Malicious URL detection using machine learning: A survey

D Sahoo, C Liu, SCH Hoi - arXiv preprint arXiv:1701.07179, 2017 - arxiv.org
Malicious URL, aka malicious website, is a common and serious threat to cybersecurity.
Malicious URLs host unsolicited content (spam, phishing, drive-by exploits, etc.) and lure …

Detecting malicious URLs via a keyword-based convolutional gated-recurrent-unit neural network

W Yang, W Zuo, B Cui - Ieee Access, 2019 - ieeexplore.ieee.org
With the continuous development of Web attacks, many web applications have been
suffering from various forms of security threats and network attacks. The security detection of …

Adopting automated whitelist approach for detecting phishing attacks

NA Azeez, S Misra, IA Margaret, L Fernandez-Sanz - Computers & Security, 2021 - Elsevier
Phishing is considered a great scourge in cyberspace. Presently, there are two major
challenges known with the existing anti-phishing solutions. Low detection rate and lack of …

Malicious URL detection based on a parallel neural joint model

J Yuan, G Chen, S Tian, X Pei - Ieee Access, 2021 - ieeexplore.ieee.org
A parallel neural joint model algorithm is proposed for the analysis and detection of
malicious Uniform Resource Locator (URL). By detecting and analyzing malicious URL's …

Phishing url detection with lexical features and blacklisted domains

J Hong, T Kim, J Liu, N Park, SW Kim - Adaptive autonomous secure cyber …, 2020 - Springer
Many cyberattacks start with phishing to lure victims into malicious web pages where
malware codes are hidden. Victim machines are infected by malware and the attacker can …

[HTML][HTML] Detection and defending the XSS attack using novel hybrid stacking ensemble learning-based DNN approach

M Krishnan, Y Lim, S Perumal, G Palanisamy - Digital Communications and …, 2022 - Elsevier
Existing web-based security applications have failed in many situations due to the great
intelligence of attackers. Among web applications, Cross-Site Scripting (XSS) is one of the …

A bi-directional LSTM model with attention for malicious URL detection

F Ren, Z Jiang, J Liu - 2019 IEEE 4th Advanced Information …, 2019 - ieeexplore.ieee.org
Malicious URLs have become an important attack vector used by attackers to perpetrate
cybercrimes, how to effectively detect malicious URLs is an important and urgent problem to …

[HTML][HTML] A unified learning approach for malicious domain name detection

AA Wagan, Q Li, Z Zaland, S Marjan, DK Bozdar… - Axioms, 2023 - mdpi.com
The DNS firewall plays an important role in network security. It is based on a list of known
malicious domain names, and, based on these lists, the firewall blocks communication with …

Adaptive Quotient Filters

R Wen, H McCoy, D Tench, G Tagliavini… - arXiv preprint arXiv …, 2024 - arxiv.org
Adaptive filters, such as telescoping and adaptive cuckoo filters, update their representation
upon detecting a false positive to avoid repeating the same error in the future. Adaptive …

Evaluating the effectiveness of phishing reports on twitter

SS Roy, U Karanjit, S Nilizadeh - 2021 APWG Symposium on …, 2021 - ieeexplore.ieee.org
Phishing attacks are an increasingly potent web-based threat, with nearly 1.5 million such
websites being created on a monthly basis. In this work, we present the first study towards …