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.
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.
A next-generation firewall (NGFW) and artificial intelligence (AI) are integrated in an AI-powered firewall.AI-powered firewalls use machine learning algorithms and real-time monitoring to analyze network traffic and identify possible security vulnerabilities before any cyber attack.
Artificial intelligence-powered distributed denial of service attacks are known as AI powered Denial of Service (DDoS). DDoS attacks that are more accurate, flexible, and readily accessible by using automation and machine learning.
The Internet of Things (IoT) is a network of physical devices that have sensors, software, and communication technologies incorporated in them.
The use of AI technologies, such as generative AI (GenAI), to facilitate or expedite cyberattacks is known as “Dark AI.”Attackers develop or use dark AI to take advantage of weaknesses, automate attacks.
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.