Latest Articles for Online Safety

Examining how evolving language affects models detecting online abuse.

A new framework enhances detection of harmful online language through continuous learning.

An overview of user awareness and experiences with safety technologies on social media.

AI-generated images fuel the rise of deceptive social media accounts.

Phishing tactics are evolving with AI, posing new risks for organizations.

Exploring the challenges and strategies for moderating hate speech online.

A look at deception online and how to detect it effectively.

Examining the challenges LGBTQ+ youth face on social media platforms.

A new method enhances detection of hateful content in memes.

A new framework enhances hate speech detection by generating realistic test cases.

Examining content moderation's role in online mental health communities.

Examining how users perceive fairness in moderation decisions on platforms.

This article discusses how language models help identify hate speech.

A study on the impact and identification of hateful memes in the Bengali language.

This study tackles user-intended attacks on offensive language in Korean social media.

New evaluation methods aim to improve detection of harmful content online.

This article explores how users perceive adversarial phishing sites and ways to improve detection.

Enhancing tools to detect harmful language in online spaces is crucial for safety.

SGHateCheck focuses on local languages to tackle online hate speech effectively.

A new framework that protects online identities while preserving message clarity.

New research reveals gaps in detecting transient domains used for online abuse.

Examining the impact and spread of malicious information on social platforms.

Examining the impact of nudges on password change behavior after data breaches.

Research reveals harmful content exposure for Amharic speakers on YouTube.

A new approach using conversational agents for safer discussions on WhatsApp.

A new framework improves detecting harmful language in online spaces.

An analysis of how online services handle children's data privacy.

LLMs assist human raters in effectively identifying harmful online content.

LionGuard enhances content safety by focusing on Singapore's unique language context.

Addressing the challenges of E2EE and account recovery methods.

This paper introduces Demarcation to tackle online abusive speech effectively.

A new dataset aims to improve hate speech detection in Indonesia.

A study assessing the quality of datasets for identifying hate speech online.

A new method improves identification of hate speech in Arabic social media.

A new method promotes fairness in identifying targeted toxic language across demographic groups.

A new model improves password guessing and strength assessment.

Learn to detect and prevent brute-force attacks through practical training scenarios.

A study on the effectiveness of offensive language detection systems and datasets.

PhishLang offers improved detection for phishing websites using advanced analysis techniques.

A new system targets hate speech in memes effectively.