Survey Report on Cyber Crimes and Cyber Criminals Get Protected from Cyber Crimes: Review Paper
Marripelli Koteshwar1 , Bipin Bihari Jaya Singh2
Section:Review Paper, Product Type: Journal Paper
Volume-7 ,
Issue-12 , Page no. 99-109, Dec-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i12.99109
Online published on Dec 31, 2019
Copyright © Marripelli Koteshwar, Bipin Bihari Jaya Singh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Marripelli Koteshwar, Bipin Bihari Jaya Singh, “Survey Report on Cyber Crimes and Cyber Criminals Get Protected from Cyber Crimes: Review Paper,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.12, pp.99-109, 2019.
MLA Style Citation: Marripelli Koteshwar, Bipin Bihari Jaya Singh "Survey Report on Cyber Crimes and Cyber Criminals Get Protected from Cyber Crimes: Review Paper." International Journal of Computer Sciences and Engineering 7.12 (2019): 99-109.
APA Style Citation: Marripelli Koteshwar, Bipin Bihari Jaya Singh, (2019). Survey Report on Cyber Crimes and Cyber Criminals Get Protected from Cyber Crimes: Review Paper. International Journal of Computer Sciences and Engineering, 7(12), 99-109.
BibTex Style Citation:
@article{Koteshwar_2019,
author = {Marripelli Koteshwar, Bipin Bihari Jaya Singh},
title = {Survey Report on Cyber Crimes and Cyber Criminals Get Protected from Cyber Crimes: Review Paper},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2019},
volume = {7},
Issue = {12},
month = {12},
year = {2019},
issn = {2347-2693},
pages = {99-109},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4981},
doi = {https://doi.org/10.26438/ijcse/v7i12.99109}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i12.99109}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4981
TI - Survey Report on Cyber Crimes and Cyber Criminals Get Protected from Cyber Crimes: Review Paper
T2 - International Journal of Computer Sciences and Engineering
AU - Marripelli Koteshwar, Bipin Bihari Jaya Singh
PY - 2019
DA - 2019/12/31
PB - IJCSE, Indore, INDIA
SP - 99-109
IS - 12
VL - 7
SN - 2347-2693
ER -
VIEWS | XML | |
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Abstract
Digital Crime is a wrongdoing which includes the utilization of computerized innovations in commission of offense, coordinated to registering and correspondence advances. The cutting edge methods that are multiplying towards the utilization of web movement brings about making misuse, defenselessness making a reasonable path for exchanging secret information to submit an offense through illicit action. The movement includes like assaulting on Information focus Data System, burglary, youngster sex entertainment assembled pictures, online exchange misrepresentation, web deal extortion and furthermore organization in web vindictive exercises, for example, infection, worm and outsider maltreatment like phishing, email tricks and so on. The all-inclusive methodology of system like web at all dimensions of system needs to recoup from perpetrating illicit action in everywhere throughout the world and to stop the criminal nature by ensuring unlawful movement by upholding distinctive dimension of firewall setting inside its disconnected control for each country so as to screen and anticipate violations did in the internet. System security controls are utilized to avoid the entrance of programmers in systems which incorporates firewall, virtual private systems and encryption calculations. Out of these, the virtual private system assumes an indispensable job in keeping programmers from getting to the systems. Virtual Private Network (VPN) furnishes end clients with an approach to secretly get to data on their system over an open system foundation, for example, the web.
Key-Words / Index Term
cyber-crime, cyber criminals, cyber-crime hackers, protectedcateogories, cyber stalking
References
[1] N. Kumari and A. K. Mohapatra, “An insight into digital forensics branches and tools,” Proceedings of theInternational Conference on Computational Techniques in Information and Communication Technologies, 2016.
[2] M. Reith, C. Carr, and G. Gunsch, “An examination of digital forensic models,” International Journal of DigitalEvidence, vol. 1, no. 3, Fall 2002.
