A Classic Multi-method Collaborative Obfuscation Strategy

Yujie Ma; Yuanzhang Li; Zhibin Zhang; Ruyun Zhang; Lu Liu; Xiaosong Zhang

doi:10.1007/978-981-16-7502-7_10

A Classic Multi-method Collaborative Obfuscation Strategy

Yujie Ma, Yuanzhang Li, Zhibin Zhang, Ruyun Zhang, Lu Liu^*, Xiaosong Zhang

^*此作品的通讯作者

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Code obfuscation is a kind of powerful protection technique for software code. At present, research on obfuscation techniques is mainly focused on analyzing the effect of single obfuscation method, leaving few discussions on cooperative obfuscation of multiple methods. This paper firstly presented a brief introduction of the concept and methods of code obfuscation, then designed and implemented an obfuscator with multiple obfuscation methods. Then, a collaborative obfuscation strategy suitable for multiple obfuscation methods is proposed in detail. Finally, we verified that the obfuscation strategy indeed improves the performance of obfuscation through experiments.

源语言	英语
主期刊名	Data Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings
编辑	Ying Tan, Yuhui Shi, Albert Zomaya, Hongyang Yan, Jun Cai
出版商	Springer Science and Business Media Deutschland GmbH
页	90-97
页数	8
ISBN（印刷版）	9789811675010
DOI	https://doi.org/10.1007/978-981-16-7502-7_10
出版状态	已出版 - 2021
活动	6th International Conference on Data Mining and Big Data, DMBD 2021 - Guangzhou, 中国期限: 20 10月 2021 → 22 10月 2021

出版系列

姓名	Communications in Computer and Information Science
卷	1454 CCIS
ISSN（印刷版）	1865-0929
ISSN（电子版）	1865-0937

会议

会议	6th International Conference on Data Mining and Big Data, DMBD 2021
国家/地区	中国
市	Guangzhou
时期	20/10/21 → 22/10/21

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10.1007/978-981-16-7502-7_10

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引用此

Ma, Y., Li, Y., Zhang, Z., Zhang, R., Liu, L., & Zhang, X. (2021). A Classic Multi-method Collaborative Obfuscation Strategy. 在 Y. Tan, Y. Shi, A. Zomaya, H. Yan, & J. Cai (编辑), Data Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings (页码 90-97). (Communications in Computer and Information Science; 卷 1454 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-7502-7_10

Ma, Yujie ; Li, Yuanzhang ; Zhang, Zhibin 等. / A Classic Multi-method Collaborative Obfuscation Strategy. Data Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings. 编辑 / Ying Tan ; Yuhui Shi ; Albert Zomaya ; Hongyang Yan ; Jun Cai. Springer Science and Business Media Deutschland GmbH, 2021. 页码 90-97 (Communications in Computer and Information Science).

@inproceedings{4d6163b58e944ea3b6bf335d85e01fef,

title = "A Classic Multi-method Collaborative Obfuscation Strategy",

abstract = "Code obfuscation is a kind of powerful protection technique for software code. At present, research on obfuscation techniques is mainly focused on analyzing the effect of single obfuscation method, leaving few discussions on cooperative obfuscation of multiple methods. This paper firstly presented a brief introduction of the concept and methods of code obfuscation, then designed and implemented an obfuscator with multiple obfuscation methods. Then, a collaborative obfuscation strategy suitable for multiple obfuscation methods is proposed in detail. Finally, we verified that the obfuscation strategy indeed improves the performance of obfuscation through experiments.",

keywords = "Code obfuscation, Collaborative obfuscation, JavaScript, Software maintainability index",

author = "Yujie Ma and Yuanzhang Li and Zhibin Zhang and Ruyun Zhang and Lu Liu and Xiaosong Zhang",

note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; 6th International Conference on Data Mining and Big Data, DMBD 2021 ; Conference date: 20-10-2021 Through 22-10-2021",

year = "2021",

doi = "10.1007/978-981-16-7502-7_10",

language = "English",

isbn = "9789811675010",

series = "Communications in Computer and Information Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "90--97",

