A heuristic technique to detect phishing websites using TWSVM classifier

Rao, Routhu Srinivasa; Pais, Alwyn Roshan; Anand, Pritam

doi:10.1007/s00521-020-05354-z

Cited by 27 publications

(17 citation statements)

References 43 publications

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“…The app can identify zero-hour phishing attacks that blacklists are incapable to distinguish and it is quicker than visual-based appraisal procedures that are utilized in detecting phishing. Rao R. S. et al [16] proposed a heuristic strategy utilizing TWSVM (twin support vector machine) classifier to identify malignant enrolled phishing websites and furthermore websites that are facilitated on arrangement servers, to defeat the previously mentioned impediments. Their strategy distinguishes the phishing sites hosted on arrangement domains by looking at the sign-in webpage and a main webpage of the visited site.…”

Section: Heuristic-based Methodsmentioning

confidence: 99%

Phishing Detection Methods: A Review

Alanezi¹

2021

Technium

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The web has turned into a principal part of our conventional social and financial activities. The web isn't significant for singular clients just yet additionally for associations, since associations that offer web-based exchanging can accomplish an upper hand by serving overall customers. Webworks arriving at clients all around the globe with no commercial center limitations and with successful utilization of internet business. Consequently, Internet customers may be defenceless against different kinds of web risks, that may cause financial damages, information forgery, brand reputation mischief, the sacrifice of private information, and loss of customers' confidence in online business and electronic banking. Thusly, the reasonableness of the Internet for business exchanges becomes dubious. Phishing is seen as a design of web peril which is classified as the forte of mimicking a website of a legitimate undertaking proposing to gain a client's private accreditations, for instance, usernames, passwords, and federal retirement aide numbers. In this paper, we present an overview of cutting-edge research on such attacks. Besides, we expect to perceive the cutting-edge advancements in phishing, furthermore, give a far-reaching overview and comparison of these kinds of literatures to understand the hole that is as yet prevailing around anti-phishing. This overview will be for the most types of online phishing detection techniques for the last 4 years.

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Section: Heuristic-based Methodsmentioning

confidence: 99%

Phishing Detection Methods: A Review

Alanezi¹

2021

Technium

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“…suggested a heuristic strategy using a twin support vector machine. This method detects malicious phishing sites registered on vulnerable servers by matching the difference between hyperlink and URL features for both the URL of the visited page and the home page to classify phishing websites [20]. Tan et al (2020) have extracted a new characteristic to maximize the precision of phishing detection.…”

Section: Related Workmentioning

confidence: 99%

Detecting Phishing Cyber Attack Based on Fuzzy Rules and Differential Evaluation

Abdul-Hussein¹,

Mohammed²,

Kadhim³

2022

TEM Journal

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Cyber-criminal attacks witnessed various phishing attacks that blindly attract users to use their secret personal information. This research highlights this type of attack and proposes the development of a new model to detect phishing websites. Two aspects of improvement were followed. Firstly, a new feature is inferred from a combination of features with higher classification capability than the original features. Secondly, a novel method has been proposed by using differential evaluation (DE) to select the best rules among the fuzzy rule set; the DE is a viable way to optimize the fuzzy rule, improving the classification complexity. The proposed system was evaluated by applying two malicious and legitimate datasets collected from Phishtank and Alexa websites. Results show the combination feature can include a promising method for detecting phishing attacks according to the evaluation metrics in the precision of 0.973, recall of 0.933, F-measure of 0.947, and accuracy of 0.976.

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“…There proposed approach gained 99% accuracy overall. Rao (2020) proposed a novel heuristic approach for the detection of registered phishing sites and URLs hosted on compromised servers. They used login and home page of visiting sites for malicious website detection using URL, hyperlink, and similarity‐based features.…”

Section: Existing Researches On Detection Of Phishing Attacksmentioning

confidence: 99%

A review of phishing attacks and countermeasures for internet of things‐based smart business applications in industry 4.0

Sadiq

Anwar

Butt

et al. 2021

Human Behav and Emerg Tech

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Due to the advancement in industry 4.0, cybercrimes in internet‐based business applications are rapidly increasing. To encounter such attacks, the intruders use various tools and techniques such as Phishing, Malware, SQL Injection, Ransomware, Cross‐Site Scripting (XSS), Denial of Service (DoS), Session Hijacking, and Credential Reuse. Phishing is most commonly in practice in the current digital era. Phishing is a fraudulent attempt to obtain sensitive information from deceiving users. These types of cyber‐attacks are used to harm individuals or entire businesses depending on the targeted objective of the attacker. To combat these attacks, the research community provides various phishing detection techniques. In this article, we classify state‐of‐the‐art fishing detection techniques in five major categories, that are, (1) Data Mining, Deep Learning & Machine Learning‐Based Approach, (2) Search Engine‐Based Approach, (3) URL Scan‐Based Approach, (4) Blacklisting‐Whitelisting Approach, and (5) Visual Similarity‐Based Approach. Further, a comparative analysis is provided within each category concerning their strength and weaknesses. Moreover, the article provides phishing prevention best practices to the readers to avoid such attacks.

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A heuristic technique to detect phishing websites using TWSVM classifier

Cited by 27 publications

References 43 publications

Phishing Detection Methods: A Review

Phishing Detection Methods: A Review

Detecting Phishing Cyber Attack Based on Fuzzy Rules and Differential Evaluation

A review of phishing attacks and countermeasures for internet of things‐based smart business applications in industry 4.0

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