Annotated Bibliography for the DEWPOINT project

This bibliography covers aspects of the Detection and Early Warning of Proliferation from Online INdicators of Threat (DEWPOINT) project including 1) data management and querying, 2) baseline and advanced methods for classifying free text, and 3) algorithms to achieve the ultimate goal of inferring intent from free text sources. Metrics for assessing the quality and correctness of classification are addressed in the second group. Data management and querying include methods for efficiently storing, indexing, searching, and organizing the data we expect to operate on within the DEWPOINT project

Annotated Bibliography for the MATADOR Project

The MATADOR project is focused on developing methods to infer the operational mode of facilities that have the potential to be used in weapons development programs. Our central hypothesis is that by persistent, non-intrusive monitoring of such facilities, differences between various use scenarios can be reliably discovered. The impact of success in this area is that new tools and techniques for monitoring and treaty verification would make it easier to reliably discover and document weapons development activities. This document captures the literature that will serve as a basis to approach this task. The relevant literature is divided into topical areas that relate to the various aspects of expected MATADOR project development. We have found that very little work that is directly applicable for our purposes has been published, which has motivated the development of novel methods under the project. Therefore, the manuscripts referenced in this document were selected based on their potential use as foundational blocks for the methods we anticipate developing, or so that we can understand the limitations of existing methods

Evidence of the Generation of Isosaccharinic Acids and Their Subsequent Degradation by Local Microbial Consortia within Hyper-Alkaline Contaminated Soils, with Relevance to Intermediate Level Radioactive Waste Disposal

The contamination of surface environments with hydroxide rich wastes leads to the formation of high pH (>11.0) soil profiles. One such site is a legacy lime works at Harpur Hill, Derbyshire where soil profile indicated in-situ pH values up to pH 12. Soil and porewater profiles around the site indicated clear evidence of the presence of the α and β stereoisomers of isosaccharinic acid (ISA) resulting from the anoxic, alkaline degradation of cellulosic material. ISAs are of particular interest with regards to the disposal of cellulosic materials contained within the intermediate level waste (ILW) inventory of the United Kingdom, where they may influence radionuclide mobility via complexation events occurring within a geological disposal facility (GDF) concept. The mixing of uncontaminated soils with the alkaline leachate of the site resulted in ISA generation, where the rate of generation in-situ is likely to be dependent upon the prevailing temperature of the soil. Microbial consortia present in the uncontaminated soil were capable of surviving conditions imposed by the alkaline leachate and demonstrated the ability to utilise ISAs as a carbon source. Leachate-contaminated soil was sub-cultured in a cellulose degradation product driven microcosm operating at pH 11, the consortia present were capable of the degradation of ISAs and the generation of methane from the resultant H2/CO2 produced from fermentation processes. Following microbial community analysis, fermentation processes appear to be predominated by Clostridia from the genus Alkaliphilus sp, with methanogenesis being attributed to Methanobacterium and Methanomassiliicoccus sp. The study is the first to identify the generation of ISA within an anthropogenic environment and advocates the notion that microbial activity within an ILW-GDF is likely to influence the impact of ISAs upon radionuclide migration

Defending Our Public Biological Databases as a Global Critical Infrastructure

Progress in modern biology is being driven, in part, by the large amounts of freely available data in public resources such as the International Nucleotide Sequence Database Collaboration (INSDC), the world's primary database of biological sequence (and related) information. INSDC and similar databases have dramatically increased the pace of fundamental biological discovery and enabled a host of innovative therapeutic, diagnostic, and forensic applications. However, as high-value, openly shared resources with a high degree of assumed trust, these repositories share compelling similarities to the early days of the Internet. Consequently, as public biological databases continue to increase in size and importance, we expect that they will face the same threats as undefended cyberspace. There is a unique opportunity, before a significant breach and loss of trust occurs, to ensure they evolve with quality and security as a design philosophy rather than costly “retrofitted” mitigations. This Perspective surveys some potential quality assurance and security weaknesses in existing open genomic and proteomic repositories, describes methods to mitigate the likelihood of both intentional and unintentional errors, and offers recommendations for risk mitigation based on lessons learned from cybersecurity

Physicochemical property distributions for accurate and rapid pairwise protein homology detection

