Abstract

Artificial intelligence is a technology to make the machines human compatible. Various techniques like- heuristic search (Generate and test, Hill climbing, BFS, DFS, Problem reduction, constraint satisfaction, means-ends analysis etc. ), game playing, understanding, planning, NLP, Learning, commonsense, predictions and actions, and expert systems are there to make the system intelligent. This paper primarily focuses on the problem of malicious objects in the cyber space and discusses the usage of different AI techniques to overcome the mentioned problem. Every day the information stored in the computer and the information in transit faces threats due to malicious objects which further leads to a big loss. This paper discusses the possibilities to incorporate the AI techniques to analyze the data and finding and restricting the malicious objects. To make a proactive cyber defense system how the system log can be explored to find the malicious object and how the AI techniques like heuristic search can help in this process is discussed. This paper also discusses about the uncertainty of attacks and gives some views to implement AI techniques such as probability and Bayes' theorem, certainty factors and rule based system, Bayesian networks, fuzzy logic etc.

References

• Dinesh Kumar Saini "Sense the Future" Campus Volume 1- Issue 11, Page No14-17, February 2011.
• Antonatos S. , Akritidis P. , Markatos E. P. , Anagnostakis K. G. Defending against hit-list worms using network address space randomization. Proceedings of the 2005 ACM workshop on Rapid malcode. ACM Press New York NY, USA. pp. 30-40; 2005.
• Dinesh Kumar Saini "A Mathematical Model for the Effect of Malicious Object on Computer Network Immune System" Applied Mathematical Modeling, 35(2011) Page No. 3777-3787 USA, doi:10. 1016/. 2011. 02. 025.
• Bimal Kumar Mishra and Dinesh Kumar Saini "Mathematical Models on Computer viruses" Elsevier International Journal of Applied Mathematics and Computation, 187(2), 929-936. Volume 187, Issue 2, 15 April 2007, Pages 929-936. USA
• Bimal Kumar Mishra and Dinesh Kumar Saini "SEIRS epidemic model of transmission of malicious objects in computer network" Elsevier International Journal of Applied Mathematics and Computation, Volume 188, Issue 2, 15 May 2007, Pages 1476-1482. USA
• Gorodetsky V. , Karsaev O. , Samoilov V. Multi-agent and Data Mining Technologies for Situation Assessment in Security-related Applications. Monitoring, Security, and Rescue Techniques in Multi-agent Systems, Series of books, Advances in Soft Computing, Springer, pp. 411-422, 2005.
• Gaines B. R. , Fuzzy reasoning and logics of uncertainty. Proceedings of the sixth international symposium on Multiple-valued logic. IEEE Computer Society Press Los Alamitos, CA, USA. pp. 179-188, 1976.
• Dinesh Kumar Saini and Hemraj Saini "VAIN: A Stochastic Model for Dynamics of Malicious Objects", the ICFAI Journal of Systems Management, Vol. 6, No1, pp. 14- 28, February 2008. INDIA
• Hemraj Saini and Dinesh Kumar Saini "Malicious Object dynamics in the presence of Anti Malicious Software" European Journal of Scientific Research ISSN 1450-216X Vol. 18 No. 3 (2007), pp. 491-499 © Euro Journals Publishing, Inc. 2007 http://www. eurojournals. com/ejsr. htm EUROPE
• Jan-Erik Lane, The logic of means-end analysis , Quality and Quantity Springer Verilog, Volume 20, Number 4, Netherland, pp. 339-356, 1986.
• Kienzle D. M. , Elder M. C. Recent worms: a survey and trends. Proceedings of the 2003 ACM workshop on Rapid malcode. ACM Press New York, NY, USA. pp. 1-10; 2003.
• Sayadjari O. S. Cyber Defense: art to science. Communication of the ACM. 2004, Volume-47, Issue-3, ACM Press New York, NY, USA, pp. 52-57, 2004.
