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B. K. Alese

Work place: Department of Computer Science, Federal University of Technology, Akure, Ondo State, Nigeria

E-mail: bkalese@futa.edu.ng

Website:

Research Interests: Intrusion Detection System, Detection Theory

Biography

ALESE, Boniface Kayode Place & Date of Birth: Ilawe – Ekiti, Nigeria. 21 December, 1969

 

Educational Background:

  • D. in Computer Science, Federal University of Technology, Akure, Ondo State., Nigeria - 2004
  • Tech in Computer Science,Federal University of Technology, Akure, Ondo State, Nigeria-2000
  • Tech in Industrial Mathematics, Federal University of Technology, Akure, Ondo State, Nigeria-1997
  • NCE in Mathematics/Physics, Ondo State College of Education, Ikere-Ekiti, Ekiti State, Nigeria - 1990

 

Research/Area of Interest: CyberSecurity, Intrusion Detection.

 

Working Experience

Professor, Department of Computer Science, Federal University of Technology, Akure, Nigerai

Membership of Professional Bodies

  • Member, Nigeria Computer Society, MNCS (Membership Number 05310)
  • Member, Institute of Electrical and Electronics Engineering (Computer Society) New York, MIEEE (Membership Number 80661453)
  • Member, Association for Computing Machinery; New York, MACM (Membership Number 0273409)
  • Member, International Association of Engineers (Membership Number 135763)
  • Member, Infonomics Society, United Kingdom
  • Computer Professional of Nigeria (CPN) Registered (Reg No 003686/2012)
  • Member, Cyber Security Experts Association of Nigeria
  • Member, Information Systems Security Association, Virginia, United States (Membership Number 38991819)
  • Member, Information Systems Audit and Control Association, United States of America (Membership Number,964629)

Author Articles
Pre-Processing of University Webserver Log Files for Intrusion Detection

By Bukola A. Onyekwelu B. K. Alese A. O. Adetunmbi

DOI: https://doi.org/10.5815/ijcnis.2017.01.03, Pub. Date: 8 Jan. 2017

Web Server log files can reveal lots of interesting patterns when analyzed. The results obtained can be used in various applications, one of which is detecting intrusions on the web. For good quality of data and usable results, there is the need for data preprocessing. In this research, different stages of data preprocessing were carried out on web server log files obtained over a period of five months. The stages are Data Conversion, Session Identification, Data Cleaning and Data Discretization. Data Discretization was carried out in two phases to take care of data with continuous attributes. Some comparisons were carried out on the discretized data. The paper shows that with each preprocessing step, the data becomes clearer and more usable. At the final stage, the data presented offers a wide range of opportunities for further research. Therefore, preprocessing web server log files provides a standard processing platform for adequate research using web server logs. This method is also useful in monitoring and studying web usage pattern in a particular domain. Though the research covers webserver log obtained from a University domain, and thus, reveals the pattern of web access within a university environment, it can also be applied in e-commerce and any other terrain.

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