The impact of data fragment sizes on file type recognition

Research output: A Conference proceeding or a Chapter in BookConference contribution

1 Citation (Scopus)

Abstract

Determining the original file type of data fragments helps data recovery, spam detection, virus scanning, and network monitoring operations. In many cases, only unordered fragments of the original file are available for investigation. Therefore, we can only base on the content of a fragment to identify its file type. However, data fragments come with different sizes, as they may be the residual data recovered from storage media or network packets. It is stated that identifying the file type of larger fragments is easier than the smaller size ones [1]. Therefore, it is important to study the impact of data fragment sizes on file type recognition. In this paper, we study the results of applying machine learning technique to identify file types of data fragments of different sizes in order to find the minimum size required for file type recognition purpose.
Original languageEnglish
Title of host publication2014 10th International Conference on Natural Computation, ICNC 2014
EditorsShuhua Han, Tao Li
Place of PublicationChina
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages748-752
Number of pages5
ISBN (Electronic)9781479951512
ISBN (Print)9781479951505
DOIs
Publication statusPublished - 2014
Event2014 10th International Conference on Natural Computation, ICNC 2014 - Xiamen, Xiamen, China
Duration: 19 Aug 201421 Aug 2014

Publication series

Name2014 10th International Conference on Natural Computation, ICNC 2014

Conference

Conference2014 10th International Conference on Natural Computation, ICNC 2014
CountryChina
CityXiamen
Period19/08/1421/08/14

Fingerprint

Packet networks
Viruses
Learning systems
Scanning
Recovery
Monitoring

Cite this

TRAN, D., MA, W., & SHARMA, D. (2014). The impact of data fragment sizes on file type recognition. In S. Han, & T. Li (Eds.), 2014 10th International Conference on Natural Computation, ICNC 2014 (pp. 748-752). [6975930] (2014 10th International Conference on Natural Computation, ICNC 2014). China: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICNC.2014.6975930
TRAN, Dat ; MA, Wanli ; SHARMA, Dharmendra. / The impact of data fragment sizes on file type recognition. 2014 10th International Conference on Natural Computation, ICNC 2014. editor / Shuhua Han ; Tao Li. China : IEEE, Institute of Electrical and Electronics Engineers, 2014. pp. 748-752 (2014 10th International Conference on Natural Computation, ICNC 2014).
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title = "The impact of data fragment sizes on file type recognition",
abstract = "Determining the original file type of data fragments helps data recovery, spam detection, virus scanning, and network monitoring operations. In many cases, only unordered fragments of the original file are available for investigation. Therefore, we can only base on the content of a fragment to identify its file type. However, data fragments come with different sizes, as they may be the residual data recovered from storage media or network packets. It is stated that identifying the file type of larger fragments is easier than the smaller size ones [1]. Therefore, it is important to study the impact of data fragment sizes on file type recognition. In this paper, we study the results of applying machine learning technique to identify file types of data fragments of different sizes in order to find the minimum size required for file type recognition purpose.",
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TRAN, D, MA, W & SHARMA, D 2014, The impact of data fragment sizes on file type recognition. in S Han & T Li (eds), 2014 10th International Conference on Natural Computation, ICNC 2014., 6975930, 2014 10th International Conference on Natural Computation, ICNC 2014, IEEE, Institute of Electrical and Electronics Engineers, China, pp. 748-752, 2014 10th International Conference on Natural Computation, ICNC 2014, Xiamen, China, 19/08/14. https://doi.org/10.1109/ICNC.2014.6975930

The impact of data fragment sizes on file type recognition. / TRAN, Dat; MA, Wanli; SHARMA, Dharmendra.

2014 10th International Conference on Natural Computation, ICNC 2014. ed. / Shuhua Han; Tao Li. China : IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 748-752 6975930 (2014 10th International Conference on Natural Computation, ICNC 2014).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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AU - MA, Wanli

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N2 - Determining the original file type of data fragments helps data recovery, spam detection, virus scanning, and network monitoring operations. In many cases, only unordered fragments of the original file are available for investigation. Therefore, we can only base on the content of a fragment to identify its file type. However, data fragments come with different sizes, as they may be the residual data recovered from storage media or network packets. It is stated that identifying the file type of larger fragments is easier than the smaller size ones [1]. Therefore, it is important to study the impact of data fragment sizes on file type recognition. In this paper, we study the results of applying machine learning technique to identify file types of data fragments of different sizes in order to find the minimum size required for file type recognition purpose.

AB - Determining the original file type of data fragments helps data recovery, spam detection, virus scanning, and network monitoring operations. In many cases, only unordered fragments of the original file are available for investigation. Therefore, we can only base on the content of a fragment to identify its file type. However, data fragments come with different sizes, as they may be the residual data recovered from storage media or network packets. It is stated that identifying the file type of larger fragments is easier than the smaller size ones [1]. Therefore, it is important to study the impact of data fragment sizes on file type recognition. In this paper, we study the results of applying machine learning technique to identify file types of data fragments of different sizes in order to find the minimum size required for file type recognition purpose.

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TRAN D, MA W, SHARMA D. The impact of data fragment sizes on file type recognition. In Han S, Li T, editors, 2014 10th International Conference on Natural Computation, ICNC 2014. China: IEEE, Institute of Electrical and Electronics Engineers. 2014. p. 748-752. 6975930. (2014 10th International Conference on Natural Computation, ICNC 2014). https://doi.org/10.1109/ICNC.2014.6975930