Artificial Intelligence Review

, Volume 42, Issue 4, pp 1029–1044

Evaluation of artificial intelligent techniques to secure information in enterprises


DOI: 10.1007/s10462-012-9372-9

Cite this article as:
Rehman, A. & Saba, T. Artif Intell Rev (2014) 42: 1029. doi:10.1007/s10462-012-9372-9


Information security paradigm is under a constant threat in enterprises particularly. The extension of World Wide Web and rapid expansion in size and types of documents involved in enterprises has generated many challenges. Extensive research has been conducted to determine the effective solutions to detect and respond but still the space is felt for improvement. Factors that hinder the development of an accurate detection and response techniques have shown links to the amount of data processing involved, number of protocols and application running across and variation in users’ requirements and responses. This paper is aimed at discussing the current issue in artificial intelligent (A.I.) techniques that could help in developing a better threat detection algorithm to secure information in enterprises. It is also investigated that the current information security techniques in enterprises have shown an inclination towards A.I. Conventional techniques for detection and response mostly requires human efforts to extract characteristics of malicious intent, investigate and analyze abnormal behaviors and later encode the derived results into the detection algorithm. Instead, A.I. can provide a direct solution to these requirements with a minimal human input. We have made an effort in this paper to discuss the current issues in information security and describe the benefits of artificially trained techniques in security process. We have also carried out survey of current A.I. techniques for IDS. Limitations of the techniques are discussed to identify the factors to be taken into account for efficient performance. Lastly, we have provided a possible research direction in this domain.


A.I. techniques Information security Network intrusion detection systems (NIDS) Threats Performance 

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Faculty of Computer Science and Information SystemsUniversiti Teknologi Malaysia, SkudaiJohorMalaysia
  2. 2.College of Engineering and Computer SciencesSalman Abdul Aziz UniversityAlkharjKSA

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