Thursday Bytes | Gen AI and Its Malicious Impact on the Cyber-Physical Threat Landscape
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2 ماه پیش
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https://www.gspann.com/
Gen AI and Its Malicious Impact on the Cyber-Physical Threat Landscape
Gen AI is a revolutionary tool for creating content and improving workflows. However, it also poses significant cybersecurity threats. Malicious actors are increasingly using Gen AI to infiltrate systems that were once secure.
Key Threats Posed by Gen AI:
1️⃣ Social Engineering: Gen AI creates fake credentials, audio files, and video footage, deceiving individuals into sharing private data. Only 73% of people can detect AI-generated speech, and many cannot identify fake images.
2️⃣ Physical Attacks: 86% of industrial organizations have adopted IIoT solutions, meaning internet-connected devices control many physical systems. The FBI reports attempts to infiltrate IIoT systems using Gen AI models to override physical systems and damage essential infrastructure, potentially causing malfunctions, explosions, and fires.
3️⃣ Data Breaches: 55% of data loss protection events involve users inputting personally identifiable information into generative AI tools. This risk escalates when hackers use Gen AI models for social engineering and brute-force attacks, bypassing traditional cybersecurity measures.
4️⃣ Theft of Technology: Organizations are concerned about their Gen AI models being compromised. Internal breaches of well-known systems have demonstrated this threat. If malicious actors gain access to AI models developed by national intelligence agencies, the security implications could be severe.
Combating These Risks:
✔ Threat Detection: Gen AI models continuously analyze new information and adapt to changes in threat indicators, enabling proactive protection of core systems from sophisticated attacks. These tools autonomously review historical data to identify anomalous actions, allowing systems to counter evolving threats in real time.
✔Threat Response: By monitoring network activity for unusual behavior, Gen AI ensures immediate action to contain and neutralize attacks. This approach is crucial for organizations integrating physical and cybersecurity systems, preventing cybercriminals from infiltrating IIoT installations.
✔ Vulnerability Patch Generation: Malicious entities use Gen AI to analyze internal systems and identify exploitable vulnerabilities. Organizations can deploy their Gen AI tools to generate virtual patches automatically. These models test patches in controlled environments, ensuring fixes without disrupting operations.
✔ Enhanced Credential Security: Gen AI generates fabricated credentials for testing and optimization. AI-generated biometric data can train systems to detect fake credentials. This technique helps employees recognize AI-generated social engineering strategies.
🔗Read more on our business and technology solutions here: https://lnkd.in/dykpa5NP
#GenAI #GenerativeAI #Cybersecurity #SocialEngineering #IndustrialInternetofThings #IIoT #DataBreachDetection #ThreatDetection #ThursdayBytes #GSPANN
Gen AI and Its Malicious Impact on the Cyber-Physical Threat Landscape
Gen AI is a revolutionary tool for creating content and improving workflows. However, it also poses significant cybersecurity threats. Malicious actors are increasingly using Gen AI to infiltrate systems that were once secure.
Key Threats Posed by Gen AI:
1️⃣ Social Engineering: Gen AI creates fake credentials, audio files, and video footage, deceiving individuals into sharing private data. Only 73% of people can detect AI-generated speech, and many cannot identify fake images.
2️⃣ Physical Attacks: 86% of industrial organizations have adopted IIoT solutions, meaning internet-connected devices control many physical systems. The FBI reports attempts to infiltrate IIoT systems using Gen AI models to override physical systems and damage essential infrastructure, potentially causing malfunctions, explosions, and fires.
3️⃣ Data Breaches: 55% of data loss protection events involve users inputting personally identifiable information into generative AI tools. This risk escalates when hackers use Gen AI models for social engineering and brute-force attacks, bypassing traditional cybersecurity measures.
4️⃣ Theft of Technology: Organizations are concerned about their Gen AI models being compromised. Internal breaches of well-known systems have demonstrated this threat. If malicious actors gain access to AI models developed by national intelligence agencies, the security implications could be severe.
Combating These Risks:
✔ Threat Detection: Gen AI models continuously analyze new information and adapt to changes in threat indicators, enabling proactive protection of core systems from sophisticated attacks. These tools autonomously review historical data to identify anomalous actions, allowing systems to counter evolving threats in real time.
✔Threat Response: By monitoring network activity for unusual behavior, Gen AI ensures immediate action to contain and neutralize attacks. This approach is crucial for organizations integrating physical and cybersecurity systems, preventing cybercriminals from infiltrating IIoT installations.
✔ Vulnerability Patch Generation: Malicious entities use Gen AI to analyze internal systems and identify exploitable vulnerabilities. Organizations can deploy their Gen AI tools to generate virtual patches automatically. These models test patches in controlled environments, ensuring fixes without disrupting operations.
✔ Enhanced Credential Security: Gen AI generates fabricated credentials for testing and optimization. AI-generated biometric data can train systems to detect fake credentials. This technique helps employees recognize AI-generated social engineering strategies.
🔗Read more on our business and technology solutions here: https://lnkd.in/dykpa5NP
#GenAI #GenerativeAI #Cybersecurity #SocialEngineering #IndustrialInternetofThings #IIoT #DataBreachDetection #ThreatDetection #ThursdayBytes #GSPANN
2 ماه پیش
در تاریخ 1403/04/13 منتشر شده
است.
31
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