Work place: Institute of Information Technology of Azerbaijan National Academy of Sciences, 9, F.Agayev Street, Baku, Azerbaijan
E-mail: sbunyadova@gmail.com
Website:
Research Interests: Computer systems and computational processes, Data Mining, Data Structures and Algorithms
Biography
Saadat Nazirova was born on June 03, 1979 in Azerbaijan. She received the B.Sc. and M.Sc. degrees from Applied Mathematics and Cybernetics department of Azerbaijan State University, in 2000 and 2002, respectively.
From 2006 she is PHD student at the Institute of Information Technology of Azerbaijan National Academy of Sciences. She has published over 10 refereed journal and conference papers in the areas of email filtering systems. Her representative published articles lists as follow: Classification of Textual E-mail Spam Using Data Mining Techniques (USA: Applied Computational Intelligence and Soft Computing, 2011), Two Approaches on Implementation of CBR and CRM Technologies to the Spam Filtering Problem (USA: Journal of Information Security, 2012), Survey on Spam filtering techniques (USA: Communications and Networks, 2011), etc. Moreover, she is an expert in implementation of ISO 27000, 20000 standards and development of Information Security Management Systems. Her research interests include text classification, data mining, CBR and CRM technologies. Especially, her researches about the methods of filtering electronic junk mail.
DOI: https://doi.org/10.5815/ijisa.2012.10.03, Pub. Date: 8 Sep. 2012
In this paper the development of anti-spam software detecting information attacks is offered. For this purpose it is considered spam filtration system with the multilayered, multivalent architecture, coordinating all ISP’s in the country. All users and ISPs of this system involved in spam filtration process. After spam filtering process, saved spam templates are analyzed and classified. This parameterizing of spam templates give possibility to define the thematic dependence from geographical. For example, what subjects prevail in spam messages sent from the certain countries? Analyzing origins of spam templates from spam-base, it is possible to define and solve the organized social networks of spammers. Thus, the offered system will be capable to reveal purposeful information attacks if those occur.
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