A fuzzy hashing technique for large scale software birthmarks

Takehiro Tsuzaki; Teruaki Yamamoto; Haruaki Tamada; Akito Monden

doi:10.1109/ICIS.2016.7550868

A fuzzy hashing technique for large scale software birthmarks

Takehiro Tsuzaki, Teruaki Yamamoto, Haruaki Tamada, Akito Monden

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

3 Citations (Scopus)

Abstract

Software birthmarks have been proposed as a method for enabling the detection of programs that may have been stolen by measuring the similarity between the two programs. A birthmark is created from each program by extracting its native characteristics. The birthmarks of the programs can then be compared. However, because the extracted birthmarks contain a large amount of information, a large amount of time is needed when using them to compare large programs. This paper describes our work to reduce this comparison time. Achieving faster comparisons will enable the evaluation of large programs and simplify the use of birthmarks. Specifically, our method creates hashes from conventional birthmark information using fuzzy hashing, and then measures the similarity of the programs using the obtained hash values. Using the proposed method, we achieved a major speed increase over the conventional birthmark method with distinction rates of over 90%. On the other hand, because preservation performance decreased substantially, the similarity threshold value needed to be lowered when using the proposed method.

Original language	English
Title of host publication	2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509008063
DOIs	https://doi.org/10.1109/ICIS.2016.7550868
Publication status	Published - Aug 23 2016
Event	15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016 - Okayama, Japan Duration: Jun 26 2016 → Jun 29 2016

Other

Other	15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016
Country/Territory	Japan
City	Okayama
Period	6/26/16 → 6/29/16

ASJC Scopus subject areas

Computer Science(all)
Energy Engineering and Power Technology
Control and Optimization

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10.1109/ICIS.2016.7550868

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A fuzzy hashing technique for large scale software birthmarks. / Tsuzaki, Takehiro; Yamamoto, Teruaki; Tamada, Haruaki et al.

2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. 7550868.

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

Tsuzaki, T, Yamamoto, T, Tamada, H & Monden, A 2016, A fuzzy hashing technique for large scale software birthmarks. in 2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings., 7550868, Institute of Electrical and Electronics Engineers Inc., 15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016, Okayama, Japan, 6/26/16. https://doi.org/10.1109/ICIS.2016.7550868

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abstract = "Software birthmarks have been proposed as a method for enabling the detection of programs that may have been stolen by measuring the similarity between the two programs. A birthmark is created from each program by extracting its native characteristics. The birthmarks of the programs can then be compared. However, because the extracted birthmarks contain a large amount of information, a large amount of time is needed when using them to compare large programs. This paper describes our work to reduce this comparison time. Achieving faster comparisons will enable the evaluation of large programs and simplify the use of birthmarks. Specifically, our method creates hashes from conventional birthmark information using fuzzy hashing, and then measures the similarity of the programs using the obtained hash values. Using the proposed method, we achieved a major speed increase over the conventional birthmark method with distinction rates of over 90%. On the other hand, because preservation performance decreased substantially, the similarity threshold value needed to be lowered when using the proposed method.",

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A fuzzy hashing technique for large scale software birthmarks

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