Abstract

The emergence of software artifacts greatly emphasizes the need for protecting intellectual property rights (IPR) hampered by software piracy requiring effective measures for software piracy control. Software birthmarking targets to counter ownership theft of software by identifying similarity of their origins. A novice birthmarking approach has been proposed in this paper that is based on hybrid of text-mining and graph-mining techniques. The code elements of a program and their relations with other elements have been identified through their properties (i.e., code constructs) and transformed into Graph Manipulation Language (GML). The software birthmarks generated by exploiting the graph theoretic properties (through clustering coefficient) are used for the classifications of similarity or dissimilarity of two programs. The proposed technique has been evaluated over metrics of credibility, resilience, method theft, modified code detection and self-copy detection for programs asserting the effectiveness of proposed approach against software ownership theft. The comparative analysis of proposed approach with contemporary ones shows better results for having properties and relations of program nodes and for employing dynamic techniques of graph mining without adding any overhead (such as increased program size and processing cost).

中文翻译：

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通过数据挖掘基于图相似度的软件胎记进行盗版控制

摘要

软件工件的出现极大地强调了保护受软件盗版影响的知识产权（IPR）的必要性，这需要采取有效措施来控制软件盗版。软件胎记标记旨在通过识别软件来源的相似性来应对软件的所有权盗窃。本文提出了一种新的胎记标记方法，该方法基于文本挖掘和图形挖掘技术的混合。程序的代码元素及其与其他元素的关系已通过其属性（即代码构造）进行了标识，并已转换为图形操作语言（GML）。通过利用图的理论特性（通过聚类系数）生成的软件胎记用于两个程序的相似性或不相似性分类。已通过程序的可信度，复原力，方法盗窃，修改后的代码检测和自复制检测等指标对所提出的技术进行了评估，这些程序断言了所提出的方法可有效防止软件所有权被盗。所提出的方法与现代方法的比较分析显示出更好的结果，因为它们具有程序节点的属性和关系，以及在不增加任何开销（例如增加程序大小和处理成本）的情况下采用图挖掘的动态技术。