Booz Allen Interns Apply Machine Learning to Solve Tough Problems

The steam engine. The airplane. The microprocessor. Now, machine intelligence—machines’ ability to perceive, interpret, and take action based on data—represents the next transformative technology for society. We’re already seeing its awe-inspiring effects: from trucks that drive themselves, to computer programs that develop drug therapies, to software that writes news articles and composes music.

This summer, three teams of Booz Allen Summer Games interns are applying machine learning to protect against the growing number of cyber attacks creating instability and uncertainty in today’s marketplace. These interns are developing smart tech solutions such as detection tools to help security professionals prioritize cybersecurity alerts, algorithms to detect cyber breaches, and automated IT systems that function like dashboards and chatbots to ensure continuity in a cyber crisis.

Below, learn more about the teams’ work in their own words:

Using Machine Learning to Help Security Experts Triage Cyber Threats
“While cybersecurity solutions have become more comprehensive and successful in detecting cyber threats, distinguishing malicious activity from normal network behavior has remained an issue for nearly every enterprise,” said Jamie Downey of the New York-based team. “In order to effectively combat the increasing number of risks associated with cyber-attacks, security professionals must be able to discern which alerts are most pressing. Our team is creating an analytic tool that uses machine learning to predict which alerts are most likely to be associated with a real network threat. The tool enables systematic prioritization of cybersecurity alerts to help analysts and managers determine the most pressing alerts and act on them quickly and effectively.”

Predicting & Preventing Cyber Attacks on Critical Infrastructure
“When people think of threats to cybersecurity they most often think of the need to protect systems like banking or credit card companies. But hidden in plain sight are countless industrial control systems that manage and protect essential infrastructure systems and utilities like electricity, water, and gasoline. Targeted attacks on these systems pose a serious threat to our nation’s safety,” said Benjamin Deaver of the Maryland-based team.  “Our goal is to develop a tool that will use machine learning to analyze vast quantities of process data and identify abnormal patterns that correlate with cyber intrusions, operational failures, and other concerns that can affect critical infrastructure availability. Our tool will help minimize tampering and cyber intrusions that could negatively impact customers, workers, the environment, our economy and our national security.”

Automating IT Operations using Machine Intelligence
“The federal government is on track to spend $85 billion this year on IT alone, and much of that expenditure is unnecessary: the result of reacting to IT slowdowns and catastrophes when they occur,” said Annie Chen of the Maryland-based team. “We are building a system that can revamp the way organizations run their IT infrastructure. By aggregating available IT data and using predictive analytics, we will enable IT teams to prevent costly and time-consuming IT slowdowns and crashes before they occur. Our personalized dashboards and chatbots enable decision makers to be looped in to IT processes, streamlining IT workflow and ultimately saving organizations time and money.”

Want to learn more about how Booz Allen’s Summer Games interns are empowered to change the world? Visit: 
http://3blmedia.com/News/From-Protecting-Critical-Infrastructure-to-Streamlining-IT-Systems-How-Booz-Allen-Interns-Apply-Machine-Learning-to-Solve-Tough-Problems