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OFFDTAN: A New Approach of Offline Dynamic Taint Analysis for Binaries
Joint Authors
Wang, Xiajing
Ma, Rui
Dou, Bowen
Jian, Zefeng
Chen, Hongzhou
Source
Security and Communication Networks
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-30
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
Dynamic taint analysis is a powerful technique for tracking the flow of sensitive information.
Different approaches have been proposed to accelerate this process in an online or offline manner.
Unfortunately, most of these approaches still have performance bottlenecks and thus reduce analytical efficiency.
To address this limitation, we present OFFDTAN, a new approach of offline dynamic taint analysis for binaries.
OFFDTAN can be described in terms of four stages: dynamic information acquisition, vulnerability modeling, offline analysis, and backtrace analysis.
It first records program runtime information and models the stack buffer overflow vulnerabilities and controlled jump vulnerabilities.
Then it performs offline analysis and backtrace analysis to locate vulnerabilities.
We implement OFFDTAN on the basis of QEMU virtual machine and apply it to off-the-shelf applications.
In order to illustrate how our approach works, we first employ a case study.
Furthermore, six applications have been verified so as to evaluate our approach.
Experimental results demonstrate that our approach is correct and effective.
Compared with other offline analysis tools, OFFDTAN has much lower application runtime overhead.
American Psychological Association (APA)
Wang, Xiajing& Ma, Rui& Dou, Bowen& Jian, Zefeng& Chen, Hongzhou. 2018. OFFDTAN: A New Approach of Offline Dynamic Taint Analysis for Binaries. Security and Communication Networks،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1214378
Modern Language Association (MLA)
Wang, Xiajing…[et al.]. OFFDTAN: A New Approach of Offline Dynamic Taint Analysis for Binaries. Security and Communication Networks No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1214378
American Medical Association (AMA)
Wang, Xiajing& Ma, Rui& Dou, Bowen& Jian, Zefeng& Chen, Hongzhou. OFFDTAN: A New Approach of Offline Dynamic Taint Analysis for Binaries. Security and Communication Networks. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1214378
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214378