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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Naidu, V. Narayanan, A. |
| Copyright Year | 2014 |
| Description | Author affiliation: Sch. of Comput. & Math. Sci., Auckland Univ. of Technol., Auckland, New Zealand (Naidu, V.; Narayanan, A.) |
| Abstract | Initial work on structural analysis of malware using the nature-inspired technique of projecting malware signatures into the amino acid/protein domain was promising in a number of ways, including the demonstration of potential links with real-world pathogen proteins. That initial work was necessarily speculative and limited by a number of experimental factors. The aim of the research reported here is to address some of these limitations and to repeat, with malware code and signatures that can be assured as genuine, the experiments previously reported but with enhancements and improvements. Intriguingly, the outcome is the same: for some reason that is not yet known, matching artificial malware code consensuses after multiple alignment against protein databases returns a high proportion of naturally occurring viral proteins. |
| Starting Page | 605 |
| Ending Page | 610 |
| File Size | 311912 |
| Page Count | 6 |
| File Format | |
| ISSN | 21579563 |
| e-ISBN | 9781479951512 |
| DOI | 10.1109/ICNC.2014.6975904 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Proteins automatic signature generation Blaster worm Amino acids Malware Matrices malware structural analysis malware modelling Grippers Biological information theory Payloads |
| Content Type | Text |
| Resource Type | Article |
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