AI in Cybersecurity: The Future of Hacking is Here

Identity and access management (IAM) today is much more complicated than in the early days of the internet.

For starters, we have a plethora of account types: "user," "guest," "admin" and "service" accounts with associated passwords requiring regular managed changes to protect a variety of systems. Password creation has also become much more complicated: You need a minimum of eight characters, one uppercase, one lowercase, numbers and special characters. Plus, personal identification numbers (PINs), two-factor authentication (2FA), multi-factor authentication (MFA), biometrics, soft and hard tokens, card readers, proximity sensors and photo ID form parts of our individual access and identification profiles.

With all these tools in place to manage who gets access to what data and under which circumstances, cyberattacks must be a thing of the past. Right?

Wrong. (Also read: The Cyberattacks Pandemic: A Look At Cybercrime in the COVID-19 Era.)

Cybercriminals' methods have evolved alongside changes to cybersecurity standards -- and they're now using artificial intelligence (AI) and machine learning (ML) to hack into your accounts.

Here's how, and what you can do to prevent it:

How AI Can Compromise Cybersecurity

Even the most sophisticated hacking tools need human-like intelligence to direct them against potential victims. That's where AI comes in.

Using AI, cybercriminals can remain dormant and undetected within a company's network for extended periods, during which time they can set up back doors to an organization's critical infrastructure. Then, once ready to launch an attack against the wider business, they can eavesdrop on meetings, extract data, spread malicious software, create privileged accounts to access other systems and/or install ransomware.

AI is a particularly effective tool for cybercriminals because of its ability to learn and anticipate what's happening now and what might happen in the future.

Some key methods cybercriminals use to hack into companies' networks with AI include:

• Creating deepfake data.
• Building better malware.
• Stealth attacks.
• AI-supported password-guessing and CAPTCHA-cracking.
• Generative Adversarial Networks (GANs).
• Human impersonation on social networking platforms.
• Weaponizing AI frameworks for hacking vulnerable hosts.
• Deep exploits.
• ML-enabled penetration testing tools.

According to Malwarebytes, there has been a recent surge in cyberattacks where hackers use AI and ML to hide behind an organization's website or infrastructure. So, to remain secure and stay in business, companies must fight fire with fire and adopt AI & ML to keep their networks safe. (Also read: Is artificial intelligence a tool or a threat to cybersecurity?)

How AI Can Strengthen Cybersecurity

The global market for AI cybersecurity technologies is predicted to grow at a compound growth rate of 23.6% through 2027, when it's forecasted to reach $46.3 billion, according to Mimecast.

AI- and ML-powered systems, such as security event management (SEM), security information management (SIM) and security information and event management (SIEM), allow security teams to detect threats faster and respond to incidents quicker. When the AI detects malicious activity on a particular IP or endpoint, it can automatically and instantly block the user from file access. (Also read: What’s the difference between SEM, SIM, and SIEM?)

Here are some major ways companies can use AI to defend against cyberattack:

• Threat and anomaly detection.
• Identity analytics and fraud detection.
• Compliance and privacy risk management.
• Bot mitigation.
• Data discovery and categorization.
• Breach and attack simulation asset discovery.
• Policy automation. (Also read: Robotic Process Automation: What You Need to Know.)
• Security orchestration.
• Behavioral analytics.

While AI can be a powerful tool to strengthen cybersecurity initiatives, it's not a replacement for traditional security approaches. In fact, it works best when used alongside traditional methods: Pairing AI with authentication, biometric technology and/or MFA can improve an organization's defences. One example of this could be implementing password managers: they provide automation to create, update and advise on the strength of chosen passwords.

Mixing AI with sound, well-thought-out cybersecurity practices and security-by-design methodologies like zero trust is the best way to bolster your organization's cybersecurity toolkit.

Conclusion

AI and ML are powerful tools and they're changing how businesses do everything -- including managing network security. As such, security and risk management professionals need to understand the evolving state of, and best practices for, leveraging them to improve IAM architecture. (Also read: Artificial Intelligence in Cybersecurity.)