Browsing by Subject "Keyword extraction"
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Item Open Access AyatDroid: a lightweight code cloning technique using different static features(IEEE - Institute of Electrical and Electronics Engineers, 2023-08-23) Glani, Y.; Ping, L.; Lin, K.; Shah, Syed AsadIn recent decades, malicious code reuse has surged in numbers and sophistication, it is a common practice among adversaries to reuse malicious code, which significantly threatens user privacy and security. Several signature-based code clone detection techniques have been proposed to detect malicious clones in Android applications that use the MD5 hash function to generate signatures. Meanwhile, these techniques only retrieve signatures from Java files. Due to the 128-bit signature size of the MD5 hash function, these techniques take longer to generate signatures. In this article, we propose the AyatDroid technique, which efficiently identifies malicious chunks by retrieving signatures from Java and manifest files. AyatDroid technique is tested on reliable CiCMalDroid 2020 dataset. We have evaluated the AyatDroid technique with other cutting-edge code clone detection techniques. Our experimental results demonstrated that AyatDroid outperformed regarding detection time and accuracy. AyatDroid is not only lightweight but also efficient, allowing it to be implemented on the large scale.Item Open Access Using lexical chains for keyword extraction(Elsevier Ltd, 2007-11) Ercan, G.; Cicekli, I.Keywords can be considered as condensed versions of documents and short forms of their summaries. In this paper, the problem of automatic extraction of keywords from documents is treated as a supervised learning task. A lexical chain holds a set of semantically related words of a text and it can be said that a lexical chain represents the semantic content of a portion of the text. Although lexical chains have been extensively used in text summarization, their usage for keyword extraction problem has not been fully investigated. In this paper, a keyword extraction technique that uses lexical chains is described, and encouraging results are obtained. © 2007 Elsevier Ltd. All rights reserved.