Spare run
Modern cyber threats are no longer confined to simple viruses or malware. The contemporary threat landscape encompasses a wide array of challenges, such as advanced persistent threats (APTs), ransomware attacks, zero-day exploits, and phishing scams.
The Growing Complexity of Cyber Threats
Traditional signature-based detection methods are reactive and struggle to identify previously unseen threats. Machine learning algorithms can analyze vast datasets to identify anomalies, recognize patterns, and establish a baseline of normal behavior.
Modern malware is often polymorphic, altering its code to evade detection. Machine learning algorithms can analyze code and behavior patterns to identify malware variants, even if they have never been encountered before.
ML-powered systems can respond to threats in real time. For example, if a system detects unauthorized access, it can immediately take action to block the intruder and prevent further damage.
Real-time Response: AI in Cybersecurity