Publications
Secure channel establishment in disadvantaged networks: optimizing TLS using intercepting proxies
Summary
Summary
Transport Layer Security (TLS) is a secure communication protocol that is used in many secure electronic applications. In order to establish a TLS connection, a client and server engage in a handshake, which usually involves the transmission of digital certificates. In this paper we present a practical speedup of TLS...
Physical layer considerations for wideband cognitive radio
Summary
Summary
Next generation cognitive radios will benefit from the capability of transmitting and receiving communications waveforms across many disjoint frequency channels spanning hundreds of megahertz of bandwidth. The information theoretic advantages of multi-channel operation for cognitive radio (CR), however, come at the expense of stringent linearity requirements on the analog transmit...
TALENT: dynamic platform heterogeneity for cyber survivability of mission critical applications
Summary
Summary
Despite the significant amount of effort that often goes into securing mission critical systems, many remain vulnerable to advanced, targeted cyber attacks. In this work, we design and implement TALENT (Trusted dynAmic Logical hEterogeNeity sysTem), a framework to live-migrate mission critical applications across heterogeneous platforms. TALENT enables us to change...
Hogs and slackers: using operations balance in a genetic algorithm to optimize sparse algebra computation on distributed architectures
Summary
Summary
We present a framework for optimizing the distributed performance of sparse matrix computations. These computations are optimally parallelized by distributing their operations across processors in a subtly uneven balance. Because the optimal balance point depends on the non-zero patterns in the data, the algorithm, and the underlying hardware architecture, it...
Graph-embedding for speaker recognition
Summary
Summary
Popular methods for speaker classification perform speaker comparison in a high-dimensional space, however, recent work has shown that most of the speaker variability is captured by a low-dimensional subspace of that space. In this paper we examine whether additional structure in terms of nonlinear manifolds exist within the high-dimensional space...
Simple and efficient speaker comparison using approximate KL divergence
Summary
Summary
We describe a simple, novel, and efficient system for speaker comparison with two main components. First, the system uses a new approximate KL divergence distance extending earlier GMM parameter vector SVM kernels. The approximate distance incorporates data-dependent mixture weights as well as the standard MAP-adapted GMM mean parameters. Second, the...
Multi-pitch estimation by a joint 2-D representation of pitch and pitch dynamics
Summary
Summary
Multi-pitch estimation of co-channel speech is especially challenging when the underlying pitch tracks are close in pitch value (e.g., when pitch tracks cross). Building on our previous work, we demonstrate the utility of a two-dimensional (2-D) analysis method of speech for this problem by exploiting its joint representation of pitch...
Transcript-dependent speaker recognition using mixer 1 and 2
Summary
Summary
Transcript-dependent speaker-recognition experiments are performed with the Mixer 1 and 2 read-transcription corpus using the Lincoln Laboratory speaker recognition system. Our analysis shows how widely speaker-recognition performance can vary on transcript-dependent data compared to conversational data of the same durations, given enrollment data from the same spontaneous conversational speech. A...
Generating client workloads and high-fidelity network traffic for controllable, repeatable experiments in computer security
Summary
Summary
Rigorous scientific experimentation in system and network security remains an elusive goal. Recent work has outlined three basic requirements for experiments, namely that hypotheses must be falsifiable, experiments must be controllable, and experiments must be repeatable and reproducible. Despite their simplicity, these goals are difficult to achieve, especially when dealing...
Machine learning in adversarial environments
Summary
Summary
Whenever machine learning is used to prevent illegal or unsanctioned activity and there is an economic incentive, adversaries will attempt to circumvent the protection provided. Constraints on how adversaries can manipulate training and test data for classifiers used to detect suspicious behavior make problems in this area tractable and interesting...