AI In Cybersecurity – The Good, Bad And Everything In-Between

Today, more data is being generated than ever. Thanks to the developments in data analytics tools, organizations in various industries are paying extra attention to big data collection and storage.

Big data combined with the increasing population of cloud storage solutions make it easier for cybercriminals to design new kinds of attacks.

As we move forward with breakthroughs in technology, hackers are equipped with better tools too.

Thus, data privacy and cybersecurity is at a risk. Tech giants have started exploring if artificial intelligence can provide better cybersecurity.

Several companies have even started early adoption of AI-based solutions for better security.

Why AI has the Potential for Cybersecurity?

Artificial Intelligence consists of building models that can analyse data and learn from it.

AI models are capable of identifying trends and patterns in data. Therefore, it can be an effective tool to spot threats and attacks.

How AI Can Help In Enhancing Cybersecurity?

Discussed below are some of the ways in which AI promises better cybersecurity.

1. Managing Vulnerabilities

Most of the companies adopted a reactive strategy where they start taking action only after a vulnerability is detected.

AI has the power to adopt proactive measures where the model can spot anomalies and alert the concerned department in advance.

2. Better Authentication

Relying on the traditional way of username and passwords for logging in to one’s account has time and again proven to be vulnerable to attacks.

Most people do not take the effort to create a strong password.

Even those who do, may store their passwords in unencrypted files to remember them.

AI-based login solutions use multiple factors to learn the login patterns of each user.

For each user, the system computes a risk analysis score based on factors like the IP address used for login, the time of login, the user’s location and so on. Therefore, these login systems are better equipped to thwart attacks.

With a large dataset, one can train and build models to recognize phishing attacks.

Artificial Intelligence can be used to detect the common sources of phishing and produce alerts in time.

3. Proactively detect threats

Threats in cybersecurity can potentially cause huge damages to any organization. To ensure that cybersecurity is not compromised, AI can help detect and manage threats quickly.

Supervised algorithms have been used to build ML models that can classify whether a particular situation is a threat or not.

However, it has been observed that purely relying on AI often results in many false positives.

Hence, cybersecurity experts recommend using a combination of traditional methods and AI-based solutions.

Limitations of implementing AI in Cybersecurity

Technology can be a double-edged sword.

On one hand, large organizations invest in R&D to reap the benefits of AI to the fullest.

On the other hand, people with malicious intent too have access to AI. If systems using supervised algorithms are hacked, the hacker can alter the classifications and group labels to their convenience.

Then, the whole purpose of implementing AI is nullified.

While it is true that AI provides multiple solutions for better cybersecurity, it comes with its own limitations.

Here are some of the limitations of implementing AI for cybersecurity.

1. Cost

AI-based solutions require systems with massive computing power and make use of data.

Small and medium enterprises cannot afford to invest in solutions that use artificial intelligence.

2. Data collection

Data forms the core of artificial intelligence-based solutions. The more the amount of data, better is the accuracy of the model that uses it.

The data must have enough number of entries of all kinds – malicious attacks included.

Currently, how many companies can afford to implement unbiased data collection techniques?

3. Hacker’s perspective

Hackers who have access to AI and the knowledge of using the right tools can build AI-resistant models before they launch their attack. In such cases, the victim is at a loss.

Companies using AI for Cybersecurity

Google implements machine learning to tag spam emails for Gmail users.

IBM’s cognitive learning platform Watson has invested in research on automating security operations using machine learning.

Summary

Overall, AI has a lot to offer for companies looking to tighten cybersecurity.

However, there are several hurdles before companies can freely start using AI-based solutions for the same.

Google and IBM have set the ball rolling, by implementing machine learning in cybersecurity.

Hopefully, several other tech companies will take the lead and continue innovating.