Publications
On the challenges of effective movement
Summary
Summary
Moving Target (MT) defenses have been proposed as a gamechanging approach to rebalance the security landscape in favor of the defender. MT techniques make systems less deterministic, less static, and less homogeneous in order to increase the level of effort required to achieve a successful compromise. However, a number of...
Information leaks without memory disclosures: remote side channel attacks on diversified code
Summary
Summary
Code diversification has been proposed as a technique to mitigate code reuse attacks, which have recently become the predominant way for attackers to exploit memory corruption vulnerabilities. As code reuse attacks require detailed knowledge of where code is in memory, diversification techniques attempt to mitigate these attacks by randomizing what...
Spectral anomaly detection in very large graphs: Models, noise, and computational complexity(92.92 KB)
Summary
Summary
Anomaly detection in massive networks has numerous theoretical and computational challenges, especially as the behavior to be detected becomes small in comparison to the larger network. This presentation focuses on recent results in three key technical areas, specifically geared toward spectral methods for detection.
Finding good enough: a task-based evaluation of query biased summarization for cross language information retrieval
Summary
Summary
In this paper we present our task-based evaluation of query biased summarization for cross-language information retrieval (CLIR) using relevance prediction. We describe our 13 summarization methods each from one of four summarization strategies. We show how well our methods perform using Farsi text from the CLEF 2008 shared-task, which we...
Quantitative evaluation of dynamic platform techniques as a defensive mechanism
Summary
Summary
Cyber defenses based on dynamic platform techniques have been proposed as a way to make systems more resilient to attacks. These defenses change the properties of the platforms in order to make attacks more complicated. Unfortunately, little work has been done on measuring the effectiveness of these defenses. In this...
Using deep belief networks for vector-based speaker recognition
Summary
Summary
Deep belief networks (DBNs) have become a successful approach for acoustic modeling in speech recognition. DBNs exhibit strong approximation properties, improved performance, and are parameter efficient. In this work, we propose methods for applying DBNs to speaker recognition. In contrast to prior work, our approach to DBNs for speaker recognition...
Talking Head Detection by Likelihood-Ratio Test(220.2 KB)
Summary
Summary
Detecting accurately when a person whose face is visible in an audio-visual medium is the audible speaker is an enabling technology with a number of useful applications. The likelihood-ratio test formulation and feature signal processing employed here allow the use of high-dimensional feature sets in the audio and visual domain...
A survey of cryptographic approaches to securing big-data analytics in the cloud
Summary
Summary
The growing demand for cloud computing motivates the need to study the security of data received, stored, processed, and transmitted by a cloud. In this paper, we present a framework for such a study. We introduce a cloud computing model that captures a rich class of big-data use-cases and allows...
Computing on masked data: a high performance method for improving big data veracity
Summary
Summary
The growing gap between data and users calls for innovative tools that address the challenges faced by big data volume, velocity and variety. Along with these standard three V's of big data, an emerging fourth "V" is veracity, which addresses the confidentiality, integrity, and availability of the data. Traditional cryptographic...
Computing on masked data: a high performance method for improving big data veracity
Summary
Summary
The growing gap between data and users calls for innovative tools that address the challenges faced by big data volume, velocity and variety. Along with these standard three V's of big data, an emerging fourth "V" is veracity, which addresses the confidentiality, integrity, and availability of the data. Traditional cryptographic...