Headlines
The legal frameworks and regulations established to oversee the advancement and application of artificial intelligence technology are known as AI regulations.
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.
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.
AI in cybersecurity provides large-scale data analysis, automated response, and real-time threat identification to reduce risks more quickly than with conventional methods.
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.
When it comes to digital computer forensic, mobile forensic, and cloud forensic investigations, artificial intelligence (AI) is particularly effective at sorting through vast volumes of evidence and identifying pertinent information via automated searches of photos, videos, language, and audio files.
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.