A novel lightweight URL phishing detection system using SVM and similarity index
نویسندگان
چکیده
منابع مشابه
A Review on Phishing URL Detection using Machine Learning Systems
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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Phishing attacks rise in quantity and quality. With short online lifetimes of those attacks, classical blacklist based approaches are not su cient to protect online users. While attackers manage to achieve high similarity between original and fraudulent websites, this fact can also be used for attack detection. In many cases attackers try to make the Internet address (URL) from a website look s...
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Phishing is a kind of attack that belongs to social engineering and this attack seeks to trick people in order to let them reveal their confidential information. Several methods are introduced to detect phishing websites by using different types of features. Unfortunately, these techniques implemented for specific attack vector such as detecting phishing emails which make implementing wide scop...
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— Pattern classification is a branch of machine learning that focuses on recognition of patterns and regularities in data. In adversarial applications like biometric authentication, spam filtering, network intrusion detection the pattern classification systems are used. Extending pattern classification theory and design methods to adversarial environment is thus a novel and very relevant resear...
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I. INTRODUCTION Increasing use of Internet banking and shopping by a broad spectrum of users results in greater potential profits from phishing attacks. Phish are fake websites that masquerade as legitimate sites, to trick unsuspecting users into sharing sensitive information: credentials, passwords, financial information, or other personal information that can enable fraud. This threat is espe...
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ژورنال
عنوان ژورنال: Human-centric Computing and Information Sciences
سال: 2017
ISSN: 2192-1962
DOI: 10.1186/s13673-017-0098-1