Birthmark-Based Software Classification Using Rough Sets

详细信息    查看全文

• 作者：Shah Nazir ; Sara Shahzad ; Lala Septem Riza
• 关键词：Software birthmark ; Software classification ; Rough set theory
• 刊名：Arabian Journal for Science and Engineering
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：42
• 期：2
• 页码：859-871
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Engineering, general; Science, Humanities and Social Sciences, multidisciplinary;
• 出版者：Springer Berlin Heidelberg
• ISSN：2191-4281
• 卷排序：42

文摘

Software theft or piracy is a rapidly growing problem which includes copying, modifying, and misusing proprietary software opposed to the license agreement. Software birthmark is a property of software that has been used for the detection of software theft successfully. Two separate pieces of software can be compared to identify the similarity in code by using their birthmarks. Comparison of the birthmarks of the softwares in question tells us whether software is a duplicate copy of another software or not. Similarity in birthmarks of two computer programs indicates that they are same. Until now, classification of software as pirated or not pirated still becomes a challenging task. Therefore, in this paper we present the use of rough set theory, which is a mathematical approach to deal with vagueness and uncertainty in classification problems. The technique is validated through an empirical case study. Some experiments show that the techniques are successful in assessing the specified properties of the birthmark and thus providing a valid classification decision.