[3] E. Casey, Digital Evidence and Computer Crime: Forensic Science, Computers and the Internet. San Diego, CA: Academic Press, 3rd edition, 2011, chapter 1.
[4] “Digital forensics,” Wikipedia, the free encyclopedia,https://en.wikipedia.org/wiki/Digital_forensics.
[5] Dr. V.Tayal,” Cyber Piracy in the Indian Information Technology Regime: Issues and Challenges” Cyber Law CybercrimeInternet an E-commerce, By Prof. Vimlendutayal, Bharat.
[6] C. Vidya, ”Cybercrimeto Cyber Terrorism”, Amicus Books, The ICFAI University Press.
[7] Richard Power, "1999 CSI/FBI Computer Crime and Security Survey,” Computer Security Issues & Trends, Computer Security Institute, winter 1999.
[8] Denning D E, “An Cyber attacks-Detection Model,” In IEEE Transaction on Software Engineering, Vol. Se-13, No. 2, pp. 222-232, February 1987.
[9] Lee, W, Stolfo S and Mok K , “Adaptive Cyber attacks Detection: A Data Mining Approach,” In Artificial Intelligence Review, Kluwer Academic Publishers, 14(6), pp. 533 - 567, December 2000.
[10] Satinder Singh, Guljeet Kaur, “Unsupervised Anomaly Detection In Network Cyber attacks Detection Using Clusters,” Proceedings of National Conference on Challenges & Opportunities in Information Technology RIMT-IET, MandiGobindgarh. March 23, 2007.
[11] Eric Bloedorn , Alan D. Christiansen , William Hill , Clement Skorupka , Lisa M. Talbot , Jonathan Tivel, “Data Mining for Network Cyber attacks Detection: How to Get Started,” CiteSeer, 2001
[12] L. Portnoy, “Cyber attacks Detection with Unlabeled Data Using Clustering,” Undergraduate Thesis, Columbia University, 2000.
[13] TheodorosLappas and KonstantinosPelechrinis, “Data Mining Techniques for (Network) Cyber attacks Detection Systems,” http://citeseerx.ist.psu.edu/viewdoc/ download? doi=10.1.1.120.2533&rep=rep1&type=pdf.
[14] Dewan Md. Farid, NouriaHarbi, SumanAhmmed, Md. Zahidur Rahman, and Chowdhury Mofizur Rahman, “Mining Network Data for Cyber attacks Detection through Naïve Bayesian with Clustering”, World Academy of Science, Engineering and Technology, 2010.
[15] The KDD Archive. KDD99 cup dataset, 1999. http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html
[16] [ X. Li and N. Ye., “A supervised clustering algorithm for computer cyber attacks detection,” Knowledge and Information Systems, 8, pp498-509, ISSN 0219-1377, 2005
[17] Kruegel C., Mutz D., Robertson W., Valeur F., “Bayesian event classification for cyber attacks detection,” In: Proceedings of the 19th Annual Computer Security Applications Conference; 2003.
[18] Portnoy L., Eskin E., Stolfo S.J., “Cyber attacks detection with unlabeled data using clustering,” In: Proceedings of The ACM Workshop on Data Mining Applied to Security; 2001.
[19] Paxson V., “Bro: A System for Detecting Network Intruders in Real-Time”, Computer Networks, 31(23-24), pp. 2435-2463, 14 Dec. 1999.
[20] D.Barbara, J.Couto, S.Jajodia, and N.Wu, "ADAM: A test bed for exploring the use of data mining in cyber attacks detection”, SIGMOD, vol30, no.4, pp 15-24, 2001.
[21] P.Domingos, and M.J. Pizzani, "On the optimality of the simple Bayesian classifier under zero-one loss”, m/c learning, Vol.29, no2-3, pp 103-130, 1997.
[22] F. Provost, and T. Fawcett, “Robust classification for imprecise environment,” Machine Learning, vol. 42/3, 2001, pp. 203-231.
