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Automated hacking and malware

Posted: Sun Dec 15, 2024 5:20 am
by jakaria25
Machine learning algorithms are continually improving at identifying and exploiting vulnerabilities faster than traditional hacking methods. AI-enabled ransomware can now identify and encrypt the most critical files first, spreading autonomously across a network and making it difficult for traditional defenses to stop.

In automated credential stuffing attacks, AI-powered bots can automatically test combinations of leaked usernames and passwords at an unprecedented rate. Machine learning algorithms how to build phone number list optimize these attacks by learning from past attempts, increasing the likelihood of gaining unauthorized access to accounts.

Another example is AI-powered botnets, which use machine learning algorithms to identify and exploit Internet of Things (IoT) devices that are vulnerable due to weak security protocols. They can also be used to spread misinformation on social media networks.

Fight AI with AI
Fortunately for security officials, AI also powers tools that can detect subtle network anomalies and suspicious activity that might go unnoticed by traditional security tools. AI can also aggregate and analyze threat data from multiple sources, helping to speed up coordination and communication between public- and private-sector partners.

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Governments can implement automated response systems powered by AI to quickly neutralize cyber threats before they escalate. These systems use machine learning to assess the severity of an attack, isolate compromised systems and trigger countermeasures like blocking malicious traffic or disabling compromised accounts. AI-powered automation reduces the time between detection and response, which is crucial in mitigating the damage caused by cyber incidents. Government organizations can use the below strategies to counteract AI-powered cyber threats.