Results 91 to 100 of about 9,881 (133)
Detecting phishing website using Pattern Mining
IOP Conference Series: Materials Science and Engineering, 2019 Abstract Nowadays users are purchasing products and payments through online. While using these websites they will ask for the information of the users like username and password etc. There are some websites which are used to hack the details of the user. This type of websites is called phishing websites.
B Sreelekha, B Harika, Mrs.L. Sujihelen
openaire +1 more source
Managing cyberattacks in wartime: The case of Ukraine
Public Administration Review, Volume 85, Issue 3, Page 619-627, May/June 2025.Abstract Cybersecurity specialists face continual challenges in protecting organizations and societies from ever‐evolving cyberattacks. These challenges intensify dramatically in the context of war, yet our understanding of cyberattacks during wartime is limited.
Iryna Fyshchuk +2 more
wiley +1 more source
Cyber-crime Science = Crime Science + Information Security [PDF]
, 2010 Cyber-crime Science is an emerging area of study aiming to prevent cyber-crime by combining security protection techniques from Information Security with empirical research methods used in Crime Science.
Hartel, Pieter +2 more
core +2 more sources
Cybersecurity and Data Protection Practices Among Australian Dermatologists
Australasian Journal of Dermatology, Volume 66, Issue 7, Page e474-e480, November 2025.
Nicole Kah Mun Yoong +2 more
wiley +1 more source
Design of Efficient Phishing Detection Model using Machine Learning
Tehnički GlasnikRecently, there have been cases of phishing attempts to steal personal information through fake sites disguised as major sites. Although phishing attacks continue and increase, countermeasures remain in the form of defense after identifying the attack ...
Bong-Hyun Kim
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Anti-phishing as a web-based user service [PDF]
, 2006 This paper describes the recent phenomenon of phishing, in which email messages are sent to unwitting recipients in order to elicit personal information and perpetrate identity theft and financial fraud.
Cranston, C., Weir, G.R.S.
core
An Evasion Attack against ML-based Phishing URL Detectors
, 2020 Background: Over the year, Machine Learning Phishing URL classification (MLPU) systems have gained tremendous popularity to detect phishing URLs proactively. Despite this vogue, the security vulnerabilities of MLPUs remain mostly unknown. Aim: To address
Babar, M. Ali, Gaire, Raj, Sabir, Bushra
core
Investigation of Attitudes Towards Security Behaviors [PDF]
, 2018 Cybersecurity attacks have increased as Internet technology has proliferated. Symantec’s 2013 Internet Security Report stated that two out of the top three causes of data breaches in 2012 were attributable to human error (Pelgrin, 2014).
Kelley, Daniel
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Detecting and characterizing lateral phishing at scale [PDF]
, 2019 We present the first large-scale characterization of lateral phishing attacks, based on a dataset of 113 million employee-sent emails from 92 enterprise organizations. In a lateral phishing attack, adversaries leverage a compromised enterprise account to
Cidon, A +7 more
core +2 more sources
IEEE AccessRecent advancements in Artificial Intelligence (AI) have greatly impacted cybersecurity, particularly in detecting phishing websites. Traditional methods struggle to address evolving vulnerabilities, but research shows that Machine Learning (ML ...
Phan The Duy +5 more
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