editor = "Ying Tan and Yuhui Shi and Albert Zomaya and Hongyang Yan and Jun Cai",

booktitle = "Data Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings",

address = "Germany",

}

Ma, Y, Li, Y, Zhang, Z, Zhang, R, Liu, L & Zhang, X 2021, A Classic Multi-method Collaborative Obfuscation Strategy. 在 Y Tan, Y Shi, A Zomaya, H Yan & J Cai (编辑), Data Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings. Communications in Computer and Information Science, 卷 1454 CCIS, Springer Science and Business Media Deutschland GmbH, 页码 90-97, 6th International Conference on Data Mining and Big Data, DMBD 2021, Guangzhou, 中国, 20/10/21. https://doi.org/10.1007/978-981-16-7502-7_10

A Classic Multi-method Collaborative Obfuscation Strategy. / Ma, Yujie; Li, Yuanzhang; Zhang, Zhibin 等.
Data Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings. 编辑 / Ying Tan; Yuhui Shi; Albert Zomaya; Hongyang Yan; Jun Cai. Springer Science and Business Media Deutschland GmbH, 2021. 页码 90-97 (Communications in Computer and Information Science; 卷 1454 CCIS).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - A Classic Multi-method Collaborative Obfuscation Strategy

AU - Ma, Yujie

AU - Li, Yuanzhang

AU - Zhang, Zhibin

AU - Zhang, Ruyun

AU - Liu, Lu

AU - Zhang, Xiaosong

PY - 2021

Y1 - 2021

N2 - Code obfuscation is a kind of powerful protection technique for software code. At present, research on obfuscation techniques is mainly focused on analyzing the effect of single obfuscation method, leaving few discussions on cooperative obfuscation of multiple methods. This paper firstly presented a brief introduction of the concept and methods of code obfuscation, then designed and implemented an obfuscator with multiple obfuscation methods. Then, a collaborative obfuscation strategy suitable for multiple obfuscation methods is proposed in detail. Finally, we verified that the obfuscation strategy indeed improves the performance of obfuscation through experiments.

AB - Code obfuscation is a kind of powerful protection technique for software code. At present, research on obfuscation techniques is mainly focused on analyzing the effect of single obfuscation method, leaving few discussions on cooperative obfuscation of multiple methods. This paper firstly presented a brief introduction of the concept and methods of code obfuscation, then designed and implemented an obfuscator with multiple obfuscation methods. Then, a collaborative obfuscation strategy suitable for multiple obfuscation methods is proposed in detail. Finally, we verified that the obfuscation strategy indeed improves the performance of obfuscation through experiments.

KW - Code obfuscation

KW - Collaborative obfuscation

KW - JavaScript

KW - Software maintainability index

UR - http://www.scopus.com/inward/record.url?scp=85119621181&partnerID=8YFLogxK

U2 - 10.1007/978-981-16-7502-7_10

DO - 10.1007/978-981-16-7502-7_10

M3 - Conference contribution

AN - SCOPUS:85119621181

SN - 9789811675010

T3 - Communications in Computer and Information Science

SP - 90

EP - 97

BT - Data Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings

A2 - Tan, Ying

A2 - Shi, Yuhui

A2 - Zomaya, Albert

A2 - Yan, Hongyang

A2 - Cai, Jun

PB - Springer Science and Business Media Deutschland GmbH

T2 - 6th International Conference on Data Mining and Big Data, DMBD 2021

Y2 - 20 October 2021 through 22 October 2021

ER -

Ma Y, Li Y, Zhang Z, Zhang R, Liu L, Zhang X. A Classic Multi-method Collaborative Obfuscation Strategy. 在 Tan Y, Shi Y, Zomaya A, Yan H, Cai J, 编辑, Data Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. 页码 90-97. (Communications in Computer and Information Science). doi: 10.1007/978-981-16-7502-7_10

A Classic Multi-method Collaborative Obfuscation Strategy

摘要

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会议

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