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Using leader-based communication to improve the scalability of single-round group membership algorithms

April 4, 2005
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Conference Paper
Author:
Roger I. Khazan
…
Published in:
IPDPS 2005: 19th Int. Parallel and Distributed Processing Symp., 4-8 April 2005, pp. 280-287.
Topic:
algorithms
R&D area:
R&D group:

Summary

Sigma, the first single-round group membership (GM) algorithm, was recently introduced and demonstrated to operate consistently with theoretical expectations in a simulated WAN environment. Sigma achieved similar quality of membership configurations as existing algorithms but required fewer message exchange rounds. We now consider Sigma in terms of scalability. Sigma involves all-to-all (A2A) type of communication among members. A2A protocols have been shown to perform worse than leader-based (LB) protocols in certain networks, due to greater message overhead and higher likelihood of message loss. Thus, although LB protocols often involve additional communication steps, they can be more efficient in practice, particularly in fault-prone networks with large numbers of participating nodes. In this paper, we present Leader-Based Sigma, which transforms the original all-to-all version into a more scalable centralized communication scheme, and discuss the rounds vs. messages tradeoff involved in optimizing GM algorithms for deployment in large-scale, fault-prone dynamic network environments.
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Summary

Sigma, the first single-round group membership (GM) algorithm, was recently introduced and demonstrated to operate consistently with theoretical expectations in a simulated WAN environment. Sigma achieved similar quality of membership configurations as existing algorithms but required fewer message exchange rounds. We now consider Sigma in terms of scalability. Sigma involves...

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Using leader-based communication to improve the scalability of single-round group membership algorithms

An annotated review of past papers on attack graphs

March 31, 2005
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Project Report
Author:
Richard P. Lippmann
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Published in:
MIT Lincoln Laboratory Report IA-1
Topic:
attack graphs
R&D area:
R&D group:

Summary

This report reviews past research papers that describe how to construct attack graphs, how to use them to improve security of computer networks, and how to use them to analyze alerts from intrusion detection systems. Two commercial systems are described [I, 2], and a summary table compares important characteristics of past research studies. For each study, information is provided on the number of attacker goals, how graphs are constructed, sizes of networks analyzed, how well the approach scales to larger networks, and the general approach. Although research has made significant progress in the past few years, no system has analyzed networks with more than 20 hosts, and computation for most approaches scales poorly and would be impractical for networks with more than even a few hundred hosts. Current approaches also are limited because many require extensive and difficult-to-obtain details on attacks, many assume that host-to-host reachability information between all hosts is already available, and many produce an attack graph but do not automatically generate recommendations from that graph. Researchers have suggested promising approaches to alleviate some of these limitations, including grouping hosts to improve scaling, using worst-case default values for unknown attack details, and symbolically analyzing attack graphs to generate recommendations that improve security for critical hosts. Future research should explore these and other approaches to develop attack graph construction and analysis algorithms that can be applied to large enterprise networks.
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Summary

This report reviews past research papers that describe how to construct attack graphs, how to use them to improve security of computer networks, and how to use them to analyze alerts from intrusion detection systems. Two commercial systems are described [I, 2], and a summary table compares important characteristics of...

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An annotated review of past papers on attack graphs

Speaker adaptive cohort selection for Tnorm in text-independent speaker verification

March 19, 2005
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Conference Paper
Author:
Douglas E. Sturim
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Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. 1, 19-23 March 2005, pp. I-741 - I-744.
Topic:
speaker recognition
R&D area:
R&D group:

Summary

In this paper we discuss an extension to the widely used score normalization technique of test normalization (Tnorm) for text-independent speaker verification. A new method of speaker Adaptive-Tnorm that offers advantages over the standard Tnorm by adjusting the speaker set to the target model is presented. Examples of this improvement using the 2004 NIST SRE data are also presented.
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Summary

In this paper we discuss an extension to the widely used score normalization technique of test normalization (Tnorm) for text-independent speaker verification. A new method of speaker Adaptive-Tnorm that offers advantages over the standard Tnorm by adjusting the speaker set to the target model is presented. Examples of this improvement...

