Data Security

How Artificial Intelligence Can Enhance Cybersecurity

February 15, 2024

How Artificial Intelligence Can Enhance Cybersecurity

Introduction

Cybersecurity is more important than ever as cyber threats continue to evolve. Artificial intelligence (AI) offers promising solutions to detect, defend against, and respond to cyber attacks. In this article, I will explore how AI can enhance cybersecurity across several key areas.

AI-Powered Threat Detection

AI can analyze massive amounts of network data to detect anomalies and identify threats.

Machine learning algorithms can be trained to recognize normal network activity and alert on deviations that may signal cyber attacks. As the algorithms process more data over time, they continuously improve threat detection accuracy.
AI techniques like natural language processing can analyze large volumes of log data to identify signs of compromise written in human language. This allows detecting threats that produce no obvious anomalies in network traffic.
By processing inputs from diverse sensors and threat intelligence feeds, AI correlation engines can connect the dots between seemingly unrelated anomalies to uncover sophisticated multi-stage attacks.
Deep learning algorithms can be trained on malicious code samples to detect new malware and zero-day exploits based on similar code features and behaviors.

Automating Threat Hunting and Investigation

AI automation augments human analysts to hunt for advanced threats missed by preventative controls.

User and entity behavior analytics (UEBA) apply AI algorithms to detect changes in normal behavior that may signify insider threats and account compromises. UEBA solutions can automatically investigate and prioritize anomalies for human review.
AI techniques can analyze system memory, suspicious files, and malware code to extract indicators of compromise and uncover attacker tactics, techniques and procedures. This automates time-consuming malware analysis.
By continually cross-referencing new evidence with historical network activity, AI can identify related anomalies to uncover all traces of an attack. This allows efficient scoping of complex threats.

AI-Powered Response and Remediation

Once threats are detected, AI can assist humans in containing attacks and restoring systems.

Security orchestration, automation and response (SOAR) platforms utilize AI to automatically execute playbooks of security policies and remediation actions in response to threats. Humans define the playbooks, while the AI automates rapid response at machine speeds.
AI agents can be deployed in compromised networks to quickly gather forensic evidence for humans to contain and eradicate threats. The agents autonomously cover more attack surface than human analysts.
AI techniques called generative adversarial networks (GANs) can automatically synthesize fake system configurations, files and data. Deploying these fakes as traps and lures provides added deception to detect adversaries and divert them from real assets.

Conclusion

The rapid evolution of cyber threats requires automation that only AI can provide. By applying AI across key use cases like threat detection, investigation, and response, organizations can enhance their cyber defenses and create a more resilient security posture. However, AI is not a magic bullet; it requires careful oversight and integration into existing processes and controls driven by cybersecurity professionals. AI and humans have complementary strengths in enhancing cybersecurity.