[23] Athanasios Papoulis and S. Unnikrishna Pillai,. "Probability, Random Variables and stochastic Processes ", McGraw-Hill, Fourth Edition, ISBN 0073660116, 2002
[24] P. Kabiri and A.A. Ghorbani, “Research on Cyber attacks Detection and Response: A Survey,” International Journal of Network Security, 1, 84-102, September 2005
[25] A. Patcha and J-M. Park, “An overview of anomaly detection techniques: Existing solutions and latest technological trends,” Comput. Netw., 51, 3448-3470. ISSN 1389-1286. 2007.
[26] [ T.M. Mitchell. Machine Learning. McGraw-Hill. ISBN: 0-07-115467-1, 1997.
[27] [21] N. Ben Amor, S. Benferhat and Z. Elouedi, “Naive Bayes vs Decision Trees in Cyber attacks Detection Systems,” Proceedings of the ACM symposium on Applied computing, ISBN 1-58113-812-1, pages 420-424, New York, USA, 2004.
[28] M. Panda and M.R. Patra, “Network cyber attacks detection using naive bayes,” IJCSNS International Journal of Computer Science and Network Security, 7, 258-263, 2007
[29] F. Gharibian and A.A. Ghorbani, “Comparative Study of Supervised Machine Learning Techniques for Cyber attacks Detection,” In CNSR ’07: Proceedings of the Fifth Annual Conference on Communication Networks and Services Research, Pages 350-358, Washington, DC, USA, 2007
[30] L. Portnoy, E. Eskin and S. Stolfo, “Cyber attacks Detection With Unlabeled Data Using Clustering,” In Proceedings of the ACM Workshop on Data Mining Applied to Security, 2001.
[31] K. Leung and C. Leckie, “Unsupervised anomaly detection in network cyber attacks detection using clusters,” Proceedings of the 28th Australasian conference on Computer Science, ISBN 1-920-68220-1, pages 333-342, Darlinghurst, Australia, Australia, 2005.
[32] W. Wang, X. Guan and X. Zhang, “Processing of massive audit data streams for real-time anomaly cyber attacks detection,” Comput. Commun., 31, 58- 72. ISSN 0140-3664, 2008
[33] J. Song, K. Ohira, H. Takakura, Y. Okabe and Y. Kwon, “A Clustering Method for Improving Performance of Anomaly-Based Cyber attacks Detection System,” IEICE Transactions on Information and Systems, E91-D, 1282-1291. ISSN 0916-8532, 2008
[34] E.J. Spinosa, A.P. de Leon F. de Carvalho and J. Gama, “Cluster-based novel concept detection in data streams applied to cyber attacks detection in computer networks,” Proceedings of the ACM symposium on Applied computing, pages 976-980. ACM. ISBN 978-1-59593-753-7 , New York, NY, USA, 2008
[35] E. Leon, O. Nasaoui and J. Gomez, “Anomaly Detection Based on Unsupervised Niche Clustering with Application to Network Cyber attacks Detection,” In Proceedings of the Congress of Evolutionary Computation, 2004.
[36] O. Nasraoui and R. Krishnapuram, “A Robust Estimator Based on Density and Scale Optimization and its Application to Clustering,” In Proceedings of the Fifth IEEE International Conference on Fuzzy Systems, volume 2, pages 1031 – 1035, 1999.
[37] Harry Zhang, “The Optimality of Naive Bayes". FLAIRS conference 2004.
[38] Caruana, R. and Niculescu-Mizil, A., "An empirical comparison of supervised Learning algorithms". Proceedings of the 23rd international conference on Machine learning, 2006.
[39] George H. John and Pat Langley, “Estimating Continuous Distributions in Bayesian Classifiers,” Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence. pp. 338-345. Morgan Kaufmann, San Mateo, 1995.
