffin, J., Robertson, A. additionally, Weir, D., 2017. Disquieting Daesh: assessing takedown of online dread monger material and its belongings. Vox-Pol. URL: http://www.voxpol.eu/wpfb-record/dcuj5528-irritating daesh-1706- web-v2-pdf .
6. Bloom, M., Tiflati, H. likewise, Horgan, J., 2017. Investigating ISIS's Preferred Platform: Telegram. Dread based abuse and Political Violence, Vol. 29, pp.1-13.
7. Wagner, C., Singer, P., Karimi, F., Pfeffer, J. in addition, Strohmaier, M., 2017 (April). Analyzing from Social Networks with Attributes. In Proceedings of the 26th International Conference on World Wide Web (pp. 1181-1190).
8. T. Precht, Home created dread-based persecution and islamistradicalisation in europe, From change to mental fighting, 2007.
9. Berger, J.M. likewise, Morgan, J., 2015. The ISIS Twitter Census: Defining and portraying the quantity of occupants in ISIS supporters on Twitter.
10. J. Li et al., Social media: New perspectives to improve remote recognizing for emergency response, Proc. IEEE, vol. 105, no. 10, pp. 1900– 1912, Oct. 2017.
11. Sukhjit Singh Sehra, Jaiteg Singh and Hardeep Singh Rai, Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap: 1 July 2017.
12. Ruchika Aggarwal, Latika Gupta, Automatic text summarization, Ruchika Aggarwal et al, International Journal of Computer Science and Mobile Computing, Vol.6 Issue.6, June- 2017, pg. 158-167.
13. Nimai Chand Das Adhikari, Nishanth Domakonda, Chinmaya Chandan, An Intelligent Approach to Demand Forecasting, ICICT 2017, ISBN:978-1-5090-6697-1.
14. Lisa Kaati, Enghin Omer, NicoPrucha, Amendra Shrestha Detecting Multipliers of Jihadism on Twitter IEEE, 2015.
15. W. V. Fitzgerald. (Jun. 2010). Meeting With Westboro Baptist Church: Hate Name God. [Online]. Available: http://www.digitaljournal. com/article/2933642470 IEEE transactions on information forensics and security, Vol. 10, No. 11, November 2015.
16. J. R. Scanlon and M. S. Gerber, Automatic recognizable proof of computerized selection by unpleasant radicals, Secure. Exhort., vol. 3, no. 1, pp. 1– 10, Aug. 2014.
17. L. Bowman-Grieve, A psychological perspective on virtual systems supporting mental oppressor and devotee conviction frameworks as a device for enlistment, Secure. Instruct, vol. 2, no. 1, pp. 1– 5, 2013.
18. Wright, S., Denney, D., Pinkerton, A., Jansen, V. additionally, Bryden, J., 2016. Resurgent radicals: Quantitative examination concerning Jihadists who get suspended yet return on Twitter.
19. J. C. Scott, The Moral Economy of the Peasant: Rebellion and Subsistence in Southeast Asia. London, U.K.: Yale Univ. Press, 1976.
20. E. J. Wood, Insurgent Collective Action and Civil War in El Salvador. New York, NY, USA: Cambridge Univ. Press, 2003.
21. R. Jacob S. Gerber Scanlon and Matthew Forecasting Brutal Extremist Cyber Recruitment.