AI in cyber security: Pros and cons

ARTIFICIAL Intelligence (AI) has been making waves in virtually every industry, and cyber security is no exception.

Several companies are adopting the technology into different business functions, such as logistics and IT.

But as AI quickly leaks into the business landscape, it’s also been the subject of criticism.

Recently, news reports have revealed that three quarters of global businesses are considering or have already implemented a ban on using ChatGPT and other AI applications within the workplace.

This decision is owing to recognised risks they pose on cyber security and data privacy. The Benefits of AI in Cyber Security

AI has become a powerful tool in the fight against cyber threats as it can help detect, analyse, and respond to malicious attacks faster. Some benefits of AI in cybersecurity Faster Threat Detection and Response Leveraging AI helps you better understand your networks and identify potential threats faster. AI-powered solutions can sift through vast amounts of data to identify abnormal behaviour and detect malicious activity, such as a new zero-day attack.

AI can also automate many security processes, such as patch management, making staying on top of your cyber security needs easier.

It can help you respond faster to attacks by automating specific tasks, such as rerouting traffic away from a vulnerable server or alerting your IT team to potential issues. Improved Accuracy and Efficiency AI-based cyber security systems provide improved accuracy and efficiency compared to traditional security solutions. For example, AI can scan scads of devices for potential vulnerabilities in a fraction of the time it would take human operators to do the same task.

Furthermore, AI algorithms can recognise patterns that may be difficult for the human eye to spot, leading to more accurate detection of malicious activity.

Greater scalability and cost savings

AI can automate tedious security tasks, freeing valuable resources to focus on other business areas.

It can also process vast amounts of data quickly and accurately to identify threats faster than any human could. This helps reduce response times to security incidents and helps lower the cost of defending against cyber threats.

AI-driven tools can also help identify malicious activity by correlating different data points, allowing you to protect your systems proactively. These solutions are easily scalable, meaning you can obtain additional protection without significant hardware or personnel costs.

The risks of relying on AI in cyber security AI’s ability to analyse large data sets with lightning speed promises unparalleled protection against cyber-attacks, and companies worldwide are investing heavily in its application.

But even as AI is increasingly relied upon to bolster security, there are still risks in relying on this technology.

Biased decision-making in AI systems can arise from various sources, including data sets containing biased information or algorithms that lack the necessary objectivity.

If not managed properly, these biases can lead to discriminatory decisions against certain groups or individuals and have significant consequences for the organisation.

For example, a decision made by an AI system based on biased inputs could lead to false positives and block legitimate users from accessing company systems, resulting in lost productivity or customers.

Lack of explain ability and transparency The algorithms used to make decisions about security threats are not always transparent, leaving you vulnerable to potential bias or manipulation. AI can be difficult to interpret, so it is hard to understand why decisions were made or how they can be improved.

This lack of understanding can lead to poor decisions, which can have severe implications for an organisation’s security.

AI-based cyber security solutions may not always accurately identify every threat or potential breach, leading to potential risks going unnoticed and causing further damage. Examples of AI in Cyber Crime Cyber criminals may use AI to:

Easily create new malware that can contain new zero-day vulnerabilities or bypass detection.

Create new, sophisticated, original, or targeted phishing attacks. Such actions can increase the number of scenarios, making it difficult for reputation engines to keep up.

Analyse and collect data much quicker and help identify other avenues of attack.

Create deep fakes (video or audio) that can be used to convince victims in social engineering attacks.

Conduct attacks such as intrusions or generate new hacking tools.

And because AI relies on data sets that are often biased or incomplete, it can lead to missed threats and false positives, creating a false sense of security and leading to realworld consequences.– terranovasecurity.com