Related papers: PhishSigma++: Malicious Email Detection with Typed…

Phishing attacks targeting both organizations and individuals are becoming an increasingly significant threat as technology advances. Current automatic detection methods often lack explainability and robustness in detecting new phishing…

Phishing attacks represent an increasingly sophisticated and pervasive threat to individuals and organizations, causing significant financial losses, identity theft, and severe damage to institutional reputations. Existing phishing…

The escalating reliance on revolutionary online web services has introduced heightened security risks, with persistent challenges posed by phishing despite extensive security measures. Traditional phishing systems, reliant on machine…

Phishing websites remain a persistent cybersecurity threat by mimicking legitimate sites to steal sensitive user information. Existing machine learning-based detection methods often rely on supervised learning with labeled data, which not…

Phishing attacks pose a significant cybersecurity threat, evolving rapidly to bypass detection mechanisms and exploit human vulnerabilities. This paper introduces PhishKey to address the challenges of adaptability, robustness, and…

Security operations centers (SOCs) face a persistent challenge: efficiently triaging a high volume of user-reported phishing emails while maintaining robust protection against threats. This paper presents the first randomized controlled…

Phishing campaigns involve adversaries masquerading as trusted vendors trying to trigger user behavior that enables them to exfiltrate private data. While URLs are an important part of phishing campaigns, communicative elements like text…

Spear phishing is a widespread concern in the modern network security landscape, but there are few metrics that measure the extent to which reconnaissance is performed on phishing targets. Spear phishing emails closely match the…

The growth of highly advanced Large Language Models (LLMs) constitutes a huge dual-use problem, making it necessary to create dependable AI-generated text detection systems. Modern detectors are notoriously vulnerable to adversarial…

In the pursuit of an effective spam detection system, the focus has often been on identifying known spam patterns either through rule-based detection systems or machine learning (ML) solutions that rely on keywords. However, both systems…

Machine learning (ML) based approaches have been the mainstream solution for anti-phishing detection. When they are deployed on the client-side, ML-based classifiers are vulnerable to evasion attacks. However, such potential threats have…

Phishing attacks represent a significant cybersecurity threat, necessitating adaptive detection techniques. This study explores few-shot Adaptive Linguistic Prompting (ALP) in detecting phishing webpages through the multimodal capabilities…

The rapid adoption of open-source Large Language Models (LLMs) in offline and enterprise environments has introduced a largely unexamined security risk like susceptibility to adversarial phishing prompts under static safety configurations.…

Social engineering attacks delivered via email, commonly known as phishing, represent a persistent cybersecurity threat leading to significant organizational incidents and data breaches. Although many organizations train employees on…

Anticipating emerging attack methodologies is crucial for proactive cybersecurity. Recent advances in Large Language Models (LLMs) have enabled the automated generation of phishing messages and accelerated research into potential attack…

Cyber attacks such as phishing, IRS scams, etc., still are successful in fooling Internet users. Users are the last line of defense against these attacks since attackers seem to always find a way to bypass security systems. Understanding…

Large language models (LLMs) have emerged as a promising phishing detection mechanism, addressing the limitations of traditional deep learning-based detectors, including poor generalization to previously unseen websites and a lack of…

Most research into anti-phishing defence assumes that the mal-actor is attempting to harvest end-users' personally identifiable information or login credentials and, hence, focuses on detecting phishing websites. The defences for this type…

Spam and phishing remain critical threats in cybersecurity, responsible for nearly 90% of security incidents. As these attacks grow in sophistication, the need for robust defensive mechanisms intensifies. Bayesian spam filters, like the…

Text-based communication is highly favoured as a communication method, especially in business environments. As a result, it is often abused by sending malicious messages, e.g., spam emails, to deceive users into relaying personal…