Is It Possible To Trust AI Decision-Making In Cybersecurity?

As AI continues to evolve and develop, people have been keen to recognize its potential in the cybersecurity industry. Its use is already prevalent, as almost 51% of businesses use AI for threat detection. Moreover, as the cyber threat landscape continues to grow, there is a dire need for such autonomous systems to help curb the rising advances of cyber attacks. 

In simpler terms, to minimize the impact of the rising number of cyber attacks, humans must entrust AI with making decisions they once made. However, since AI is still significantly evolving, it is hard to grasp how AI will impact decision-making and whether we can trust the results. 

What Does AI-Decision Making Mean To Cybersecurity?

AI decision-making means the capability of AI-powered systems to conduct data-processing tasks and make decisions with little or no help from humans. They make numerous micro-decisions through the constraints and guide rails set by humans. 

These systems can quantify qualitative data, make precise decisions and tackle complex tasks such as data analysis, anomaly detection, data crunching, and much more. As a result, humans are left only to manage things at a macro level making their day-to-day tasks more strategic. AI decision-making has the following three categories:

  • Decision Support:   a system that combines human intelligence and AI-powered data-driven insights to make informed decisions. 
  • Decision augmentation:   a system that utilizes predictive analytics or prescriptive analysis to develop potential and specific outcomes or decisions based on needs. 
  • Decision automation:   a system designed to replace humans by automating their daily decision-making tasks. 

Regarding cybersecurity, AI-decision making can play a very dynamic role. These systems can collect real-time data about active cyber threats, such as gathering insight into the latest malware campaigns. They are specifically functional against disturbingly common cyber attacks such as phishing scams, malware campaigns, and denial-of-service attacks, as they can work continually to gain relevant insight and help ensure security. 

Is It Possible To Trust AI In Cybersecurity?

When it comes to technology, there is no black-or-white distinction of whether it is bound to be entirely good or bad, but rather it all comes with a designated set of pros and cons. When pondering over the integration of AI into cybersecurity, there are several pros to consider, such as:

  • Unlike humans, AI systems can search for cyber threats and vulnerabilities around the clock without rest. 
  • According to research, AI-powered security systems have great potential in fraud detection, intrusion detection, and malware detection through data and behavior analysis. 
  • An ML or AI-powered system observes and learns in record time, unlike human cybersecurity experts needing strict training and tests. 
  • Human error is a significant security concern that AI-powered systems can help eradicate. 

While integrating AI into cyber security does seemingly comes with many benefits, there are also several risks to consider, such as:

  • AI systems need updated data sets to work efficiently and would require a team of dedicated teams to integrate those data sets; otherwise, the security system would fail. 
  • While AI is efficient, it is still technology and open to exploitation. There are instances of modern AI technology used to launch cyber and ransomware attacks. 
  • Since we are yet to comprehend AI decision-making fully, ML algorithms can make detection mistakes unknown to security persons putting the systems at risk of cyber attacks. 

Since AI has pros and cons, deciding whether to trust it in cyber security is challenging. As AI grows, it has formed an interoperable connection with cybersecurity, and organizations have quickly started integrating it within their security systems. 75% of enterprises now rely on AI-powered solutions for network security today. Amongst this, the only solution left is a secure AI integration in cybersecurity. 

Best Ways To Integrate AI Decision-Making Into Cybersecurity

With AI becoming a crucial part of cybersecurity while having a significant associated risk, finding reliable methods to integrate it within security systems is critical. Some of the best tips that an organization can make use of while integrating AI are as follows:

  • Ensure AI transparency and explainability, as this can help detect and address potential vulnerabilities within the system. 
  • Organizations must adopt responsible data governance practices while training AI models to mitigate bias. 
  • Organizations should accept regular security assessments to identify and address potential vulnerabilities. 
  • Organizations should thoroughly assess security when adopting AI systems through third-party vendors. 

Looking into these tips can help organizations ensure their AI models are secure and reliable for enabling robust security, 

Final Words 

AI has yet to evolve and develop and until its true potential or risks are not yet fully identified, the element of trust will always remain in question. However, while security professionals struggle with completely trusting AI, ignoring its benefits to the cybersecurity industry can lead to several downsides too.

Amidst this, the best way left is to take a leap of faith and find reliable methods for integrating AI autonomous systems within an organizational security infrastructure. 

Iam Waqas is s a cybersecurity journalist and writer who focuses on technology & online privacy.

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