Machine Learning Implications in Cybersecurity

Anthony Wright
2 min readJan 26, 2021

A former U.S. Navy combat pilot who has served in a managerial position in Maryland, Anthony Wright obtained an MA in national security and strategic studies from the Naval War College in 2007. An accomplished executive, Anthony Wright has led software projects across several states, including Virginia and Maryland. While also pursuing a degree in data science at Georgetown University, he seeks to promote cutting-edge technological solutions with machine learning capabilities.

Machine learning is an advancing technological approach that focuses on equipping AI with the ability to learn from and respond to data automatically in real time. This new technological approach will enable machines to perform complex tasks with minimal to no human interactions. In this capacity, AI can efficiently serve humans in a wide range of applications. In terms of national security, these advanced functionalities can serve military applications.

Machine learning will revolutionize data analytics. AI embedded with ML systems can perform predictive analytics from large streams of digital information. This will serve as a solution to several problems associated with the conventional systems of today, including data overload and mismanaged information. In the defense space, this functionality can automate processes such as cyber situation awareness, pattern recognition, malware detection, cybersecurity, and risk management.

If the high speed required to perform any cyber operation is considered, it becomes apparent that only machines can provide the most efficient response in the early stages of any serious cyberattack. Through machine learning, AI can learn from indicators of compromise, and recognize these characteristics in a wide range of modalities, even if they are scrambled throughout the network. Once these loops are detected, AI can automatically counter these threats by setting up self-configuring networks and also perform response actions like self-patching. This will strengthen the system’s resilience and increase protection against cyber threats.

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Anthony Wright

Anthony Wright — Former Maryland Resident Working in Data Science