Camouflage Worm Detection and Counter-Measures
Edward Danso Ansong1, J. B. Hayfron-Acquah2, Dominic Damoah3, Michael Asante4, Brighter Agyeman5
1Edward Danso Ansong, Department of Computer Science & Information Technology,Valley View University, Accra-Ghana.
2J. B. Hayfron-Acquah, Department of Computer Science, Kwame Nkrumah University of Science & Technology, Kumasi-Ghana.
3Dominic Damoah, Department of Computer Science & Information Technology, Valley View University, Accra-Ghana.
4Michael Asante, Department of Computer Science, Kwame Nkrumah University of Science & Technology, Kumasi-Ghana.
5Brighter Agyeman, Department of Computer Science & Information Technology, Valley View University, Accra-Ghana.
Manuscript received on August 01, 2014. | Revised Manuscript Received on August 15, 2014. | Manuscript published on August 20, 2014. | PP: 1-4 | Volume-2, Issue-9, August 2014. | Retrieval Number: C0627012314/2014©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This research focuses special attention on a new class of worms called Camouflaging worm (C-Worm). The key difference between C-Worm and traditional worms is that, it displays the ability to intelligently analyse and make changes to its scan traffic volume over time. This new class of active worms is an attack that spread itself on the internet by exploiting vulnerabilities on computer systems.
Keywords: C-Worm, Camouflaging, traditional, vulnerabilities.