Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/109371
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Type: Conference paper
Title: Improving tool support for software reverse engineering in a security context
Author: Cleary, B.
Treude, C.
Filho, F.
Storey, M.
Salois, M.
Citation: Lecture Notes in Artificial Intelligence, 2013 / Schmorrow, D., Fidopiastis, C. (ed./s), vol.8027 LNAI, pp.113-122
Publisher: Springer
Issue Date: 2013
Series/Report no.: Lecture Notes in Computer Science
ISBN: 9783642394539
ISSN: 0302-9743
1611-3349
Conference Name: International Conference on Augmented Cognition (21 Jul 2013 - 26 Jul 2013 : Las Vegas, NV)
Editor: Schmorrow, D.
Fidopiastis, C.
Statement of
Responsibility: 
Brendan Cleary, Christoph Treude, Fernando Figueira Filho, Margaret-Anne Storey, and Martin Salois
Abstract: Illegal cyberspace activities are increasing rapidly and many software engineers are using reverse engineering methods to respond to attacks. The security-sensitive nature of these tasks, such as the understanding of malware or the decryption of encrypted content, brings unique challenges to reverse engineering: work has to be done offline, files can rarely be shared, time pressure is immense, and there is a lack of tool and process support for capturing and sharing the knowledge obtained while trying to understand assembly code. To help us gain an understanding of this reverse engineering work, we conducted an exploratory study at a government research and development organization to explore their work processes, tools, and artifacts [1]. We have been using these findings to improve visualization and collaboration features in assembly reverse engineering tools. In this talk, we will present a review of the findings from our study, and present prototypes we have developed to improve capturing and sharing knowledge while analyzing security concerns.
Keywords: Malware; reverse engineering; empirical study.
Description: LNCS, volume 8027
Rights: Springer-Verlag Berlin Heidelberg 2013
DOI: 10.1007/978-3-642-39454-6_12
Published version: http://dx.doi.org/10.1007/978-3-642-39454-6
Appears in Collections:Aurora harvest 3
Computer Science publications

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