Headlines
AI threat detection uses automation, behavioral analytics, and machine learning to instantly detect cyber threats.The use of AI technologies, including as machine learning models, large language models (LLMs), and natural language processing (NLP), to augment and expedite up threat identification, investigation, and mitigation in real time is known as AI-driven threat detection and response.
Agentic AI is an artificial intelligence system that uses machine learning models called AI agents to solve issues in real time by simulating human decision-making.Powered by advanced foundation models and multimodal generative AI, these autonomous AI systems combine thinking, memory, and decision-making.
Zero-day attacks exploit unknown vulnerabilities in firmware, hardware, or software before developers have a chance to build a fix.In order to identify and prevent zero-day attacks before they have a chance to do serious harm, artificial intelligence (AI) offers a proactive and flexible method.
Web applications are protected from cyberattacks by AI-powered web application firewalls (WAFs) security solution.AI-WAF analyzes incoming web traffic, detects potential threats, and takes proactive steps to prevent them using cutting-edge machine learning algorithms and AI techniques.
Phishing scams powered by AI are getting more sophisticated, faster, and more challenging to detect than in the past. With the objective of tricking users into disclosing vital information, cybercriminals are already using AI tools to generate convincing emails, clone websites, imitate human behavior, and even create realistic voices.
Businesses and organizations can use AI to combat advanced phishing, ransomware, and business email compromise (BEC) operations which are much more effective then traditional defences.
Malware that is created, altered, controlled, or enhanced with AI is referred to as AI-powered malware. The AI layer could be used to develop code, choose targets, change behavior, avoid detection, or automate chores for attackers.
Behavioral biometrics use physical activity and behavior analysis to help detect and prevent fraud.Behavioral biometrics analyzes distinct patterns in consumers’ interactions with technology, such as walking patterns, touchscreen pressure, mouse movements, and typing rhythm.
Phishing, malware, and BEC threats are prevented by AI-powered email protection before they reach users’ inboxes or AI-driven workflows.
A fundamental concept in artificial intelligence, AI Fairness seeks to ensure fair and just results for people or groups, regardless of their varied characteristics.