Hidden markov model for masquerade detection based on sequence alignment

Wei Qiu; Andy Wai Hoong Khong; Wee Peng Tay

doi:10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00055

Hidden markov model for masquerade detection based on sequence alignment

Wei Qiu, Andy Wai Hoong Khong, Wee Peng Tay

Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

A masquerade attack, in which an attacker impersonates a legitimate user to utilize the user's privileges, can be triggered either by someone within the organization or by an outsider. We propose the sequence alignment based hidden Markov model (SA-HMM) approach, where we incorporate the benefits of both the sequence alignment and continuous hidden Markov model (HMM). The sequence alignment module for the proposed algorithm allows the algorithm to tolerate variations in user activity sequence. The HMM module takes the positional information between the observations of users into account. The proposed approach achieves a high hit ratio of 94.1% outperforming existing masquerade detection approaches.

Original language	English
Title of host publication	Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	286-291
Number of pages	6
ISBN (Electronic)	9781538675182
DOIs	https://doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00055
Publication status	Published - Oct 26 2018
Externally published	Yes
Event	16th IEEE International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018 - Athens, Greece Duration: Aug 12 2018 → Aug 15 2018

Publication series

Name	Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018

Conference

Conference	16th IEEE International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018
Country/Territory	Greece
City	Athens
Period	8/12/18 → 8/15/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

ASJC Scopus Subject Areas

Computer Networks and Communications
Information Systems
Artificial Intelligence
Information Systems and Management
Safety, Risk, Reliability and Quality
Control and Optimization

Keywords

Hidden Markov models
Masquerade detection
Sequence ailgnment

Access to Document

10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00055

Cite this

Qiu, W., Khong, A. W. H., & Tay, W. P. (2018). Hidden markov model for masquerade detection based on sequence alignment. In Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018 (pp. 286-291). Article 8511898 (Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00055

Qiu, Wei ; Khong, Andy Wai Hoong ; Tay, Wee Peng. / Hidden markov model for masquerade detection based on sequence alignment. Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 286-291 (Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018).

@inproceedings{853e21f3417d4ca6a0e8e27442d45fc9,

title = "Hidden markov model for masquerade detection based on sequence alignment",

abstract = "A masquerade attack, in which an attacker impersonates a legitimate user to utilize the user's privileges, can be triggered either by someone within the organization or by an outsider. We propose the sequence alignment based hidden Markov model (SA-HMM) approach, where we incorporate the benefits of both the sequence alignment and continuous hidden Markov model (HMM). The sequence alignment module for the proposed algorithm allows the algorithm to tolerate variations in user activity sequence. The HMM module takes the positional information between the observations of users into account. The proposed approach achieves a high hit ratio of 94.1% outperforming existing masquerade detection approaches.",

keywords = "Hidden Markov models, Masquerade detection, Sequence ailgnment",

author = "Wei Qiu and Khong, {Andy Wai Hoong} and Tay, {Wee Peng}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 16th IEEE International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018 ; Conference date: 12-08-2018 Through 15-08-2018",

year = "2018",

month = oct,

day = "26",

doi = "10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00055",

language = "English",

series = "Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "286--291",

booktitle = "Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018",

address = "United States",

}

Qiu, W, Khong, AWH & Tay, WP 2018, Hidden markov model for masquerade detection based on sequence alignment. in Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018., 8511898, Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018, Institute of Electrical and Electronics Engineers Inc., pp. 286-291, 16th IEEE International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018, Athens, Greece, 8/12/18. https://doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00055

Hidden markov model for masquerade detection based on sequence alignment. / Qiu, Wei; Khong, Andy Wai Hoong; Tay, Wee Peng.
Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 286-291 8511898 (Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Hidden markov model for masquerade detection based on sequence alignment

AU - Qiu, Wei

AU - Khong, Andy Wai Hoong

AU - Tay, Wee Peng

PY - 2018/10/26

Y1 - 2018/10/26

N2 - A masquerade attack, in which an attacker impersonates a legitimate user to utilize the user's privileges, can be triggered either by someone within the organization or by an outsider. We propose the sequence alignment based hidden Markov model (SA-HMM) approach, where we incorporate the benefits of both the sequence alignment and continuous hidden Markov model (HMM). The sequence alignment module for the proposed algorithm allows the algorithm to tolerate variations in user activity sequence. The HMM module takes the positional information between the observations of users into account. The proposed approach achieves a high hit ratio of 94.1% outperforming existing masquerade detection approaches.

AB - A masquerade attack, in which an attacker impersonates a legitimate user to utilize the user's privileges, can be triggered either by someone within the organization or by an outsider. We propose the sequence alignment based hidden Markov model (SA-HMM) approach, where we incorporate the benefits of both the sequence alignment and continuous hidden Markov model (HMM). The sequence alignment module for the proposed algorithm allows the algorithm to tolerate variations in user activity sequence. The HMM module takes the positional information between the observations of users into account. The proposed approach achieves a high hit ratio of 94.1% outperforming existing masquerade detection approaches.

KW - Hidden Markov models

KW - Masquerade detection

KW - Sequence ailgnment

UR - http://www.scopus.com/inward/record.url?scp=85056859106&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056859106&partnerID=8YFLogxK

U2 - 10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00055

DO - 10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00055

M3 - Conference contribution

AN - SCOPUS:85056859106

T3 - Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018

SP - 286

EP - 291

BT - Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 16th IEEE International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018

Y2 - 12 August 2018 through 15 August 2018

ER -

Qiu W, Khong AWH, Tay WP. Hidden markov model for masquerade detection based on sequence alignment. In Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 286-291. 8511898. (Proceedings - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, IEEE 16th International Conference on Pervasive Intelligence and Computing, IEEE 4th International Conference on Big Data Intelligence and Computing and IEEE 3rd Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2018). doi: 10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00055

Hidden markov model for masquerade detection based on sequence alignment

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus Subject Areas

Keywords

Access to Document

Other files and links

Fingerprint

Cite this