A Machine-Learning Approach to Phishing Detection and Defense

Other author Amiri, I. S.
Other author Akanbi, O. A.
Other author Fazeldehkordi, E.
Format Electronic
Publication InfoSyngress Press [Imprint] San Diego : Elsevier Science & Technology Books
Description100 p. 22.900 x 015.200 cm.
Supplemental ContentFull text available from eBook - Computer Science 2015 [EBCCS15]

Summary Annotation Phishing is one of the most widely-perpetrated forms of cyber attack, used to gather sensitive information such as credit card numbers, bank account numbers, and user logins and passwords, as well as other information entered via a web site. The authors of "A Machine-Learning Approach to Phishing Detetion and Defense" have conducted research to demonstrate how a machine learning algorithm can be used as an effective and efficient tool in detecting phishing websites and designating them as information security threats. This methodology can prove useful to a wide variety of businesses and organizations who are seeking solutions to this long-standing threat. "A Machine-Learning Approach to Phishing Detetion and Defense" also provides information security researchers with a starting point for leveraging the machine algorithm approach as a solution to other information security threats.Discover novel research into the uses of machine-learning principles and algorithms to detect and prevent phishing attacksHelp your business or organization avoid costly damage from phishing sourcesGain insight into machine-learning strategies for facinga variety of information security threats"
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
ISBN9780128029275
ISBN0128029277 (Trade Paper) Active Record
Standard identifier# 9780128029275
Stock number00991439

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