<p>Abstract</p> <p>Background</p> <p>The challenge of remote homology detection is that many evolutionarily related sequences have very little similarity at the amino acid level. Kernel-based discriminative methods, such as support vector machines (SVMs), that use vector representations of sequences derived from sequence properties have been shown to have superior accuracy when compared to traditional approaches for the task of remote homology detection.</p> <p>Results</p> <p>We introduce a new method for feature vector representation based on the physicochemical properties of the primary protein sequence. A distribution of physicochemical property scores are assembled from 4-mers of the sequence and normalized based on the null distribution of the property over all possible 4-mers. With this approach there is little computational cost associated with the transformation of the protein into feature space, and overall performance in terms of remote homology detection is comparable with current state-of-the-art methods. We demonstrate that the features can be used for the task of pairwise remote homology detection with improved accuracy versus sequence-based methods such as BLAST and other feature-based methods of similar computational cost.</p> <p>Conclusions</p> <p>A protein feature method based on physicochemical properties is a viable approach for extracting features in a computationally inexpensive manner while retaining the sensitivity of SVM protein homology detection. Furthermore, identifying features that can be used for generic pairwise homology detection in lieu of family-based homology detection is important for applications such as large database searches and comparative genomics.</p

Annotated Bibliography for the DEWPOINT project

This bibliography covers aspects of the Detection and Early Warning of Proliferation from Online INdicators of Threat (DEWPOINT) project including 1) data management and querying, 2) baseline and advanced methods for classifying free text, and 3) algorithms to achieve the ultimate goal of inferring intent from free text sources. Metrics for assessing the quality and correctness of classification are addressed in the second group. Data management and querying include methods for efficiently storing, indexing, searching, and organizing the data we expect to operate on within the DEWPOINT project

Final Report for Bio-Inspired Approaches to Moving-Target Defense Strategies

This report records the work and contributions of the NITRD-funded Bio-Inspired Approaches to Moving-Target Defense Strategies project performed by Pacific Northwest National Laboratory under the technical guidance of the National Security Agency’s R6 division. The project has incorporated a number of bio-inspired cyber defensive technologies within an elastic framework provided by the Digital Ants. This project has created the first scalable, real-world prototype of the Digital Ants Framework (DAF)[11] and integrated five technologies into this flexible, decentralized framework: (1) Ant-Based Cyber Defense (ABCD), (2) Behavioral Indicators, (3) Bioinformatic Clas- sification, (4) Moving-Target Reconfiguration, and (5) Ambient Collaboration. The DAF can be used operationally to decentralize many such data intensive applications that normally rely on collection of large amounts of data in a central repository. In this work, we have shown how these component applications may be decentralized and may perform analysis at the edge. Operationally, this will enable analytics to scale far beyond current limitations while not suffering from the bandwidth or computational limitations of centralized analysis. This effort has advanced the R6 Cyber Security research program to secure digital infrastructures by developing a dynamic means to adaptively defend complex cyber systems. We hope that this work will benefit both our client’s efforts in system behavior modeling and cyber security to the overall benefit of the nation

Final Report for Bio-Inspired Approaches to Moving-Target Defense Strategies

This report records the work and contributions of the NITRD-funded Bio-Inspired Approaches to Moving-Target Defense Strategies project performed by Pacific Northwest National Laboratory under the technical guidance of the National Security Agency’s R6 division. The project has incorporated a number of bio-inspired cyber defensive technologies within an elastic framework provided by the Digital Ants. This project has created the first scalable, real-world prototype of the Digital Ants Framework (DAF)[11] and integrated five technologies into this flexible, decentralized framework: (1) Ant-Based Cyber Defense (ABCD), (2) Behavioral Indicators, (3) Bioinformatic Clas- sification, (4) Moving-Target Reconfiguration, and (5) Ambient Collaboration. The DAF can be used operationally to decentralize many such data intensive applications that normally rely on collection of large amounts of data in a central repository. In this work, we have shown how these component applications may be decentralized and may perform analysis at the edge. Operationally, this will enable analytics to scale far beyond current limitations while not suffering from the bandwidth or computational limitations of centralized analysis. This effort has advanced the R6 Cyber Security research program to secure digital infrastructures by developing a dynamic means to adaptively defend complex cyber systems. We hope that this work will benefit both our client’s efforts in system behavior modeling and cyber security to the overall benefit of the nation