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In software engineering, if two code fragments are closely similar with minor modifications, or even identical as a result of copy-paste behavior, they are called software/code clones. Code clones can cause trouble in software maintenance and the debugging process because identifying all copied compromised code fragments in other locations is time-consuming. Researchers have been studying code clone detection issues for a long time, and the discussion mainly focuses on software engineering management and system maintenance. Another considerable issue is that code cloning provides an easy way for attackers to maliciously inject code. A thorough survey of code clone identification/detection from the security perspective is indispensable for providing a comprehensive review of previous related studies and proposing potential research directions. This paper satisfies the above requirements. We review and introduce previous security-related studies following three classifications and various comparison criteria. We then discuss three further research directions: (i) deep learning-based code clone vulnerability detection, (ii) vulnerable code clone detection for 5G-Internet of Things devices, and (iii) real-time detection methods for more efficiently detecting clone attacks. These methods are more advanced and adaptive to technological development and still have sufficient research space for future studies.

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Cited by 10 publications

References 16 publications

A method for vulnerability detection by IoT network traffic analytics

A method for vulnerability detection by IoT network traffic analytics

Framework to Analyse and Exploit the Smart Home IoT Firmware

A Survey of Software Clone Detection From Security Perspective

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