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HOMOLIAK, I. ŠULÁK, L. HANÁČEK, P.
Original Title
Features for Behavioral Anomaly Detection of Connectionless Network Buffer Overflow Attacks
Type
conference paper
Language
English
Original Abstract
Buffer overflow (BO) attacks are one of the most dangerous threads in the area of network security. Methods for detection of BO attacks basically use two approaches: signature matching against packets' payload versus analysis of packets' headers with the behavioral analysis of the connection's flow. The second approach is intended for detection of BO attacks regardless of packets' content which can be ciphered. In this paper, we propose a technique based on Network Behavioral Anomaly Detection (NBAD) aimed at connectionless network traffic. A similar approach has already been used in related works, but focused on connection-oriented traffic. All principles of connection-oriented NBAD cannot be applied in connectionless anomaly detection. There is designed a set of features describing the behavior of connectionless BO attacks and the tool implemented for their offline extraction from network traffic dumps. Next, we describe experiments performed in the virtual network environment utilizing SIP and TFTP network services exploitation and further data mining experiments employing supervised machine learning (ML) and Naive Bayes classifier. The exploitation of services is performed using network traffic modifications with intention to simulate real network conditions. The experimental results show the proposed approach is capable of distinguishing BO attacks from regular network traffic with high precision and class recall.
Keywords
Buffer overflow, Connectionless traffic, SIP, TFTP, UDP vulnerabilities, NBAD, Naive Bayes
Authors
HOMOLIAK, I.; ŠULÁK, L.; HANÁČEK, P.
Released
30. 3. 2017
Publisher
Springer International Publishing
Location
Jeju Island
ISBN
978-3-319-56549-1
Book
Information Security Applications - 17th International Workshop, WISA 2016, Jeju Island, Korea, August 25-27, 2016, Revised Selected Papers
Edition
Lecture Notes in Computer Science
0302-9743
Periodical
Year of study
10144
Number
1
State
Federal Republic of Germany
Pages from
66
Pages to
78
Pages count
13
URL
https://link.springer.com/chapter/10.1007%2F978-3-319-56549-1_6
BibTex
@inproceedings{BUT134712, author="Ivan {Homoliak} and Ladislav {Šulák} and Petr {Hanáček}", title="Features for Behavioral Anomaly Detection of Connectionless Network Buffer Overflow Attacks", booktitle="Information Security Applications - 17th International Workshop, WISA 2016, Jeju Island, Korea, August 25-27, 2016, Revised Selected Papers", year="2017", series="Lecture Notes in Computer Science", journal="Lecture Notes in Computer Science", volume="10144", number="1", pages="66--78", publisher="Springer International Publishing", address="Jeju Island", doi="10.1007/978-3-319-56549-1\{_}6", isbn="978-3-319-56549-1", issn="0302-9743", url="https://link.springer.com/chapter/10.1007%2F978-3-319-56549-1_6" }
Documents
WISA-camera-ready.pdf