Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
9-2011
Abstract
Due to the erratic nature, the value of a function argument in one normal program execution could become illegal in another normal execution context. Attacks utilizing such erratic arguments are able to evade detections as fine-grained context information is unavailable in many existing detection schemes. In order to obtain such fine-grained context information, a precise model on the internal program states has to be built, which is impractical especially monitoring a closed source program alone. In this paper, we propose an intrusion detection scheme which builds on two diverse programs providing semantically-close functionality. Our model learns underlying semantic correlation of the argument values in these programs, and consequently gains more accurate context information compared to existing schemes. Through experiments, we show that such context information is effective in detecting attacks which manipulate erratic arguments with comparable false positive rates.
Keywords
Intrusion detection, system call argument, diversity
Discipline
Information Security
Research Areas
Cybersecurity
Publication
Security and Privacy in Communication Networks: 7th International ICST Conference, SecureComm 2011, London, UK, September 7-9, 2011, Revised Selected Papers
Volume
96
First Page
172
Last Page
189
ISBN
9783642319099
Identifier
10.1007/978-3-642-31909-9_10
Publisher
Springer Verlag
City or Country
Heidelberg
Citation
HAN, Jin; YAN, Qiang; DENG, Robert H.; and GAO, Debin.
On Detection of Erratic Arguments. (2011). Security and Privacy in Communication Networks: 7th International ICST Conference, SecureComm 2011, London, UK, September 7-9, 2011, Revised Selected Papers. 96, 172-189.
Available at: https://ink.library.smu.edu.sg/sis_research/1429
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1007/978-3-642-31909-9_10