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Speaker adaptive cohort selection for Tnorm in text-independent speaker verification

Measuring human readability of machine generated text: three case studies in speech recognition and machine translation

March 19, 2005
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Conference Paper
Author:
Douglas A. Jones
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Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, Vol. 5, ICASSP, 19-23 March 2005, pp. V-1009 - V-1012.
Topic:
machine translation
R&D area:
R&D group:

Summary

We present highlights from three experiments that test the readability of current state-of-the art system output from (1) an automated English speech-to-text system (2) a text-based Arabic-to-English machine translation system and (3) an audio-based Arabic-to-English MT process. We measure readability in terms of reaction time and passage comprehension in each case, applying standard psycholinguistic testing procedures and a modified version of the standard Defense Language Proficiency Test for Arabic called the DLPT*. We learned that: (1) subjects are slowed down about 25% when reading system STT output, (2) text-based MT systems enable an English speaker to pass Arabic Level 2 on the DLPT* and (3) audio-based MT systems do not enable English speakers to pass Arabic Level 2. We intend for these generic measures of readability to predict performance of more application-specific tasks.
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Summary

We present highlights from three experiments that test the readability of current state-of-the art system output from (1) an automated English speech-to-text system (2) a text-based Arabic-to-English machine translation system and (3) an audio-based Arabic-to-English MT process. We measure readability in terms of reaction time and passage comprehension in each...

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Measuring human readability of machine generated text: three case studies in speech recognition and machine translation

The 2004 MIT Lincoln Laboratory speaker recognition system

March 19, 2005
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Conference Paper
Author:
Douglas A. Reynolds
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Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. 1, 19-23 March 2005, pp. I-177 - I-180.
Topic:
speaker recognition
R&D area:
R&D group:

Summary

The MIT Lincoln Laboratory submission for the 2004 NIST Speaker Recognition Evaluation (SRE) was built upon seven core systems using speaker information from short-term acoustics, pitch and duration prosodic behavior, and phoneme and word usage. These different levels of information were modeled and classified using Gaussian Mixture Models, Support Vector Machines and N-gram language models and were combined using a single layer perception fuser. The 2004 SRE used a new multi-lingual, multi-channel speech corpus that provided a challenging speaker detection task for the above systems. In this paper we describe the core systems used and provide an overview of their performance on the 2004 SRE detection tasks.
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Summary

The MIT Lincoln Laboratory submission for the 2004 NIST Speaker Recognition Evaluation (SRE) was built upon seven core systems using speaker information from short-term acoustics, pitch and duration prosodic behavior, and phoneme and word usage. These different levels of information were modeled and classified using Gaussian Mixture Models, Support Vector...

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The 2004 MIT Lincoln Laboratory speaker recognition system

Design considerations and results for an overlapped subarray radar antenna

March 5, 2005
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Conference Paper
Author:
Jeffrey S. Herd
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Published in:
2005 IEEE Aerospace Conf., 5-12 March 2005, pp. 1087-1092.
Topic:
antennas
R&D area:
R&D group:

Summary

Overlapped subarray networks produce flattopped sector patterns with low sidelobes that suppress grating lobes outside of the main beam of the subarray pattern. They are typically used in limited scan applications, where it is desired to minimize the number of controls required to steer the beam. However, the architecture of an overlapped subarray antenna includes many signal crossovers and a wide variation in splitting/combining ratios, which make it difficult to maintain required error tolerances. This paper presents the design considerations and results for an overlapped subarray radar antenna, including a custom subarray weighting function and the corresponding circuit design and fabrication. Measured pattern results will be shown for a prototype design compared with desired patterns.
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Summary

Overlapped subarray networks produce flattopped sector patterns with low sidelobes that suppress grating lobes outside of the main beam of the subarray pattern. They are typically used in limited scan applications, where it is desired to minimize the number of controls required to steer the beam. However, the architecture of...

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Design considerations and results for an overlapped subarray radar antenna

Evaluating static analysis tools for detecting buffer overflows in C code

March 1, 2005
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Thesis
Author:
Kendra J. Kratkiewicz
Published in:
Thesis (MLA)--Harvard University, 2005.
Topic:
software
R&D area:
R&D group:

Summary

This project evaluated five static analysis tools using a diagnostic test suite to determine their strengths and weaknesses in detecting a variety of buffer overflow flaws in C code. Detection, false alarm, and confusion rates were measured, along with execution time. PolySpace demonstrated a superior detection rate on the basic test suite, missing only one out of a possible 291 detections. It may benefit from improving its treatment of signal handlers, and reducing both its false alarm rate (particularly for C library functions) and execution time. ARCHER performed quite well with no false alarms whatsoever; a few key enhancements, such as in its inter-procedural analysis and handling of C library functions, would boost its detection rate and should improve its performance on real-world code. Splint detected significantly fewer overflows and exhibited the highest false alarm rate. Improvements in its loop handling, and reductions in its false alarm rate would make it a much more useful tool. UNO had no false alarms, but missed a broad variety of overflows amounting to nearly half of the possible detections in the test suite. It would need improvement in many areas to become a very useful tool. BOON was clearly at the back of the pack, not even performing well on the subset of test cases where it could have been expected to function. The project also provides a buffer overflow taxonomy, along with a test suite generator and other tools, that can be used by others to evaluate code analysis tools with respect to buffer overflow detection.
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Summary

This project evaluated five static analysis tools using a diagnostic test suite to determine their strengths and weaknesses in detecting a variety of buffer overflow flaws in C code. Detection, false alarm, and confusion rates were measured, along with execution time. PolySpace demonstrated a superior detection rate on the basic...

