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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 1 of 1 1 An Adversarial Attack Analysis on Malicious Advertisement URL Detection Framework ... Nowroozi, Ehsan; Abhishek; Mohammadi, Mohammadreza; Conti, Mauro. - : arXiv, 2022 Abstract: Malicious advertisement URLs pose a security risk since they are the source of cyber-attacks, and the need to address this issue is growing in both industry and academia. Generally, the attacker delivers an attack vector to the user by means of an email, an advertisement link or any other means of communication and directs them to a malicious website to steal sensitive information and to defraud them. Existing malicious URL detection techniques are limited and to handle unseen features as well as generalize to test data. In this study, we extract a novel set of lexical and web-scrapped features and employ machine learning technique to set up system for fraudulent advertisement URLs detection. The combination set of six different kinds of features precisely overcome the obfuscation in fraudulent URL classification. Based on different statistical properties, we use twelve different formatted datasets for detection, prediction and classification task. We extend our prediction analysis for mismatched and ... : 13 ... Keyword: Artificial Intelligence cs.AI; Cryptography and Security cs.CR; FOS Computer and information sciences; Machine Learning cs.LG; Networking and Internet Architecture cs.NI URL: https://dx.doi.org/10.48550/arxiv.2204.13172 https://arxiv.org/abs/2204.13172 BASE Hide details

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