Data science

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Visible to the public SBE TWC: Small: Collaborative: Pocket Security - Smartphone Cybercrime in the Wild

Most of the world's internet access occurs through mobile devices such as smart phones and tablets. While these devices are convenient, they also enable crimes that intersect the physical world and cyberspace. For example, a thief who steals a smartphone can gain access to a person?s sensitive email, or someone using a banking app on the train may reveal account numbers to someone looking over her shoulder. This research will study how, when, and where people use smartphones and the relationship between these usage patterns and the likelihood of being a victim of cybercrime.

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Visible to the public SBE: Small: An optimization framework for prioritizing cyber-security mitigations for securing information technology infrastructure

Our nation's information technology (IT) infrastructure is vulnerable to numerous security risks, including security vulnerabilities within the IT supply chain. This research addresses the cyber-security risks and vulnerabilities that exist in the Federal IT infrastructure. It will provide new insights for prioritizing and deploying IT security mitigations in a budget-constrained environment. It will also develop tools that can be used by Federal decision-makers and other large organizations which make investments.

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Visible to the public EAGER: TWC: Collaborative: iPrivacy: Automatic Recommendation of Personalized Privacy Settings for Image Sharing

The objective of this project is to investigate a comprehensive image privacy recommendation system, called iPrivacy (image Privacy), which can efficiently and automatically generate proper privacy settings for newly shared photos that also considers consensus of multiple parties appearing in the same photo. Photo sharing has become very popular with the growing ubiquity of smartphones and other mobile devices.

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Visible to the public TWC: TTP Option: Small: Collaborative: Integrated Smart Grid Analytics for Anomaly Detection

The modernized electric grid, the Smart Grid, integrates two-way communication technologies across power generation, transmission and distribution, in order to deliver electricity efficiently, securely and cost-effectively. On the monitoring and control side, it employs real-time monitoring offered by a messaging-based advanced metering infrastructure (AMI), which ensures the grid?s stability and reliability, as well as the efficient implementation of demand response schemes to mitigate bursts demand.

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Visible to the public Breakthrough: Collaborative: Secure Algorithms for Cyber-Physical Systems

Modern systems such as the electric smart grid consist of both cyber and physical components that must work together; these are called cyber-physical systems, or CPS. Securing such systems goes beyond just cyber security or physical security into cyber-physical security. While the threats multiply within a CPS, physical aspects also can reduce the threat space. Unlike purely cyber systems, such as the internet, CPS are grounded in physical reality.

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Visible to the public TWC: TTP Option: Small: Collaborative: Integrated Smart Grid Analytics for Anomaly Detection

The modernized electric grid, the Smart Grid, integrates two-way communication technologies across power generation, transmission and distribution, in order to deliver electricity efficiently, securely and cost-effectively. On the monitoring and control side, it employs real-time monitoring offered by a messaging-based advanced metering infrastructure (AMI), which ensures the grid's stability and reliability, as well as the efficient implementation of demand response schemes to mitigate bursts demand.

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Visible to the public SBE: Small: Statistical Models and Methods for Dynamic Complex Networks

The project examines the structure and function of dynamic networks by formulating and analyzing probabilistic models for temporally evolving networks and processes occurring on them. In addition, the project seeks practical and efficient statistical methods for network inference. The project is primarily motivated by national security concerns surrounding counter-terrorism and cybersecurity, but outcomes should be directly relevant in biological, social, and physical science applications as well as mathematical areas of probability theory, combinatorics, and graph theory.

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Visible to the public EAGER: Toward Transparency in Public Policy via Privacy-Enhanced Social Flow Analysis with Applications to Ecological Networks and Crime

Recent improvements in computing capabilities, data collection, and data science have enabled tremendous advances in scientific data analysis. However, the relevant data are often highly sensitive (e.g., Census records, tax records, medical records). This project addresses an emerging and critical scientific problem: Privacy concerns limit access to raw data that might reveal information about individuals. Techniques to "sanitize" such data (e.g., anonymization) could have negative impact on the quality of the scientific results that use the data.

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Visible to the public TWC: Medium: Collaborative: Black-Box Evaluation of Cryptographic Entropy at Scale

The ability to generate random numbers -- to flip coins -- is crucial for many computing tasks, from Monte Carlo simulation to secure communications. The theory of building such subsystems to generate random numbers is well understood, but the gap between theory and practice is surprisingly wide. As built today, these subsystems are opaque and fragile. Flaws in these subsystems can compromise the security of millions of Internet hosts.

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Visible to the public EAGER: Model Driven Framework for Audio Forensics

The goal of this project is to investigate the reliability, robustness, and computationally efficiency of digital audio forensic methods under various adversarial conditions, e.g., lossy compression attack. We aim to identify and develop mathematical tools for modeling and characterizing of microphone nonlinearities (fingerprints), statistical methods for acoustic environment estimation, and system identification based framework for linking an acquisition device to the audio recording.