Dark AI is enhancing cyber attacks, making existing defenses obsolete. Preemptive Cybersecurity, powered by deep learning, is crucial for identifying and stopping unknown threats in real-time across entire data estates. This approach empowers SOC teams and scales with modern enterprises. (Affected: cybersecurity sector, enterprises, government)
Keypoints :
- Dark AI accelerates attack sophistication, bypassing traditional signature-based defenses.
- Gartner predicts Preemptive Cybersecurity to be essential by the early 2030s.
- Preemptive Data Security focuses on identifying unknown and zero-day threats via behavior, not signatures.
- Real-time prevention quarantines malicious files before execution, ensuring seamless protection.
- Solutions must provide rapid insights and explainability to aid SOC teams in understanding attack motives.
- Systems must scale efficiently across growing data estates and diverse endpoints without bottlenecks.
- Defense must cover the entire data estate, including endpoints, cloud, applications, and storage.
- Purpose-built deep learning frameworks outperform traditional ML in threat detection accuracy and speed.
- Deep learning enables autonomous threat identification and continuous adaptation to new attack methods.
- Deep Instinct’s DSX Brain is a unique deep learning cybersecurity framework addressing current and future needs.
MITRE Techniques :
- Initial Access (T1078) – Dark AI automates creating and permuting malware to evade signature-based defenses.
- Execution (T1204) – Preemptive solutions prevent execution of zero-day malware by real-time quarantining.
- Defense Evasion (T1562) – Deep learning detects obfuscation techniques used by AI-generated malware.
- Discovery (T1083) – Real-time insights provide detailed analysis of malware behavior and capabilities.
- Impact (T1499) – Protecting entire data estates mitigates ransomware or data destruction attacks.
- Collection (T1114) – Continuous scanning of data assets prevents unauthorized collection by malicious actors.
Indicator of Compromise :
- The article includes behavioral traits of unknown or zero-day malware files as indirect IOCs for early detection.
- Examples of IOCs would be rapid mutation and obfuscation patterns unique to Dark AI-generated malware.
- Hash values of newly detected malicious files could serve as specific IOCs within preemptive solutions.
- Network indicators might include connections to newly identified C2 servers used by AI-driven threats.
Read more: https://www.deepinstinct.com/blog/the-future-has-arrived-defining-preemptive-data-security
Views: 28