Malicious-URL Detection using Logistic Regression Technique
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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Web-based malicious software (malware) has been increasing over the Internet .It poses threats to computer users through web sites. Computers are infected with Web-based malware by drive-by-download attacks. Drive-by-download attacks force users to download and install the Web-based malware without being aware of it .these attacks evade detection by using automatic redirections to various websi...
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Nowadays, malicious URLs are the common threat to the businesses, social networks, net-banking etc. Existing approaches have focused on binary detection i.e. either the URL is malicious or benign. Very few literature is found which focused on the detection of malicious URLs and their attack types. Hence, it becomes necessary to know the attack type and adopt an effective countermeasure. This pa...
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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...
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ژورنال
عنوان ژورنال: International Journal of Engineering and Management Research
سال: 2019
ISSN: 2394-6962,2250-0758
DOI: 10.31033/ijemr.9.6.18