Intrusion detection

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Visible to the public TWC: Option: Medium: Collaborative: Semantic Security Monitoring for Industrial Control Systems

Industrial control systems differ significantly from standard, general-purpose computing environments, and they face quite different security challenges. With physical "air gaps" now the exception, our critical infrastructure has become vulnerable to a broad range of potential attackers. In this project we develop novel network monitoring approaches that can detect sophisticated semantic attacks: malicious actions that drive a process into an unsafe state without however exhibiting any obvious protocol-level red flags.

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Visible to the public TWC: Option: Medium: Collaborative: Semantic Security Monitoring for Industrial Control Systems

Industrial control systems differ significantly from standard, general-purpose computing environments, and they face quite different security challenges. With physical "air gaps" now the exception, our critical infrastructure has become vulnerable to a broad range of potential attackers. In this project we develop novel network monitoring approaches that can detect sophisticated semantic attacks: malicious actions that drive a process into an unsafe state without however exhibiting any obvious protocol-level red flags.

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Visible to the public EAGER: Collaborative: Algorithmic Framework for Anomaly Detection in Interdependent Networks

Modern critical infrastructure relies on successful interdependent function among many different types of networks. For example, the Internet depends on access to the power grid, which in turn depends on the power-grid communication network and the energy production network. For this reason, network science researchers have begun examining the robustness of critical infrastructure as a network of networks, or a multilayer network. Research in network anomaly detection systems has focused on single network structures (specifically, the Internet as a single network).

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Visible to the public TWC: Small: Unsupervised and Statistical Natural Language Processing Techniques for Automatic Phishing and Opinion Spam Detection

In phishing, an attacker tries to steal sensitive information, e.g., bank/credit card account numbers, login information, etc., from Internet users. The US society and economy are increasingly dependent on the Internet and the web, which is plagued by phishing. One popular phishing method is to create a site that mimics a good site and then attract users to it via email, which is by far the most popular medium to entice unsuspecting users to the phishing site.

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Visible to the public TWC: Medium: Digital Healthcare-Associated Infection: Measurement, Defense and Prevention in a Modern Digital Healthcare Ecosystem

The pace of digitization and interconnection of hospital systems has increased tremendously as recent healthcare legislation has encouraged the interoperation of medical record systems. In addition to ordinary business operations data, hospital enterprise networks now carry patient record data and life-critical data streams from therapy systems (e.g., nuclear medicine, dialysis clinical systems). Unfortunately, the security implications of interconnecting such life-critical systems has been largely unstudied.

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Visible to the public EDU: Collaborative: Using Virtual Machine Introspection for Deep Cyber Security Education

Cybersecurity is one of the most strategically important areas in computer science, and also one of the most difficult disciplines to teach effectively. Historically, hands-on cyber security exercises helped students reinforce basic concepts, but most of them focused on user level attacks and defenses. Since OS kernels provide the foundations to the applications, any compromise to OS kernels will lead to an entirely untrusted computing. Therefore, it is imperative to teach students the practice of kernel level attacks and defenses.

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Visible to the public EDU: Collaborative: Integrating Embedded Systems Security into Computer Engineering and Science Curricula

With the advancement of technologies, networked devices become ubiquitous in the society. Such devices are not limited to traditional computers and smart phones, but are increasingly extended to cover a wide variety of embedded systems (ES), such as sensors monitoring bridges, electronics controlling the operation of automobiles and industrial equipment, home medicine devices that are constantly reporting patient health information to doctors.

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Visible to the public EAGER: Collaborative: Algorithmic Framework for Anomaly Detection in Interdependent Networks

Modern critical infrastructure relies on successful interdependent function among many different types of networks. For example, the Internet depends on access to the power grid, which in turn depends on the power-grid communication network and the energy production network. For this reason, network science researchers have begun examining the robustness of critical infrastructure as a network of networks, or a multilayer network. Research in network anomaly detection systems has focused on single network structures (specifically, the Internet as a single network).

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Visible to the public TWC: Small: Emerging Attacks Against the Mobile Web and Novel Proxy Technologies for Their Containment

Users entrust their mobile devices with sensitive data, including business emails, as well as health and financial information. Thus, mobile devices have become an increasingly popular target for attackers. Mobile devices house powerful browsers that are vulnerable to at least as many attacks as their desktop counterparts. Yet, the security of these mobile browsers is understudied by researchers, leading to a lack of current information about ongoing attacks and possible defenses.