• Dinesh Kumar Saini and Hemraj Saini "Proactive Cyber Defense and Reconfigurable Framework for Cyber Security" International Review on computer and Software (IRCOS) Vol. 2. No. 2. March 2007, Pages 89-98. ITALY
• Rich E. , Knight K. Artificial Intelligence. Second Edition, Chapter-12, pp- 307-326, TMH: New York, 1991.
• Regina Barzilayy, Daryl McCullough, Owen Rambow,Jonathan DeCristofaroz, Tanya Korelsky, Benoit Lavoie, A New Approach to Expert System Explanations, [A data base from Internet]. Available at:http://www. cogentex. com/papers/explanation-iwnlg98. pdf
• Dinesh Kumar Saini and Nirmal Gupta "Fault Detection Effectiveness in GUI Components of Java Environment through Smoke Test", Journal of Information Technology, ISSN 0973-2896 Vol. 3, issue3, 7-17 September 2007.
• Dinesh Kumar Saini and Nirmal Gupta "Class Level Test Case Generation in Object Oriented Software Testing, International Journal of Information Technology and Web Engineering, (IJITWE) Vol. 3, Issue 2, pp. 19-26 pages, march 2008. USA
• Nordlander T. E. AI Surveying: Artificial Intelligence in Business. A thesis from De Montfort University, 2001. Available at: http://www. csd. abdn. ac. uk/~tnordlan/Publications/Artificial_Intelligence
• Dinesh Kumar Saini, Lingaraj A. Hadimani and Nirmal Gupta "Software Testing Approach for Detection and Correction of Design Defects in Object Oriented Software" Journal of Computing, Volume 3, Issue 4, April 2011, ISSN 2151-9617, Page No. 44-50.
• Jabbar Yousif and Dinesh Kumar Saini "Hindi Part-of-Speech Tagger Based Neural Networks" Journal of Computing, Volume 3, Issue 2, March, 2011, ISSN 2151-9617, Page No. 59-66.
• Dinesh Kumar Saini and Bimal Kumar Mishra "Design Patterns and their effect on Software Quality" Vol. 5, No. 1, January 2007, Page356-365 ACCST Research Journal, INDIA
• Hemraj Saini, Dinesh Kumar Saini, Nirmal Gupta, "Cyber Defense Architecture in Campus Wide Network System" International Journal of Theoretical and Applied Information Technology (JATIT)-(E-ISSN 1817-3195, ISSN 1992-8645), April 2008. Europe.
• Dinesh Kumar Saini "Testing Polymorphism in Object Oriented Systems for improving software Quality" ACM SIGSOFT Volume 34 Number 2 March 2009, ISSN: 0163-5948, USA
• Lakshmi Sunil Prakash, Dinesh Kumar Saini and Kutti N. S. "Integrating EduLearn Learning Content Management System (LCMS) with Cooperating Learning Object Repositories (LORs) in a Peer to Peer (P2P) architectural Framework" ACM SIGSOFT Volume 34 Number 3 May 2009, ISSN: 0163-5948, USA.
• J Lafferty, A McCallum "Conditional random fields: Probabilistic models for segmenting and labeling sequence data" Proceedings of the 18th International Conference on Machine Learning 2001 (ICML 2001), pages 282-289.
• Dinesh Kumar Saini, Jabar H. Yousif, and Wail M. Omar "Enhanced Inquiry Method for Malicious Object Identification" ACM SIGSOFT Volume 34 Number 3 May 2009, ISSN: 0163-5948, USA.
• H Saini, D. K. Saini and N. Gupta "E-Business System Development: Review on Methods, Design Factors, Techniques and Tools with an Extensive Case Study for Secure Online Retail Selling Industry" Journal of science and Technology (ISSN 0974-6846), Vol. 2. No. 5, May 2009, India.
• J Zhu, Z Nie, JR Wen, B Zhang Proceedings of the 22nd 2d conditional random fields for web information extraction", extracted from microsoft. com, 2005dl. acm. org
• Wail M. Omar, Dinesh K. Saini and Mustafa Hassan "Credibility Of Digital Content in a Healthcare Collaborative Community" Software Tools and Algorithms for Biological Systems in book series "Advances in Experimental Medicine and Biology, AEMB" Springer, Volume 696, Part 8, Page No. 717-724, DOI: 10. 1007/978-1-4419-7046-6_73,