Sun. Sep 24th, 2023

Cybercriminals will find new ways to take advantage of technology as it advances and becomes more integrated into the modern world. The cybersecurity industry must be more innovative. Artificial intelligence (AI), could it be the solution to future security threats in the future?

What is AI decision-making in Cybersecurity?

AI programs are capable of making autonomous decisions and implementing security measures around the clock. They can analyze a much larger amount of risk data than the human brain at any one time. A program that uses AI to protect networks and data storage systems is constantly updating its protection, which includes a constant study of cyber attacks.

Cybercriminals are constantly trying to steal data and hardware. People need experts in cybersecurity to protect them. Crimes such as phishing or denial-of-service attacks are common. AI programs can do the same things as cybersecurity experts, such as sleep or research new cybercrime tactics to combat suspicious activity.

Can people trust AI for cyber security?

There are pros and cons to every advancement. AI protects information 24/7 while learning from cyber-attacks elsewhere. Human error is not allowed to cause a network or data compromise.

AI software can be a threat in and of itself. It’s possible to attack the software because it is part of a network or computer’s system. The human brain is not susceptible to malware in the same way.

It is difficult to decide if AI will be the main cybersecurity initiative of a network. It is smart to evaluate the potential benefits and risks before making a decision about a possible cybersecurity change.

AI and Cybersecurity: Benefits

People are more likely to think positively of AI programs when they see them. Technology is already a part of the daily lives of many communities around the world. AI programs reduce safety risks at potentially dangerous workplaces so that employees can be safer when they are on the clock. It has machine-learning (ML) capabilities that collect instant data in order to identify fraud before people are able to click on links or open documents that have been sent by cybercriminals.

AI decision-making for cybersecurity may be the future. It can also improve digital security by improving it in many other ways.

Around the Clock It Monitors

Even the best cybersecurity teams need to sleep from time to time. Intruders and vulnerabilities are still a danger when they don’t monitor their networks. AI can continuously analyze data to identify patterns that may indicate a cyber attack. As global cyber-attacks happen every 39 seconds it is important to stay vigilant.

You could drastically reduce financial losses

A program that monitors vulnerabilities in the cloud, network, and applications would also help to prevent financial losses after a cyber-attack. A recent study shows that companies are losing over $1 million for every breach. This is due to the increase in remote employment. Internal IT teams are unable to control cybersecurity in a company’s entirety due to home networks. AI could reach remote workers, providing an extra layer of protection outside professional offices.

This creates biometric validation options

Biometric authentication is available for users of systems that have AI capabilities. Biometric credentials can be created by scanning a person’s fingerprint or face instead of traditional passwords or two-factor authentication.

Biometric data can also be stored as numerical values rather than raw data. Cybercriminals would be unable to use these values to gain access to confidential information if they were to hack into them.

You’re always learning to identify threats

If human-powered IT teams wish to recognize new cybersecurity threats they will need to undergo training that could last days or even weeks. AI programs are able to learn about new threats automatically. They are always prepared for system updates, which inform them of the latest hacking attempts by cybercriminals.

Threat identification methods are constantly updated, making network infrastructure and confidential information safer than ever. Human error is not possible due to gaps in knowledge between training sessions.

It eliminates human error

Human error can occur even if someone is an expert in their area. people get tired and procrastinate. They forget to do the essential tasks within their role. If that happens to someone in the IT security team, they may overlook a security task that leaves their network vulnerable.

AI is never tired and doesn’t forget what it has to do. It eliminates human errors that could lead to cybersecurity failures. If they occur, security lapses and network holes will not be a threat for very long.

Possible Concerns to Take into Consideration

AI is no different. It still poses some risks, just like any other new technology. As AI is still a relatively new technology, cybersecurity experts need to keep these concerns in mind when imagining the future of AI-based decision-making.

Updating data sets is essential for effective AI

AI must also be updated to maintain peak performance. It would not provide the level of security that clients expect without input from all computers in a company’s network. Because the AI system is unaware of sensitive information, it could be more vulnerable to intrusions.

The data sets include the most recent upgrades to cybersecurity resources. To provide consistent protection, the AI system will need to have access to the latest malware profiles and anomaly detection capabilities. It can take an IT team a long time to collect all of this information.

The IT team would require training in order to collect and update data sets for their newly installed AI security program. Each step in upgrading AI decision-making requires time and money. Those organizations that lack the resources to upgrade AI decision-making quickly could be more vulnerable to attack.

AI Can Still Present False Positives

AI decision-making includes ML algorithms. Even computers can’t be perfect, and people rely on this vital component of AI programs in order to identify security threats. Machine learning algorithms are prone to making anomaly detection errors due to their reliance on data and the fact that they’re so new.

When an AI-based security program detects a problem, it can alert experts in the security operations center so that they can manually examine and fix the issue. The program can remove the subject automatically. While this is useful for detecting real threats, false positives can be dangerous.

The AI algorithm may remove patches or data that isn’t dangerous. This puts the system at greater risk of real security problems, especially if the IT team is not monitoring the algorithm’s actions.

The team may also be distracted if this happens regularly. The team would have to spend time sifting through false positives and fix what the algorithm had accidentally broken. If this problem lasted for a long time, cybercriminals could bypass both the team as well as the algorithm. To avoid false positives, it may be best to update the AI software.

Prepare for AI’s decision-making potential

Artificial intelligence already helps people protect sensitive information. There could be benefits to future attacks if more people start to trust AI in cybersecurity.

It is essential to understand the risks and benefits of using technology in new ways.

Cybersecurity Teams will be able to understand the best ways to implement new technology without exposing their systems to vulnerabilities.

By Tejas

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