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ACMSE
2009
ACM

Applying randomized projection to aid prediction algorithms in detecting high-dimensional rogue applications

10 years 1 months ago
Applying randomized projection to aid prediction algorithms in detecting high-dimensional rogue applications
This paper describes a research effort to improve the use of the cosine similarity information retrieval technique to detect unknown, known or variances of known rogue software by applying the feature extraction technique of randomized projection. Document similarity techniques, such as cosine similarity, have been used with great success in several document retrieval applications. By following a standard information retrieval methodology, software, in machine readable format, can be regarded as documents in the corpus. These “documents” may or may not have a known rogue functionality. The query is software, again in machine readable format, which contains a certain type of rogue software. This methodology provides an ability to search the corpus with a query and retrieve/identify potentially rogue software as well as other instances of the same type of vulnerability. This retrieval is based on the similarity of the query to a given document in the corpus. To overcome what is know...
Travis Atkison
Added 27 May 2010
Updated 27 May 2010
Type Conference
Year 2009
Where ACMSE
Authors Travis Atkison
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