AI is something that we know all about because it can help us improve cybersecurity in Miami for our clients. Artificial intelligence is able to:
- Scan for threats
- Learn from attacks
- Adjust security measures to stop attacks
However, there is also a dark side to AI: cyberattacks. Hackers are always one step ahead with the tools and dedication to infiltrate networks, businesses and even IoT devices.
AI Hacking and How It’s Transforming Cyberattacks
Machine learning and AI can be used for both good and nefarious purposes. Hackers are using both AI and machine learning to help with:
- Testing their malware
- Understanding AI flaws
- Sneaking past detection
If AI tools are being used for security, you can be sure that a hacker is analyzing the behaviors of these tools for any sign of weakness that they can find. Once a weakness is found, the tools will continue trying to exploit them.
Machine learning is still algorithmic, meaning that the AI looks for certain techniques, tactics and procedures to identify malware or an attack.
Hackers who understand what the security tools are flagging as suspicious behavior can then adjust their malware to circumvent security measures.
AI Poisoning
Engaging in AI poisoning is becoming more popular among hackers who attempt to trick AI detection tools. Machine learning requires a massive amount of input to label and understand a potential attack.
Training takes place for all AI systems, and if attackers can introduce new files that transform data into information that alters detection, the hacker can then poison the AI and use its new weaknesses against it.
AI Attacks Remain a Threat
Governments echo the sentiment that AI hacking remains a critical threat to governments and businesses worldwide. Infrastructure, IoT devices and more are at risk, as hackers use AI tools to create sporadic, new threats that are unknown and pose the biggest risk in the cybersecurity industry.
While AI is being trained to scan networks and gather data rapidly, it is also being used by hackers to find network or device weaknesses.
API hacking is a prime example of this in practice. AI tools can identify device weaknesses, as they did in Moscow, which sent ride-hailing vehicles all to one location. Traffic was backed up for hours, and the issue is expected to impact IoT devices that use APIs, too.
AI is just another tool in a hacker’s arsenal to identify weaknesses that they can exploit to gain access to networks or data that is meant to be secure. Security experts must be prepared to react to quicker, more sophisticated attacks that use AI and machine learning to sidestep security measures.
Cybersecurity will remain one of the fastest-growing investments for businesses for the foreseeable future. A lot is changing as AI is released to users worldwide, and the introduction of artificial intelligence means that the same security measures of the past will not be as effective today.
Adjusting your systems to counteract attacks and strengthen your network is one of the first steps to reducing your risk of being a cyberattack victim.