Identity and access management (IAM) is much more complicated today than it was 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 that require regularly managed changes to protect a variety of systems. Password creation has also become much more complicated: you need at least eight characters, one capital letter, one lower-case letter, numbers and special characters. In addition, personal identification numbers (PINs), two-factor authentication (2FA), multi-factor authentication (MFA), biometrics, soft and hard tokens, card readers, proximity sensors and photo IDs are part of our individual access and identification profiles.
With all these tools to manage who gets access to what data under what circumstances, cyberattacks must be a thing of the past. Right?
Not correct. (Also read: The Cyberattack Pandemic: A Look at Cybercrime in the COVID-19 Era.)
Cybercriminals’ methods have evolved along with changes in cybersecurity standards – and they are now using artificial intelligence (AI) and machine learning (ML) to hack into your accounts.
Here’s how and what you can do about it:
How AI can jeopardize cybersecurity
Even the most sophisticated hacking tools require human-like intelligence to turn on potential victims. This is where AI comes in.
Using AI, cybercriminals can remain dormant and undetected on an organization’s network for extended periods of time, during which time they can set up backdoors into an organization’s critical infrastructure. Once ready to launch an attack on the broader enterprise, they can eavesdrop on meetings, extract data, distribute malicious software, create privileged accounts to access other systems, and/or install ransomware.
AI is a particularly effective tool for cybercriminals because it can learn and anticipate what’s happening now and what might happen in the future.
The top ways cybercriminals use AI to hack into corporate networks include:
According to Malwarebytes, there has recently been a surge in cyberattacks where hackers use AI and ML to hide behind an organization’s website or infrastructure. So, to stay safe and stay in business, companies must fight fire with fire and use AI and ML to protect their networks. (Also read: Is artificial intelligence a tool or a cybersecurity threat?)
How AI can strengthen cybersecurity
According to Mimecast, the global market for AI cybersecurity technologies is expected to grow by 23.6% by 2027 and then reach US$46.3 billion.
AI and ML-powered systems like Security Event Management (SEM), Security Information Management (SIM), and Security Information and Event Management (SIEM) enable security teams to detect threats faster and respond to incidents faster. If the AI detects malicious activity on a specific IP or endpoint, it can automatically and instantly ban the user from file access. (Also read: What is the difference between SEM, SIM and SIEM?)
Here are some key ways organizations can use AI to defend against cyberattacks:
While AI can be a powerful tool to strengthen cybersecurity initiatives, it is not a substitute for traditional security approaches. In fact, it works best when used alongside traditional methods: combining AI with authentication, biometric technology, and/or MFA can improve an organization’s defenses. An example of this could be the implementation of password managers: they provide automation for creating, updating and advising on the strength of selected passwords.
Combining AI with solid, well thought out cybersecurity practices and security-by-design methodologies like Zero Trust is the best way to strengthen your organization’s cybersecurity toolkit.
AI and ML are powerful tools and are changing the way businesses do everything – including managing network security. As such, security and risk management professionals need to understand the evolving state and best practices for leveraging them to improve the IAM architecture. (Also read: Artificial Intelligence in Cyber Security.)