Cybersecurity and artificial intelligence (AI) are working together. It reaps many benefits for companies to keep threats at bay.
AI and machine learning is one way to help boost cybersecurity. Along with big data, the cloud, blockchain, and more.
Yes, there are many perks to using AI. But there are also drawbacks. So, let us see what both sides of the coin look like.
Read on to know more.
Cybersecurity and Artificial Intelligence: The Perks
Threat Hunting
Traditional security techniques use signatures of compromise to find threats. Yet this is only 90% effective.
But using AI instead of it can raise the detection rate to 95%. But this can result in many false positives.
So, to get a 100% detection rate, it is best to combine both. Also, you can better the threat hunting process. Because AI can use behavioral analysis.
Network Security
Traditional network security has two aspects. Making security policies and knowing the network topography of your company.
But these two can be time-consuming. So, using AI with it can save you time. How? By learning your network traffic patterns.
Then, it can suggest the grouping of workloads and security policy.
Data Centers
AI can keep track of many vital data center processes. Like:
- backup power
- cooling filters
- power usage
- internal temperature
- bandwidth usage
So, it can give you valuable insights. Then, you can use these to improve your security to keep your vital data safe.
Also, it can save you a lot of money. How? By letting you know if there are any hardware maintenance you need to do before it breaks down.
Cybersecurity and Artificial Intelligence: The Drawbacks
Resources
If you want to use AI, you need to set aside a budget. And it means investing a lot of resources like:
- money
- time
- computing power
- memory
- data
Data Sets
AI model, in order to work as it should, needs to learn from data sets. So, your security teams may need to get as many data sets as they can.
These may be about:
- malicious codes
- malware codes
- anomalies
But it can be hard to get your hands on accurate ones.
Hackers Also Use AI
One thing to be wary of is hackers also use AI to attack. They test and train their malware so that it can be resistant to AI-based security tools.
Also, hackers learn from existing AI tools today. Then, they make more advanced attacks that are harder to fend off.
As a result, they can target both traditional security systems. As well as AI-boosted ones.
Neural Fuzzing
What is neural fuzzing? It means testing large amounts of random input data within the software. And it aims to find any weak spots.
Fuzzing drives AI to test large amounts of random input data faster. But this has another side.
Hackers can find out the weaknesses. How? By getting information with the power of neural networks. Then, they will exploit these weaknesses.
Conclusion
So, these are the two sides of AI when it comes to cybersecurity. What do you think? Can the perks outweigh the drawbacks?
