A. Ojugoa

Work place: Department of Mathematics/Computer Science, Federal University of Petroleum Resources Effurun, Delta State, Nigeria

E-mail: ojugo.arnold@fupre.edu.ng

Website:

Research Interests: Ubiquitous Computing, Computer Vision, Computer systems and computational processes

Biography

Arnold Adimabua Ojugo received BSc in Computer Science from the Imo State University Owerri in 2000, MSc in Computer Science from the Nnamdi Azikiwe University Awka in 2005, and PhD in Computer Science from Ebonyi State University Abakiliki in 2013. He currently lectures with the Department of Mathematics/Computer Science of the Federal University of Petroleum Resources Effurun, Delta State, Nigeria. His research interests: Intelligent Systems and Control, High Performance and Dynamic Computing, Machine-Learning, Computer Vision, Ubiquitous Computing, Data Security and Forensics. He is an Editor with the Progress for Intelligent Computation and Application, Advancement for Scientific and Engineering Research and SciencePG (ACIS, AJNC, NET and WCMC Journals). He is a member of: The Nigerian Computer Society, Computer Professionals of Nigeria and International Association of Engineers (IAENG).

Author Articles
Signature-Based Malware Detection Using Approximate Boyer Moore String Matching Algorithm

By A. Ojugoa A. O. Eboka

DOI: https://doi.org/10.5815/ijmsc.2019.03.05, Pub. Date: 8 Jul. 2019

Adversaries to any system restlessly continues to sought effective, non-detectable means to aid them successful penetrate secure systems, either for fun or commercial gains. They achieve these feats easily through the use of malware, which keeps on the rise, an ever-growing and corresponding overpopulated malware zoo. As such, information technology industry will continue to encounter via these escapades, both monetary and prestigious losses. Malware by design aims to alter the behaviour of its host by self-replicating its genome or codes unto it. They are quite fascinating in that on execution, some malware change their own structure so that its copies have same functionality but differ in signature and syntax from the original or parent virus. This makes signature detection quite unreliable. Study investigates detection of metamorphic malware attacks using the Boyer Moore algorithm for string-based signature detection scheme.

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