000 02217nam  2200277za 4500
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008150723s2015    onc     ob   f000 0 eng d
040 |aCaOODSP|beng
041 |aeng|bfre
043 |an-cn---
0861 |aD68-2/27-2015E-PDF
1001 |aCharland, P.
24510|aSoftware fingerprinting for automated assembly code analysis |h[electronic resource] / |cP. Charland.
260 |a[Ottawa] : |bDefence Research and Development Canada, |c2015.
300 |avii, 28, [2] p. : |bfig., tables.
4901 |aScientific report ; |v2015-R027
500 |aMarch 2015.
504 |aIncludes bibliographical references (p. 23-26).
520 |aWith the revolution in information technology, the dependence of the Canadian Armed Forces (CAF) on their information systems continues to grow. While information systems-based assets confer a distinct advantage, they also make the CAF vulnerable if adversaries interfere with those. Unfortunately, the technology required to disrupt and damage an information system through malicious software (malware) is far less sophisticated and expensive than the amount of investment required to create the system. To understand and mitigate this threat, reverse engineering has to be performed to analyze malware. However, software reverse engineering is a manually intensive and time-consuming process. The learning curve to master it is quite steep and once mastered, the process is hindered when anti-reverse engineering techniques are used. This results in the very few available reverse engineers being quickly saturated. This Scientific Report describes new approaches to accelerate the reverse engineering process of malware. The goal is to reduce redundant analysis efforts by automating the identification of code fragments which reuse (i) previously analyzed assembly code or (ii) open source code publicly available.
69207|2gccst|aComputer security
7102 |aDefence R&D Canada.
830#0|aScientific report (Defence R&D Canada)|v2015-R027|w(CaOODSP)9.802305
85640|qPDF|s1.40 MB|uhttps://publications.gc.ca/collections/collection_2015/rddc-drdc/D68-2-27-2015-eng.pdf