HOW CAN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING SUPPORT CYBERSECURITY

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HOW CAN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING SUPPORT CYBERSECURITY BY Bob Tarver 7/2/2023

Introduction: With the large growth of devices that are connected to the internet, the need to make said devices secure is a top priority. In both the private and public sectors are having their trials and tribulations as they try to protect their organizations from cyber- attacks that take place every day on a large scale. Artificial Intelligence and Machine learning helps organizations learn and analyze cyber threats in real-time.[ CITATION Sai231 \l 1033 ] Together , AI and ML can help organizations bolster their security defense by increasing the speed and accuracy of their response to cyber-attacks.[ CITATION Sai231 \l 1033 ] Analysis: In today’s world of cybersecurity comes a series of new challenges. They include: A Broad Attack Surface, Many devices that need to be protected in any organization , Attack vectors that can be exploited by threat actors.[ CITATION

Eng23 \l 1033 ] For example , in 2021 , the number of data breaches by the end of the third quarter surpassed all of 2020 by 17%.[ CITATION Sai231 \l 1033 ] In addition ransomware has been growing at a rate with the cost of each incident costing companies more than $700,000.[ CITATION Sai231 \l 1033 ] with ransomware attacks taking place every 11 seconds this has resulted in an average of 21 days of downtime.[ CITATION Sai231 \l 1033 ] A report by Capgemini Research Institute, 61% of organizations state they will not be able to identify critical threats without AI.[ CITATION Sai231 \l 1033 ] Benefits of using AI and ML: Artificial Intelligence learns more over time . It uses machine learning and deep learning techniques to analyze network behavior and find deviations or incidents from what is normal. [ CITATION Eng23 \l 1033 ] AI can identify threats . By being able to identify potential threats by threat actors, due to constant change of tactics, it makes AI a necessary tool to be used in the

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prevention of cyber-attack.[ CITATION Eng23 \l 1033 ] AI has the ability to handle large amounts of data. Any organization, whether private or public, generates substantial amounts of data daily. This can cause problems for cybersecurity personnel to check all incoming data for any threats. AI can streamline the process and make quicker decision on the course of action to take.[ CITATION Eng23 \l 1033 ] Better Overall security. Hackers change their tactics on a regular basis to keep from being detected.[ CITATION Eng23 \l 1033 ] AI eliminates time- consuming tasks . It can scan substantial amounts of data, reduce false positives by filtering out non-threating activities. [ CITATION Eng23 \l 1033 ] How AI is used in Cybersecurity: Breach risk prediction , phishing detection, malware detection and prevention, user authentication , spam filtering, bot identification, behavioral analysis, fraud detection incident response.[ CITATION Eng23 \l 1033 ]

Ways that Threat Actors can use AI for Cyber-attacks: Data Poisoning. When a threat actor can corrupt the data sets that make up the training model, it damages the model’s accuracy.[ CITATION inf20 \l 1033 ] When the predictors behavior is attacked, the possibility of more errors taking place is increased.[ CITATION inf20 \l 1033 ] Manipulation of Bots. Bots are algorithms that can be programmed to make decisions. When a threat actor can force the bot to make a wrong decision, or worse, could sabotage the system they operate within.[ CITATION inf20 \l 1033 ] This could be accomplished when the threat actors study a bot’s patterns, they can alter its decision making ability.[ CITATION inf20 \l 1033 ] Generative Adversarial Networks. It uses two sets of AI systems that can simulate data. During an interaction of the data sets, one will present the data , while the other system will point out the errors or mistakes.[ CITATION inf20 \l 1033 ] Having the ability to simulate regular data traffic during an attack can hide the

threat actors actions. A byproduct of this could be used by threat actors to steal passwords.[ CITATION inf20 \l 1033 ] Countermeasures to be used for defense: Training Data Filtering , Robust learning, and Auxiliary tools.[ CITATION Wan20 \l 1033 ] Using training data filtering , the defenders look to control the data using detection and sanitizing methods to prevent attacks.[ CITATION Wan20 \l 1033 ] With regards to robust learning , you are modifying the architecture of the trained model which in turn will reduce the impact of the poisoned data and make the system stronger.[ CITATION Wan20 \l 1033 ] Using auxiliary tools such as GAN’s and robust statistics. Using spectral signatures, they can extract a layer to calculate how a attack vector will be used.[ CITATION Wan20 \l 1033 ] Conclusion: Artificial Intelligence and Machine Learning is important for increasing the ability for cybersecurity teams to combat those who

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would attempt to damage, steal information, or destroy an organization’s computer enterprise system. IT teams will be able to identify risks and provide a direct response to a cyber-attack. While there are potential downsides to the use of AI, the ability of AI to help protect the enterprise system of any organization is of tremendous value.

References: Engati.com. (2023, April 10). Top 10 Benefits of using AI in Cybersecurity. Retrieved from Engati.com: https://www.engati.com/blog/ai-for-cybersecurity infoguardsecurity.com. (2020, October 15). Top 3 criminal methods of using artificial intelligence for cyber-attacks. Retrieved from infoguardsecurity.com: https://www.infoguardsecurity.com/top-3- criminal-methods-of-using-artificial-intelligence-for-cyber-attacks/ SailPoint.com. (2023, July 2). How AI and Machine Learning Are Improving Cybersecurity. Retrieved from SailPoint.com: https://www.sailpoint.com/identity-library/how-ai-and-machine-learning-are- improving-cybersecurity/ Wang, C. (2020, April). Poisioning Attack Countermeasures in Intelligent Networks: status Quo and Prospects. Retrieved from sciencedirect.com: https://www.sciencedirect.com/science/article/pii/S235286482100050X

HOW CAN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING SUPPORT CYBERSECURITY

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