The conference invites submissions on a broad range of topics related to the employment of NLP and AI (and in general, language studies and models) for Cyber Security including but not limited to:

Societal and Human Security and Safety

• Detection and mitigation of hate speech and offensive language
• Fake news, deepfakes, misinformation and disinformation
• Detection of machine generated language in multimodal context (text, speech and gesture)

• Cyberbullying and identification of internet offenders
• Monitoring extremist fora
•  Suicide prevention

• Social engineering identification, phishing detection
• NLP for risk assessment
• Controlled languages for safe messages
• Prevention of malicious use of ai models
• Forensic linguistics

• Voice-based security: Analysis of voice recordings or transcripts for security threats
• Detection of machine generated language in multimodal context (text, speech and gesture)
• NLP and biometrics in multimodal context

• Cryptography
• Digital forensics
• Malware detection, obfuscation
• Models for documentation
• NLP for data privacy and leakage prevention (DLP)
• Addressing dataset “poisoning” attacks

• Natural language understanding for chatbots: NLP-powered chatbots for user support and security incident reporting
• User behaviour analysis: Analysing user-generated text data (e.g., chat logs and emails) to detect insider threats or unusual behaviour
• Human supervision of technology for Cyber Security

Anomaly Detection and Threat Intelligence

• Identification of unusual or suspicious patterns in logs, incident reports or other textual data
• Detecting deviations from normal behaviour in system logs or network traffic

• Cryptography
• Digital forensics
• Malware detection, obfuscation
• Models for documentation
• NLP for data privacy and leakage prevention (DLP)
• Addressing dataset “poisoning” attacks

Systems and Infrastructure Security

• Anti-reverse engineering for protecting privacy and anonymity
• Identification and mitigation of side-channel attacks
• Authentication and access control
• Enterprise-level mitigation
• NLP for software vulnerability detection

• Analysing code and scripts for malware
• Detection using NLP to identify patterns indicative of malicious code

Ethics, Bias, and Legislation in Cyber Security

• Digital privacy and identity management
• The ethics of NLP and speech technology
• Explainability of NLP and speech technology tools
• Legislation against malicious use of AI
• Regulatory issues

• Financial Fraud Detection
• Algorithmic Trading Security
• Secure Online Banking
• Risk Management in Finance
• Financial Text Analytics

• Bias in Large Language Models (LLMs)
• Bias in security related datasets and annotations

• Intelligence applications
• Emerging and innovative applications in Cyber Security