Results 51 to 60 of about 7,019 (217)
Intelligent Ensemble Learning Approach for Phishing Website Detection Based on Weighted Soft Voting
The continuous development of network technologies plays a major role in increasing the utilization of these technologies in many aspects of our lives, including e-commerce, electronic banking, social media, e-health, and e-learning.
Altyeb Taha
doaj +1 more source
DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection
Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +1 more source
Abstract We investigate how the affordances of an online context shape the processes of social learning. Using a dataset of more than 11,000 posts from the fraud subdread on the dark web forum Dread, we examine how affordances of platform governance, connectivity, anonymity, invisibility, asynchronicity, and limited oversight influence the components ...
Fangzhou Wang, Timothy Dickinson
wiley +1 more source
“I Paid A Bribe”—Lessons and Insights From Crowdsourced Corruption Reporting in India
ABSTRACT Preventing and reducing corruption has proven to be an enormous challenge. An important step in this process is to produce and use good metrics to identify where anti‐corruption resources would be most beneficial. Most measures of corruption, however, rely on surveys of perceptions or bribery incidence.
Ina Kubbe +2 more
wiley +1 more source
Web phishing detection techniques: a survey on the state‐of‐the‐art, taxonomy and future directions
Internet dragged more than half of the world's population into the cyber world. Unfortunately, with the increase in internet transactions, cybercrimes also increase rapidly.
M. Vijayalakshmi +3 more
doaj +1 more source
Over the last few years, web phishing attacks have been constantly evolving causing customers to lose trust in e-commerce and online services. Various tools and systems based on a blacklist of phishing websites are applied to detect the phishing websites.
Waleed Ali, Sharaf Malebary
doaj +1 more source
Enhancing Phishing Email Detection through Ensemble Learning and Undersampling
In real-world scenarios, the number of phishing and benign emails is usually imbalanced, leading to traditional machine learning or deep learning algorithms being biased towards benign emails and misclassifying phishing emails.
Qinglin Qi +4 more
doaj +1 more source
It is a crime to practice phishing by employing technical tricks and social engineering to exploit the innocence of unaware users. This methodology usually covers up a trustworthy entity so as to influence a consumer to execute an action if asked by the imitated entity.
null Mr. Tahir Naquash H B +4 more
openaire +1 more source
Personalized Model‐Driven Interventions for Decisions From Experience
Abstract Cognitive models that represent individuals provide many benefits for understanding the full range of human behavior. One way in which individual differences emerge is through differences in knowledge. In dynamic situations, where decisions are made from experience, models built upon a theory of experiential choice (instance‐based learning ...
Edward A. Cranford +6 more
wiley +1 more source
Knowledge Expansion and Counterfactual Interaction for Reference-Based Phishing Detection
Phishing attacks have been increasingly prevalent in recent years, significantly eroding societal trust. As a state-of-the-art defense solution, reference-based phishing detection excels in terms of accuracy, timeliness, and explainability.
Dong, JS +4 more
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