Related references
Note: Only part of the references are listed.
Article
Computer Science, Artificial Intelligence
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Summary: This research proposes a novel phishing detection model, MOE/RF, which utilizes the revised multi-objective evolution optimization algorithm and random forest. By focusing on accuracy and minimizing false detection, the MOE/RF model outperforms several existing methods.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
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Article
Computer Science, Information Systems
Emilio Figueras-Martin et al.
Summary: This study analyzes the website connectivity, relationships, and content of a relatively unknown and less explored darknet, Freenet. The results show that Freenet has a large number of available websites, significant nodes in the network connectivity structure, and underage pornography as the predominant illegal content.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
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Summary: Phishing attacks are challenging cyberattacks that involve a large number of entities in online transactions and services. This study presents a methodology for detecting phishing websites in real scenarios using URL, HTML, and web technology features. The researchers also created a dataset of 134,000 verified samples for testing and comparison purposes.
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Article
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Summary: This study compares machine learning and deep learning techniques and presents a method for detecting phishing websites through URL analysis. It demonstrates that existing techniques have a high false-positive rate when testing with URLs from legitimate login pages.
Proceedings Paper
Computer Science, Information Systems
Qian Cui et al.
Summary: This paper introduces a new method of defense against phishing attacks by detecting messages sent to attackers in real time. This method can block attacks immediately and is also beneficial for email providers. Using a Recurrent Neural Network to learn the structure of exfiltrating emails proves to be the most effective approach.
APPLIED CRYPTOGRAPHY AND NETWORK SECURITY, ACNS 2021, PT II
(2021)
Article
Computer Science, Information Systems
Javier Velasco-Mata et al.
Summary: Botnets pose a significant threat to online security, leading to substantial economic losses worldwide. By employing feature selection techniques like Information Gain and Gini Importance, the Decision Tree model achieved the highest performance with a mean F1 score of 85% using a five feature set.
Proceedings Paper
Computer Science, Information Systems
Shoma Tanaka et al.
Summary: The researchers have proposed a method based on the similarity of website structures to effectively detect phishing sites not registered with blocklists, including those with different appearances but similar structures. Through evaluation and experimentation, the method was shown to identify phishing sites constructed using the same tools. Furthermore, the method can be improved based on the importance of web resources in web access logs.
2021 IEEE CONFERENCE ON DEPENDABLE AND SECURE COMPUTING (DSC)
(2021)
Review
Computer Science, Information Systems
Mohammad Hijji et al.
Summary: The COVID-19 pandemic has brought about significant social and economic impacts on the world, including a rise in cybersecurity challenges focused on social engineering-based cyber-attacks. These attacks, utilizing techniques like phishing, scamming, spamming, smishing, and vishing, along with fake emails, websites, and mobile apps, have targeted critical infrastructure such as hospitals and healthcare services. The study also highlights the use of malicious software like ransomware, trojans, and bots, and emphasizes the need for advanced technology like AI, blockchain, and big data analytics for future cybersecurity solutions.
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