• Journal of KIISE:Software and Applications
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• v.35 no.7
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• pp.442-451
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• 2008

Most plagiarism detection systems evaluate the similarity of source codes and detect plagiarized program pairs. If we use the source codes in plagiarism detection, the source code security can be a significant problem. Plagiarism detection based on target code can be used for protecting the security of source codes. In this paper, we propose a new plagiarism detection technique for Java programs using bytecodes without referring their source codes. The plagiarism detection procedure using bytecode consists of two major steps. First, we generate the token sequences from the Java class file by analyzing the code area of methods. Then, we evaluate the similarity between token sequences using the adaptive local alignment. According to the experimental results, we can find the distributions of similarities of the source codes and that of bytecodes are very similar. Also, the correlation between the similarities of source code pairs and those of bytecode pairs is high enough for typical test data. The plagiarism detection system using bytecode can be used as a preliminary verifying tool before detecting the plagiarism by source code comparison.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1627-1648
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• 2012

We propose an adaptive method for detecting plagiarized pairs from a large set of source code. This method is adaptive in that it uses an adaptive algorithm and it provides an adaptive threshold for determining plagiarism. Conventional algorithms are based on greedy string tiling or on local alignments of two code strings. However, most of them are not adaptive; they do not consider the characteristics of the program set, thereby causing a problem for a program set in which all the programs are inherently similar. We propose adaptive local alignment-a variant of local alignment that uses an adaptive similarity matrix. Each entry of this matrix is the logarithm of the probabilities of the keywords based on their frequency in a given program set. We also propose an adaptive threshold based on the local outlier factor (LOF), which represents the likelihood of an entity being an outlier. Experimental results indicate that our method is more sensitive than JPlag, which uses greedy string tiling for detecting plagiarism-suspected code pairs. Further, the adaptive threshold based on the LOF is shown to be effective, and the detection performance shows high sensitivity with negligible loss of specificity, compared with that using a fixed threshold.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.6
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• pp.189-196
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• 2014

Though the plagiarism is illegal and should be avoided, it still occurs frequently. Particularly, the plagiarism of source codes is more frequently committed than others since it is much easier to copy them because of their digital nature. To prevent code plagiarism, there have been reported a variety of studies. However, previous studies for plagiarism detection techniques on source codes do not consider the data structures although a source code consists both of data structures and algorithms. In this paper, a plagiarism detection technique for source codes considering data structures is proposed. Specifically, the data structures of two source codes are represented as sets of trees and compared with each other using Hungarian Method. To show the usefulness of this technique, an experiment has been performed on 126 source codes submitted as homework results in an object-oriented programming course. When both the data structures and the algorithms of the source codes are considered, the precision and the F-measure score are improved 22.6% and 19.3%, respectively, than those of the case where only the algorithms are considered.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.72-78
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• 2003

In this paper, survey of technical methods for protecting intellectual properties and proposal of art works plagiarism detection are accomplished. For this, in this paper, a survey of technical methods for inspecting of program source code plagiarism, analysis of natural languages plagiarism types and existing inspection methods are accomplished Also, author verification system and plagiarism detection about ancient literatures or art works is proposed because of ancient literatures or art work are important in the aspect of cultural properties control, protecting of author's intellectual property and owner's property estimation.

• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.833-838
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• 2006

Program Plagiarism is an infringement of software copyright. In detecting program plagiarism, many different source program comparison methods has been studied. But, it is not easy to detect plagiarized program that made a few cosmetic changes in program structures and variable names In this paper, we propose a new ground-breaking technique in detecting plagiarism by Memory Access Log Analysis.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.809-817
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• 2008

