Using Sequential Minimal Optimization for Phishing Attack Detection
- Ali Mohammad H. Al-Ibrahim
With the development of Internet technology and electronic transactions, the problem of software security has become a reality that must be confronted and is no longer an option that can be abandoned. For this reason, software must be protected in all available ways. Where attackers use many methods to enable them to penetrate systems, especially those that rely on the Internet and hackers try to identify the vulnerabilities in the programs and exploit them to enter the database and steal sensitive information.
Electronic phishing is a form of illegal access to information, such as user names, passwords, credit card details, etc. Where attackers use different types of tricks to reveal confidential user information. Where attacks appear as links and phishing is done by clicking on the links contained in them. This leads to obtaining confidential information by using those false emails, redirecting the user without his knowledge to a site similar to the site he wants to access and capturing information. The main purpose of this paper is to protect users from malicious pages that are intended to steal personal information. Therefore, an electronic phishing detection algorithm called the SMO algorithm, which deals only with the properties of links, has been used.
Weka was used in the classification process. The samples were the characteristics of the links and they contain a number of sites which were 8266 and the number of phishing sites 4116 and legitimate sites 4150 sites and results were found to be new for the previous algorithms where the real classification rate 99.0202% in the time of 1.68 seconds.
(The data was calculated based on Google Scholar Citations)
h-index (January 2018): 30
i10-index (January 2018): 163
h5-index (January 2018): 19
h5-median(January 2018): 25
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