6 Downsides of Using Artificial Intelligence in Cybersecurity

Artificial intelligence (AI) made a grand entrance into cyberspace with a promise to enhance how people interact with data. More so, it raises hopes of providing a stronger cybersecurity framework.

Several years down the line, people are yet to get the most out of AI technology in cybersecurity. In some instances, it complicates data management and raises some security concerns.

The Growing Popularity of AI in Cybersecurity

Artificial intelligence hardly goes unmentioned in discussions about cybersecurity. Tech enthusiasts are excited about its prospects of securing digital assets amid increasing cyberattacks.

There’s a cyberattack every other day. As victims of such attacks count their losses, other people are on their toes trying to secure their digital gates so as not to be the next victim.

Developers of AI technology are optimistic that it’ll enhance defensive cybersecurity. If you have either suffered a cyberattack or been exposed to one, this will sound like music to your ears. They argue that there’s only so much human-controlled cybersecurity systems can do in safeguarding your network because human errors are inevitable.

AI leverages machine learning to master certain defensive behaviors by observing and monitoring big data. It can detect suspected cyber threats from miles away and launch strong defenses automatically.

AI technology generates and processes data that you can analyze to better understand attack vectors. By paying close attention to the recurring patterns of data breaches and hacks, security experts can further enhance the defense mechanisms of AI technologies.

6 Cons of AI in Cybersecurity

Many argue that AI isn’t exactly the Messiah in cybersecurity as its believers are making it seem. There’s so much focus on the benefits of AI with little or nothing being said about its downsides. Such a bias raises cybersecurity concerns because it takes us back to square one—creating loopholes for cyberattacks.

The cons of AI technology in cybersecurity include the following:

1. Reliance on Big Data

Mastering data patterns is one of the functions of AI technology, and it does that with big data analytics. If you take big data out of the picture, the accuracy of AI becomes questionable.

If you want AI technology to be able to detect cyber threats, predict attacks and respond to them accordingly, you must train it with tons of data via machine learning. For big organizations, this might not be a problem as they deal with big data. But what about the average Joe who’s just trying to protect his network from intrusion?

AI enthusiasts create the impression that the technology is all-encompassing, but that’s not the case, as it can’t be used by people who don’t deal with big data.

2. Third-Party Data Exposure

In protecting data privacy, the fewer people handling the data, the better. Creating the infrastructure for implementing AI in cybersecurity is neither easy nor cheap. It requires high technical skills that are synonymous with tech experts.

You may not be able to manage the AI technology yourself and will have to outsource it to third-party vendors. While the vendors managing your cybersecurity with AI technology may assure you of their confidentiality, the fact is, you can’t take their word for it. They may use your data for their own interests, outside your arrangements with them.

3. A Target for Hackers

Cybercriminals make it a priority to keep up with trends in cybersecurity. With AI generating so much buzz in securing digital assets, they are working around the clock to be on top of it. While you are busy trying to enhance your security defenses with the latest algorithm, chances are that cybercriminals have already found loopholes in the algorithm.

No one has a monopoly of skills in AI in cybersecurity. There’s a power tussle between the intruders and gatekeepers. If hackers don’t beat you to it, they’ll be out of business—so they go the extra mile to stay ahead of the game.

4. Inadequate AI Cybersecurity Knowledge

Having a good cybersecurity structure isn’t necessarily about deploying the latest technology but understanding the technicalities of the technology and utilizing it efficiently. Unless you are a cyber professional, you may not have the knowledge and skills to use AI technology thoroughly. Your best bet is to outsource the job to specialized vendors.

Even when you employ the services of AI professionals to manage your cybersecurity, you won’t get the best results if you don’t have significant knowledge of the algorithm and how it works. The models your vendor is using might not be suitable for your network, but you wouldn’t know this if you lacked the necessary skills.

5. No Room for Creativity and Spontaneity

There’s no one-size-fits-all approach to cybersecurity. Sometimes, the defense mechanism you have on the ground might be inadequate to prevent an attack. If you can figure out malicious activities on time, you could apply a spontaneous strategy to manage that specific attack.

Cyber professionals have the expertise to contain cyberattacks in real-time. As humans, they can respond to unique circumstances with their creativity and initiative—something that AI technology lacks since it operates by learning behaviors over continuous training.

When malicious activities that the AI algorithm isn’t familiar with arise, it won’t be able to secure your system because it lacks the sixth sense of humans to improvise.

6. Unrealistic Expectations

The hype about AI technology in cybersecurity builds up unrealistic expectations in people. It seems like, with AI, there’s no cause to worry about cyberattacks. But that’s a flawed promise because AI technology is far from perfect.

Designed by people, an AI security system could have loopholes that may go unnoticed due to the utmost confidence people have in it. AI doesn’t offer a magic solution to your cybersecurity needs. Instead, its algorithm can give you the data you need to make better decisions and analytics. You must understand how AI technology adds value to your cybersecurity and how you can actualize that value.

Creating a Balance in Your Cybersecurity With AI

Some people argue that the inadequacies of AI technology are due to a misplacement of priorities by users who are looking for an easy way out. To get the most out of it, you must cultivate an insight-driven approach to your cybersecurity.

Pay attention to the reports your AI algorithm generates for you and take informed decisions toward enhancing your security. In the long run, the effectiveness of your cybersecurity is in your hands.

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Chris Odogwu