Deakin University
Browse

File(s) under permanent embargo

Simseer and Bugwise - web services for binary-level software similarity and defect detection

Version 2 2024-06-03, 11:47
Version 1 2014-11-11, 17:11
conference contribution
posted on 2024-06-03, 11:47 authored by S Cesare, Y Xiang
Simseer and Bugwise are online web services that perform binary program analysis: 1) Simseer identifies similarity between submitted executables based on similarity in the control flow of each binary. A software similarity service provides benefit in identifying malware variants and families, discovering software theft, and revealing plagiarism of software programs. Simseer additionally performs code packing detection and automated unpacking of hidden code using applicationlevel emulation. Finally, Simseer uses the similarity information from a sample set to identify program relationships and families through visualization of an evolutionary tree. 2) Bugwise is a service that identifies software bugs and defects. To achieve this end, it performs decompilation and data flow analysis. Bugwise can identify a subset of use-after-free bugs and has already found defects in Debian Linux. Bugwise and Simseer are both built on Malwise, a platform of binary analysis. © 2013 Australian Computer Society, Inc.

History

Volume

140

Pagination

21-30

Location

Adelaide, South Australia

Start date

2013-01-29

End date

2013-02-01

ISSN

1445-1336

ISBN-13

9781921770258

Language

eng

Publication classification

E Conference publication, E1.1 Full written paper - refereed

Copyright notice

2013, Australian Computer Society

Editor/Contributor(s)

Javadi B, Kumar Garg S

Title of proceedings

AusPDC 2013 : Proceedings of the 11th Australasian Symposium on Parallel and Distributed Computing

Event

Parallel and Distributed Computing. Australasian Symposium (11th : 2013 : Adelaide, South Australia)

Publisher

Australian Computer Society

Place of publication

Sydney, N.S.W.

Series

Conferences in Research and Practice in Information Technology Series