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Evaluating static analysis tools for detecting buffer overflows in C code

Automatic dysphonia recognition using biologically-inspired amplitude-modulation features

January 1, 2005
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Conference Paper
Author:
Nicolas Malyska
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Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. 1, 19-23 March 2005, pp. I-873 - I-876.
Topic:
language recognition
R&D area:
R&D group:

Summary

A dysphonia, or disorder of the mechanisms of phonation in the larynx, can create time-varying amplitude fluctuations in the voice. A model for band-dependent analysis of this amplitude modulation (AM) phenomenon in dysphonic speech is developed from a traditional communications engineering perspective. This perspective challenges current dysphonia analysis methods that analyze AM in the time-domain signal. An automatic dysphonia recognition system is designed to exploit AM in voice using a biologically-inspired model of the inferior colliculus. This system, built upon a Gaussian-mixture-model (GMM) classification backend, recognizes the presence of dysphonia in the voice signal. Recognition experiments using data obtained from the Kay Elemetrics Voice Disorders Database suggest that the system provides complementary information to state-of-the-art mel-cepstral features. We present dysphonia recognition as an approach to developing features that capture glottal source differences in normal speech.
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Summary

A dysphonia, or disorder of the mechanisms of phonation in the larynx, can create time-varying amplitude fluctuations in the voice. A model for band-dependent analysis of this amplitude modulation (AM) phenomenon in dysphonic speech is developed from a traditional communications engineering perspective. This perspective challenges current dysphonia analysis methods that...

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Automatic dysphonia recognition using biologically-inspired amplitude-modulation features

Estimating and evaluating confidence for forensic speaker recognition

January 1, 2005
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Conference Paper
Author:
William M. Campbell
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Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, Vol. 1, 19-23 March 2005, pp. I-717 - I-720.
Topic:
speaker recognition
R&D area:
R&D group:

Summary

Estimating and evaluating confidence has become a key aspect of the speaker recognition problem because of the increased use of this technology in forensic applications. We discuss evaluation measures for speaker recognition and some of their properties. We then propose a framework for confidence estimation based upon scores and metainformation, such as utterance duration, channel type, and SNR. The framework uses regression techniques with multilayer perceptrons to estimate confidence with a data-driven methodology. As an application, we show the use of the framework in a speaker comparison task drawn from the NIST 2000 evaluation. A relative comparison of different types of meta-information is given. We demonstrate that the new framework can give substantial improvements over standard distribution methods of estimating confidence.
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Summary

Estimating and evaluating confidence has become a key aspect of the speaker recognition problem because of the increased use of this technology in forensic applications. We discuss evaluation measures for speaker recognition and some of their properties. We then propose a framework for confidence estimation based upon scores and metainformation...

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Estimating and evaluating confidence for forensic speaker recognition

New measures of effectiveness for human language technology

January 1, 2005
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Journal Article
Author:
Douglas A. Jones
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Published in:
Lincoln Laboratory Journal, Vol. 15, No. 2, 2005, pp. 341-345.
Topic:
machine translation
R&D area:
R&D group:

Summary

The field of human language technology (HLT) encompasses algorithms and applications dedicated to processing human speech and written communication. We focus on two types of HLT systems: (1) machine translation systems, which convert text and speech files from one human language to another, and (2) speech-to-text (STT) systems, which produce text transcripts when given audio files of human speech as input. Although both processes are subject to machine errors and can produce varying levels of garbling in their output, HLT systems are improving at a remarkable pace, according to system-internal measures of performance. To learn how these system-internal measurements correlate with improved capabilities for accomplishing real-world language-understanding tasks, we have embarked on a collaborative, interdisciplinary project involving Lincoln Laboratory, the MIT Department of Brain and Cognitive Sciences, and the Defense Language Institute Foreign Language Center to develop new techniques to scientifically measure the effectiveness of these technologies when they are used by human subjects.
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Summary

The field of human language technology (HLT) encompasses algorithms and applications dedicated to processing human speech and written communication. We focus on two types of HLT systems: (1) machine translation systems, which convert text and speech files from one human language to another, and (2) speech-to-text (STT) systems, which produce...

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New measures of effectiveness for human language technology
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