Program plagiarism is widespread due to intelligent software and the global Internet environment. Consequently the detection of plagiarized source code and software is becoming important especially in academic field. Though numerous studies have been reported for detecting plagiarized pairs of codes, we cannot find any profound work on understanding the underlying mechanisms of plagiarism. In this paper, we study the evolutionary process of source codes regarding that the plagiarism procedure can be considered as evolutionary steps of source codes. The final goal of our paper is to reconstruct a tree depicting the evolution process in the source code. To this end, we extend the well-known bioinformatics approach, a local alignment approach, to detect a region of similar code with an adaptive scoring matrix. The asymmetric code similarity based on the local alignment can be considered as one of the main contribution of this paper. The phylogenetic tree or evolution tree of source codes can be reconstructed using this asymmetric measure. To show the effectiveness and efficiency of the phylogeny construction algorithm, we conducted experiments with more than 100 real source codes which were obtained from East-Asia ICPC(International Collegiate Programming Contest). Our experiments showed that the proposed algorithm is quite successful in reconstructing the evolutionary direction, which enables us to identify plagiarized codes more accurately and reliably. Also, the phylogeny construction algorithm is successfully implemented on top of the plagiarism detection system of an automatic program evaluation system.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.394-402
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• 2010

JavaScript is one of the most popular languages to develope web sites and web applications. Since applicationss written in JavaScript are sent to clients as the original source code, they are easily exposed to plagiarists. Therefore, a method to detect plagiarized JavaScript programs is necessary. The conventional program dependency graph(PDG) based approaches are not suitable to analyze JavaScript programs because they do not reflect dynamic features of JavaScript. They also generate false positives in some cases and show inefficiency with large scale search space. We devise a JavaScript specific PDG(JS PDG) that captures dynamic features of JavaScript and propose a JavaScript plagiarism detection method for precise and fast detection. We evaluate the proposed plagiarism detection method with experiment. Our experiments show that our approach can detect false-positives generated by conventional PDG and can prune the plagiarism search space.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.44-53
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• 2010

Program plagiarism is a significant factor to reduce the quality of education in computer programming. In this paper, we propose the technique of identifying similar or identical programs in order to prevent students from reckless copying their programming assignments. Existing approaches for identifying similar programs are mainly based on fingerprints or pattern matching for text documents. Different from those existing approaches, we propose an approach based on the program structur. Using paring progrmas, we first transform programs into XML documents by representing syntactic components in the programs with elements in XML document, then run X-tree Diff+, which is the change detection algorithm for XML documents, and produce an edit script as a change. The decision of similar or identical programs is made on the analysis of edit scripts in terms of program plagiarism. Analysis of edit scripts allows users to understand the process of conversion between two programs so that users can make qualitative judgement considering the characteristics of program assignment and the degree of plagiarism.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.453-462
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• 2009

Studies on software plagiarism detection, prevention and judgement have become widespread due to the growing of interest and importance for the protection and authentication of software intellectual property. Many previous studies focused on comparing all pairs of submitted codes by using attribute counting, token pattern, program parse tree, and similarity measuring algorithm. It is important to provide a clear-cut model for distinguishing plagiarism and collaboration. This paper proposes a source code clustering algorithm using a probability model on extreme value distribution. First, we propose an asymmetric distance measure pdist($P_a$, $P_b$) to measure the similarity of $P_a$ and $P_b$ Then, we construct the Plagiarism Direction Graph (PDG) for a given program set using pdist($P_a$, $P_b$) as edge weights. And, we transform the PDG into a Gumbel Distance Graph (GDG) model, since we found that the pdist($P_a$, $P_b$) score distribution is similar to a well-known Gumbel distribution. Second, we newly define pseudo-plagiarism which is a sort of virtual plagiarism forced by a very strong functional requirement in the specification. We conducted experiments with 18 groups of programs (more than 700 source codes) collected from the ICPC (International Collegiate Programming Contest) and KOI (Korean Olympiad for Informatics) programming contests. The experiments showed that most plagiarized codes could be detected with high sensitivity and that our algorithm successfully separated real plagiarism from pseudo plagiarism.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.352-367
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• 2003

The syntactic and semantic characteristics of a computer program can be represented by the keywords sequence extracted from the source code. Therefore the similarity and the difference between two programs can be clearly figured out by comparing the keyword sequences obtained from the given programs. Various methods for measuring the similarity of two different sequences have been intensively studied already in bioinformatics on biological genetic sequence manipulation. In this paper, we propose a new method for measuring the similarity of two different programs and detecting the partial plagiarism by exploiting the sequence alignment techniques. In order to evaluate the performance of the proposed method, we experimented with the actual Program codes submitted by 70 students attending a Data Structure course )tow 2001. The experimental results show that the proposed method is more effective and powerful than the fingerprint method which is the most commonly used for the Plagiarism detection.