Efficient signature generation for classifying cross-architecture IoT malware

Mohannad Alhanahnah; Qicheng Lin; Qiben Yan; Ning Zhang; Zhenxiang Chen

doi:10.1109/CNS.2018.8433203

Efficient signature generation for classifying cross-architecture IoT malware

Mohannad Alhanahnah, Qicheng Lin, Qiben Yan^*, Ning Zhang, Zhenxiang Chen

^*Corresponding author for this work

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

79 Citations (SciVal)

Original language	English
Title of host publication	2018 IEEE Conference on Communications and Network Security, CNS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781538645864
DOIs	https://doi.org/10.1109/CNS.2018.8433203
Publication status	Published (VoR) - 10 Aug 2018
Event	6th IEEE Conference on Communications and Network Security, CNS 2018 - Beijing, China Duration: 30 May 2018 → 1 Jun 2018

Publication series

Name	2018 IEEE Conference on Communications and Network Security, CNS 2018

Conference

Conference	6th IEEE Conference on Communications and Network Security, CNS 2018
Country/Territory	China
City	Beijing
Period	30/05/18 → 1/06/18

Funding

ACKNOWLEDGEMENT This work was supported in part by the US National Science Foundation under grants CNS-1566388, CNS-1717898, and CNS-1731833. This work was also supported by the National Natural Science Foundation of China under Grants No.61672262.

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10.1109/CNS.2018.8433203

Cite this

Alhanahnah, M., Lin, Q., Yan, Q., Zhang, N., & Chen, Z. (2018). Efficient signature generation for classifying cross-architecture IoT malware. In 2018 IEEE Conference on Communications and Network Security, CNS 2018 Article 8433203 (2018 IEEE Conference on Communications and Network Security, CNS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CNS.2018.8433203

@inproceedings{7e217771e3bc4922b30987977dd37a18,

title = "Efficient signature generation for classifying cross-architecture IoT malware",

author = "Mohannad Alhanahnah and Qicheng Lin and Qiben Yan and Ning Zhang and Zhenxiang Chen",

note = "Funding Information: ACKNOWLEDGEMENT This work was supported in part by the US National Science Foundation under grants CNS-1566388, CNS-1717898, and CNS-1731833. This work was also supported by the National Natural Science Foundation of China under Grants No.61672262. Publisher Copyright: {\textcopyright} 2018 IEEE.; 6th IEEE Conference on Communications and Network Security, CNS 2018 ; Conference date: 30-05-2018 Through 01-06-2018",

year = "2018",

month = aug,

day = "10",

doi = "10.1109/CNS.2018.8433203",

language = "English",

isbn = "9781538645864",

series = "2018 IEEE Conference on Communications and Network Security, CNS 2018",

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

booktitle = "2018 IEEE Conference on Communications and Network Security, CNS 2018",

}

Alhanahnah, M, Lin, Q, Yan, Q, Zhang, N & Chen, Z 2018, Efficient signature generation for classifying cross-architecture IoT malware. in 2018 IEEE Conference on Communications and Network Security, CNS 2018., 8433203, 2018 IEEE Conference on Communications and Network Security, CNS 2018, Institute of Electrical and Electronics Engineers Inc., 6th IEEE Conference on Communications and Network Security, CNS 2018, Beijing, China, 30/05/18. https://doi.org/10.1109/CNS.2018.8433203

Efficient signature generation for classifying cross-architecture IoT malware. / Alhanahnah, Mohannad; Lin, Qicheng; Yan, Qiben et al.
2018 IEEE Conference on Communications and Network Security, CNS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8433203 (2018 IEEE Conference on Communications and Network Security, CNS 2018).

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

TY - GEN

T1 - Efficient signature generation for classifying cross-architecture IoT malware

AU - Alhanahnah, Mohannad

AU - Lin, Qicheng

AU - Yan, Qiben

AU - Zhang, Ning

AU - Chen, Zhenxiang

N1 - Funding Information: ACKNOWLEDGEMENT This work was supported in part by the US National Science Foundation under grants CNS-1566388, CNS-1717898, and CNS-1731833. This work was also supported by the National Natural Science Foundation of China under Grants No.61672262. Publisher Copyright: © 2018 IEEE.

PY - 2018/8/10

Y1 - 2018/8/10

UR - https://www.scopus.com/pages/publications/85052552373

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U2 - 10.1109/CNS.2018.8433203

DO - 10.1109/CNS.2018.8433203

M3 - Conference contribution

AN - SCOPUS:85052552373

SN - 9781538645864

T3 - 2018 IEEE Conference on Communications and Network Security, CNS 2018

BT - 2018 IEEE Conference on Communications and Network Security, CNS 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 6th IEEE Conference on Communications and Network Security, CNS 2018

Y2 - 30 May 2018 through 1 June 2018

ER -

Alhanahnah M, Lin Q, Yan Q, Zhang N, Chen Z. Efficient signature generation for classifying cross-architecture IoT malware. In 2018 IEEE Conference on Communications and Network Security, CNS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8433203. (2018 IEEE Conference on Communications and Network Security, CNS 2018). doi: 10.1109/CNS.2018.8433203

Efficient signature generation for classifying cross-architecture IoT malware

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