Phishing attack detection using machine learning method

Jupin, John Arthur (2019) Phishing attack detection using machine learning method. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang.

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The development of computer networks today is increased rapidly. This can be shown based on the trend of every computer user around the world, whereby they need to connect their computer to the Internet. This shows that the use of Internet networks is very important, whether they used it for work and assignment purposes, or for the access to social media accounts, such as Instagram, Facebook and Twitter. However, in this wide use of this computer network, the privacy of computer users is in danger. This is because some of the computer users do not install security system in their computer. This problem will allow the hackers to hack and commit the network attacks. This is very dangerous, especially to the important organizations because hackers can disable the online system in the company, steal confidential information and subsequently steal company money through online without being aware of any one. The attacks that can be made includes denial-of-Service attack, DNS spoofing attack and phishing attack. The goal of this study is to apply anti-phishing tools in preventing the network security attack in an organization. In this study, phishing attacks have been studied thoroughly. After a study has been made, machine learning method is used to prevent the phishing attack. Besides, the study also shows that phishing attack is always related to the spam attack, where there might be attached phishing link in the spam message. This spam message includes the email and the SMS message that received by the user. There are several algorithms that can be used in the machine learning method to prevent the both attacks. The Naïve Bayes algorithm, Decision Tree algorithm and Support Vector Machine algorithm has been used to prevent the spam attack, as well as the phishing attack. The study of this algorithm is made thoroughly and the methods in implementing this algorithm have been discussed in detail. The experiment is conducted for the datasets that obtained by using machine learning method. The results are obtained, showing the performance of machine learning method on each dataset.

Item Type: Undergraduates Project Papers
Additional Information: Project Paper (Bachelors of Computer Science (Computer Systems & Networking)) -- Universiti Malaysia Pahang – 2019, SV: DR. MOHD ARFIAN BIN ISMAIL, e-Thesis
Uncontrolled Keywords: Phishing attacks; Machine learning method; Algorithm
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Sufarini Mohd Sudin
Date Deposited: 23 Dec 2019 03:56
Last Modified: 02 Nov 2023 03:35
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