[40] An Overview of Issues in Testing Cyber attacks Detection Systems, http://www.net-security.org/article.php?id=528, 2003.
[41] [35] ShengYi Jiang, Xiaoyu Song, Hui Wang, Jian-Jun Han, Qing-Hua Li, “A clustering-based method for unsupervised cyber attacks detections”, Pattern Recognition Letters 27 (2006) 802–810.
[42] SandhyaPeddabachigari, Ajith Abraham, CrinaGrosan, Johnson Thomas, “Modeling cyber attacks detection system using hybrid intelligent systems”, Journal of Network and Computer Applications 30 (2007) 114–132.
[43] Cheng Xiang, Png Chin Yong, Lim SweeMeng, “Design of multiple-level hybrid classifier for cyber attacks detection system using Bayesian clustering and decision trees”, Pattern Recognition Letters 29 (2008) 918–924.
[44] Arman Tajbakhsh, Mohammad Rahmati, AbdolrezaMirzaei, “Cyber attacks detection using fuzzy association rules”, Applied Soft Computing 9 (2009) 462–469.
[45] B. Abdullah, I. Abd-alghafar, Gouda I. Salama and A. Abd-alhafez, “Performance Evaluation of a Genetic Algorithm Based Approach to Network Cyber attacks Detection System”, 13th International Conference on Aerospace Sciences & Aviation Technology, ASAT- 13, May 26 – 28, 2009.
[46] Kamran Shafi, Hussein A. Abbass, “An adaptive genetic-based signature learning system for cyber attacks detection”, Expert Systems with Applications 36 (2009) 12036–12043.
[47] Shi-Jinn Horng, Ming-Yang Su, Yuan-Hsin Chen, Tzong-Wann Kao, Rong-Jian Chen, Jui-Lin Lai,CitraDwiPerkas, “A novel cyber attacks detection system based on hierarchical clustering and support vector machines”, Expert Systems with Applications 38 (2011) 306–313.
[48] Muamer N. Mohammad, NorrozilaSulaiman, Osama AbdulkarimMuhsin, “A Novel Cyber attacks Detection System by using Intelligent Data Mining in Weka Environment”, Procedia Computer Science 3 (2011) 1237–1242.
[49] Z. Muda, W. Yassin, M. N. Sulaiman and N. I. Udzir, “A K-Means and Naïve Bayes Learning Approach for Better Cyber attacks Detection”, Information Technology Journal, Vol. 10 No. 3, pp: 648-655, 2011.
[50] HeshamAltwaijry and Saeed Algarny, “Bayesian based cyber attacks detection system”, Journal of King Saud University – Computer and Information Sciences, Vol. 24, pp: 1–6, 2012.
[51] Li Hanguang and Ni Yu, “Cyber attacks Detection Technology Research Based on Apriori Algorithm”, Elsevier, Physics Procedia, Vol. 24, pp: 1615-1620, 2012.
[52] Manikandan R., Oviya P and Hemalatha C, “A New Data Mining Based Network Cyber attacksDetection Model”, Journal of Computer Application, Vol. 5, No. EICA2012-1, pp: 1-10, 2012.
[53] VikasMarkam, Lect. Shirish Mohan Dubey, “General Study of Associations rule mining in Cyber attacks Detection System”, International Journal of Emerging Technology and Advanced Engineering, Volume 2, Issue 1, January 2012.
[54] NanditaSengupta, JaydeepSen, JayaSil, MoumitaSaha, “Designing of on line cyber attacks detection system using rough set theory and Q-learning algorithm”, Neurocomputing 111 (2013) 161–168.
[55] Quinlan, J.R., 1993. C4.5: Programs for Machine Learning. Morgan Kauffman.
[56] Resendez,PMartinezandJAbraham,“AIntrodution to Digital Forensics,” June 2014, https://www.researchgate.net/publication/228864187_An_Introduction_to_Digital_Forensics