Cybersecurity is a major battleground of the 21st century for governments and corporations alike. Malicious parties routinely attempt to gain access to sensitive information stored by companies in bids to commit fraud. More serious attacks include attempts to take control of critical infrastructure, either for sabotage or to extort money.
We examine how AI is increasingly being used to improve cybersecurity systems.
How does artificial intelligence benefit cybersecurity systems?
Artificial intelligence (AI) has one major benefit over traditional security practices – it can do more, and faster. AI can examine enormous datasets and identify patterns of malicious behavior that allow it to respond instantly to suspicious activity. Its ability to notice trends means that it can keep up with the constant development of new malware.
Hackers are constantly developing new ways to exploit aging defenses, which is why spotting trends is so important. Swift identification doesn’t just foil one attack, it can inform industry-wide best practices for defending against that type of attack. Conventional software requires a lot more manual work to adapt and cover its vulnerabilities, which is often too slow to keep up with malware development.
AI is also extremely useful in identifying and controlling bots. Most users on the internet are bots, and while not all bots are malicious, they are a favorite tool for hackers. AI can identify key differences in the behavior of regular internet users, harmless bot traffic, and malicious bots that are attempting to access sensitive data. As the behavior and diversity of bots continue to develop extremely quickly, AI is necessary to identify and manage bot behavior in critical areas.
How do hackers take advantage of weaknesses in AI systems?
The enduring problem of conflict is that it’s very easy to defeat your enemy unless your enemy defeats you first. The issue is the same in cybersecurity: AI is an extremely effective way of identifying malicious behavior, but it’s also a great way of identifying vulnerabilities in security systems. In other words, the hackers are using machine learning as well.
Hackers are heavily invested in understanding the best cybersecurity practices. This includes understanding how AI works to prevent interference. Understanding how AI combats malware means that malicious parties can then use AI to determine the weaknesses of defensive artificial intelligence.
Artificial intelligence systems learn through datasets, which means that one potential line of attack is to corrupt these datasets. Poor data leads to ineffective results from machine learning systems. Protecting these resources becomes as important as protecting any other infrastructure.
Addressing malicious hackers using AI
Key next steps of using machine learning in cybersecurity include:
- Reducing the cost of machine learning compared to traditional defense software
- Creating more effective and secure datasets
- Reducing the time investment needed to teach an AI
- More research into how these systems can be weaponized and taught to interfere
Understanding the machine learning arms race
Most cybersecurity professionals agree that machine learning is the future. However, important developments need to be kept in the right hands and more needs to be done to learn how hackers are also using AI to achieve their ends. With so much progress to be made in our understanding of machine learning, it’s hard to predict what will come next.
