NDLI: From Plagiarism to Malware Detection

Content Provider	IEEE Xplore Digital Library
Author	Oprisa, C. Cabau, G. Colesa, A.
Copyright Year	2013
Description	Author affiliation: Bitdefender, Romania (Oprisa, C.; Cabau, G.) \|\| Dept. of Comput. Sci., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania (Colesa, A.)
Abstract	We have often seen how malware families evolve over time: the malware authors add new features, change the order of functions, modify some strings or add random useless code. They do all that to evade detection. In a similar way, computer science students that copy homework will change variable and function names, rephrase comments or even replace some small portions of the code. In both cases, the essence remains the same and it is easy for one to see it, by comparing two samples or two source codes. The challenge however, is to automatically find groups of similar items in a large collection. Our research shows that we can apply the same techniques in order to cluster new malicious samples into malware families and detect plagiarized students work. The paper proposes a novel approach for computing the similarity between two items, based not only on their features, but also based on the frequencies of those features in a given population. The new similarity function was tested in a clustering algorithm and it proved better than other approaches. Also, the nature of the method allows it to be used in other document classification tasks.
Starting Page	227
Ending Page	234
File Size	301683
Page Count	8
File Format	PDF
ISBN	9781479930357
e-ISBN	9781479930364
DOI	10.1109/SYNASC.2013.37
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-23
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement malware n-grams plagiarism Entropy normalized compression distance Equations entropy Plagiarism Binary codes Malware Libraries clustering similarity metric
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A new string distance for computing binary code similarities

A New Normalized Similarity for Discriminating Similar Documents

Detecting Malware with Information Complexity

Plagiarism detection among source codes using adaptive local alignment of keywords

Similarity Calculation with Length Delimiting Dictionary Distance

An Alternative to NCD for Large Sequences, Lempel-Ziv Jaccard Distance

Plagiarism detection based on structural information

On the Use of Normalized Compression Distances for Image Similarity Detection

Plagiarism Detection Using Stopword n-Grams

From Plagiarism to Malware Detection