Artificial Intelligence in Cyber Security: A Survey
Main Article Content
Abstract
Cyber-attacks have outstripped the sector's financial and human capabilities for analyzing and combatting new cyber threats. With the growth of digital presence comes an increase in the amount of personal and financial information that must be safeguarded. Indeed, cyber-attacks have the potential to completely ruin an organization's brand. The goal of this research is to determine how artificial intelligence may be used to improve cyber security. In recent years, advances in artificial intelligence have overtaken human competency in activities such as data analytics. The research team conducted a systematic review of the current literature, using data from Google Scholar, Science Direct, Research Gates, and academic journals and publications. While using artificial intelligence to guard against cyber threats has significant limitations, the study concluded that the benefits outweigh the drawbacks. According to one expert, the speed and efficiency necessary to run AI systems will almost certainly result in an increase in customer and company cyber security. Traditional scanning engines are progressively taking the place of AI engines in cyber security
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
IJCERT Policy:
The published work presented in this paper is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This means that the content of this paper can be shared, copied, and redistributed in any medium or format, as long as the original author is properly attributed. Additionally, any derivative works based on this paper must also be licensed under the same terms. This licensing agreement allows for broad dissemination and use of the work while maintaining the author's rights and recognition.
By submitting this paper to IJCERT, the author(s) agree to these licensing terms and confirm that the work is original and does not infringe on any third-party copyright or intellectual property rights.
References
S. Bhutada and P. Bhutada, Application of Artificial Intelligence in Cyber Security: in IJERCSE, 2018, 5(4): 214 219
P.V. Alberto, lecture, Topic: Application of Artificial Intelligence (AI) to Network Security?, ITEC 625, University of Maryland, University College, Maryland, Mar. 2018.
Avira, The Application of AI to Cybersecurity An Avira White Paper, Germany, Avira Operation, 2017.
S. A Panimalar, U.G. Pai and K.S. Khan, ?AI Techniques for Cyber Security?, International Research Journal of Engineering and Technology, vol. 5, 3, pp. 122 124, Mar. 2018. Available: https://www.irjet.net [assessed May. 29, 2020]
T.S. Tuang. Diep.Q. B, and Zelinka. I, Artificial Intelligence in the Cyber Domain: Offense and Defense: Symmetry, 2020, 12,410 available: www.mdp.com/journal/symmetry on [assessed Apr. 20, 2020]
E. Kanal, Machine Learning in Cybersecurity: Carnegie Mellon University Software Engineering Institute, available onhttp://insights.sei.cnu.edu./sei_blog/2017/06/machine_learning_in_cybersecurity.html
D. Selma, C. Huseyin and A. Mustafa, Application of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review, International Journal of Artificial Intelligence &Applications, vol. 6, issue 1, pp. 21 39, January 2015.
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 10, OCTOBER 2020 ISSN 2277-8616
T. Enn, ?Artificial Intelligence in Cyber Defense?, in Proceedings of 3rd International Conference on Cyber Conflicts [ICCC], 7--10 June, 2011 Tallin Estonia.
P. Dennis, A. Stuart, ?Global Challenges: Twelve risks that threaten human civilization, Global Challenges Foundation?: 2015,Available: http://globalchallenges.org /wp--content/ uploads/12--Risks--with--infinite--impact.pdf [accessed Jun. 3, 2020]
R. Stuart, D. Daniel, T. Max, ??Research Priorities for Robust and Beneficial Artificial Intelligence‘‘, AI Magazine, vol. 36, issue 4, pp. 105--114, Winter 2015
National Science & Technology Council, ?Artificial Intelligence and Cybersecurity: Opportunities and Challenges? Net. & Info.Tech R&D Sub--comtt and the ML & AI Sub--comtt, 2020.
A. M. Shamiulla, Role of Artificial Intelligence in Cyber Security, International Journal of Innovative Technology and Exploring Engineering, vol. 9 issue 1 pp. 4628--4630, November 2019
P. Pranav, ?Artificial Intelligence in cyber security?, International Journal of Research in Computer Applications & Robotics, vol 4, 1, pp.1--5, May 2016
J. Kivimaa, A. Ojamaa, E. Tyugu. Graded Security Expert System. Lecture Notes in Computer Science, v. 5508. Springer, 2009, 279--286.
B. Christain, D.A. Elizondo and T. Watson, ?Application of artificial neural networks and related techniques to intrusion detection?, World Congress on Computation Intelligence, pp 949--954, 2010
E. Tyugu, ?Artificial Intelligence in Cyber Defense?, International conference on Cyber Conflict, vol. 3, pp. 95--105, Tallinn, Estonia, Jan. 2011
W. Nadine and K. Hadas, ?Artificial Intelligence in Cybersecurity?, Cyber, Intelligence, and Security, vol. 1, 1, pp. 103--119, Jan. 2017
S. Dima, M. Robert, B. Zvi, S. Shahar and E. Yuval, ?Using Artificial Neural Network to Detect Unknown Computer Worms?, Neural Computing and Applications, vol.18, 7, pp. 663--674, Oct. 2009
E. H. Geoffrey, O. Simon and T. Yee--Whye, ?A Fast Learning Algorithm for Deep Belief Nets?, Neural Computation, vol. 18, no. 7, pp. 1527--1554, 2006
V. Thomson, ?Cyber Attacks Could be Predicted with Artificial Intelligence?, iTechPost,www.itechpost.com/articles/1734 7/cyber-attacks--predicted--artificial--intelligen ce--help.htm, Apr. 21, 2016 [Jun. 2, 2020]
S. Franklin and A. Graesser, ?Is It an Agent, or Just a Program? A Taxonomy for Autonomous Agents?, Third International Workshop on Agent Theories, Architectures, and Languages, no. 3, pp. 21--35, 1997
Y. Xia and L. Junshan, ?A Security Architecture Based on Immune Agents for MANET?, International Conference on Wireless Communication and Sensor Computing, no. , pp. 1--5, 2010
M. F. AbRazak, etal, ?Bio--inspired for features optimization and malware detection.Arabian Journal of Science and Engineering, no. 43, pp. 6963––6979. 2018
A. Fatima, etal, ?Android Malware Detection Using Genetic Algorithm based Optimized Feature Selection and Machine Learning?, In Proceedings of the 42nd International Conference on Telecommunications and Signal Processing (TSP), Budapest, Hungary, 1––3 July 2019; pp. 220––223.
R.A.R Ashfaq, etal, ?Fuzziness based semi--supervised learning approach for intrusion detection system?. Inf. Sci. 2017, 378, 484––497.
L. Lazic, ?Benefits from AI in Cyber Security?, The 11th international Conference on Business Information Security, 18th Oct. 2019, Belgrade, Serbia, pp. 1—9