Detecting Malicious URL using Machine Learning: A Survey
نویسندگان
چکیده
منابع مشابه
Malicious URL Detection using Machine Learning: A Survey
Malicious URL, a.k.a. malicious website, is a common and serious threat to cybersecurity. Malicious URLs host unsolicited content (spam, phishing, drive-by exploits, etc.) and lure unsuspecting users to become victims of scams (monetary loss, theft of private information, and malware installation), and cause losses of billions of dollars every year. It is imperative to detect and act on such th...
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Malicious URLs host unsolicited content and are used to perpetrate cybercrimes. It is imperative to detect them in a timely manner. Traditionally, this is done through the usage of blacklists, which cannot be exhaustive, and cannot detect newly generated malicious URLs. To address this, recent years have witnessed several efforts to perform Malicious URL Detection using Machine Learning. The mo...
متن کاملComparisons of machine learning techniques for detecting malicious webpages
This paper compares machine learning techniques for detecting malicious webpages. The conventional method of detecting malicious webpages is going through the black list and checking whether the webpages are listed. Black list is a list of webpages which are classified as malicious from a user's point of view. These black lists are created by trusted organizations and volunteers. They are then ...
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Seeking sensitive user data in the form of online banking user-id and passwords or credit card information, which may then be used by ‘phishers’ for their own personal gain is the primary objective of the phishing e-mails. With the increase in the online trading activities, there has been a phenomenal increase in the phishing scams which have now started achieving monstrous proportions. This pa...
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JavaScript has become a ubiquitous Web technology that enables interactive and dynamic Web sites. The widespread adoption, along with some of its properties allowing authors to easily obfuscate their code, make JavaScript an interesting venue for malware authors. In this survey paper, we discuss some of the difficulties in dealing with malicious JavaScript code, and go through some recent appro...
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ژورنال
عنوان ژورنال: International Journal for Research in Applied Science and Engineering Technology
سال: 2020
ISSN: 2321-9653
DOI: 10.22214/ijraset.2020.5447