Application of Digital Forensic Science to Electronic Discovery in Civil Litigation

Following changes to the Federal Rules of Civil Procedure in 2006 dealing with the role of Electronically Stored Information, digital forensics is becoming necessary to the discovery process in civil litigation. The development of case law interpreting the rule changes since their enactment defines how digital forensics can be applied to the discovery process, the scope of discovery, and the duties imposed on parties. Herein, pertinent cases are examined to determine what trends exist and how they effect the field. These observations buttress case studies involving discovery failures in large corporate contexts along with insights on the technical reasons those discovery failures occurred and continue to occur. The state of the art in the legal industry for handling Electronically Stored Information is slow, inefficient, and extremely expensive. These failings exacerbate discovery failures by making the discovery process more burdensome than necessary. In addressing this problem, weaknesses of existing approaches are identified, and new tools are presented which cure these defects. By drawing on open source libraries, components, and other support the presented tools exceed the performance of existing solutions by between one and two orders of magnitude. The transparent standards embodied in the open source movement allow for clearer defensibility of discovery practice sufficiency whereas existing approaches entail difficult to verify closed source solutions. Legacy industry practices in numbering documents based on Bates numbers inhibit efficient parallel and distributed processing of electronic data into paginated forms. The failures inherent in legacy numbering systems is identified, and a new system is provided which eliminates these inhibiters while simultaneously better modeling the nature of electronic data which does not lend itself to pagination; such non-paginated data includes databases and other file types which are machine readable, but not human readable in format. In toto, this dissertation provides a broad treatment of digital forensics applied to electronic discovery, an analysis of current failures in the industry, and a suite of tools which address the weaknesses, problems, and failures identified

Application of Digital Forensic Science to Electronic Discovery in Civil Litigation

Following changes to the Federal Rules of Civil Procedure in 2006 dealing with the role of Electronically Stored Information, digital forensics is becoming necessary to the discovery process in civil litigation. The development of case law interpreting the rule changes since their enactment defines how digital forensics can be applied to the discovery process, the scope of discovery, and the duties imposed on parties. Herein, pertinent cases are examined to determine what trends exist and how they effect the field. These observations buttress case studies involving discovery failures in large corporate contexts along with insights on the technical reasons those discovery failures occurred and continue to occur. The state of the art in the legal industry for handling Electronically Stored Information is slow, inefficient, and extremely expensive. These failings exacerbate discovery failures by making the discovery process more burdensome than necessary. In addressing this problem, weaknesses of existing approaches are identified, and new tools are presented which cure these defects. By drawing on open source libraries, components, and other support the presented tools exceed the performance of existing solutions by between one and two orders of magnitude. The transparent standards embodied in the open source movement allow for clearer defensibility of discovery practice sufficiency whereas existing approaches entail difficult to verify closed source solutions. Legacy industry practices in numbering documents based on Bates numbers inhibit efficient parallel and distributed processing of electronic data into paginated forms. The failures inherent in legacy numbering systems is identified, and a new system is provided which eliminates these inhibiters while simultaneously better modeling the nature of electronic data which does not lend itself to pagination; such non-paginated data includes databases and other file types which are machine readable, but not human readable in format. In toto, this dissertation provides a broad treatment of digital forensics applied to electronic discovery, an analysis of current failures in the industry, and a suite of tools which address the weaknesses, problems, and failures identified

Reconstructing Textual File Fragments Using Unsupervised Machine Learning Techniques

This work is an investigation into reconstructing fragmented ASCII files based on content analysis motivated by a desire to demonstrate machine learning\u27s applicability to Digital Forensics. Using a categorized corpus of Usenet, Bulletin Board Systems, and other assorted documents a series of experiments are conducted using machine learning techniques to train classifiers which are able to identify fragments belonging to the same original file. The primary machine learning method used is the Support Vector Machine with a variety of feature extractions to train from. Additional work is done in training committees of SVMs to boost the classification power over the individual SVMs, as well as the development of a method to tune SVM kernel parameters using a genetic algorithm. Attention is given to the applicability of Information Retrieval techniques to file fragments, as well as an analysis of textual artifacts which are not present in standard dictionaries

Thalamo-cortical communication, glutamatergic neurotransmission and neural oscillations:a unique window into the origins of ScZ?

The thalamus has recently received renewed interest in systems-neuroscience and schizophrenia (ScZ) research because of emerging evidence highlighting its important role in coordinating functional interactions in cortical-subcortical circuits. Moreover, higher cognitive functions, such as working memory and attention, have been related to thalamo-cortical interactions, providing a novel perspective for the understanding of the neural substrate of cognition. The current review will support this perspective by summarizing evidence on the crucial role of neural oscillations in facilitating thalamo-cortical (TC) interactions during normal brain functioning and their potential impairment in ScZ. Specifically, we will focus on the relationship between NMDA-R mediated (glutamatergic) neurotransmission in TC-interactions. To this end, we will first review the functional anatomy and neurotransmitters in thalamic circuits, followed by a review of the oscillatory signatures and cognitive processes supported by TC-circuits. In the second part of the paper, data from preclinical research as well as human studies will be summarized that have implicated TC-interactions as a crucial target for NMDA-receptor hypofunctioning. Finally, we will compare these neural signatures with current evidence from ScZ-research, suggesting a potential overlap between alterations in TC-circuits as the result of NMDA-R deficits and stage-specific alterations in large-scale networks in ScZ

Functional association of Sun1 with nuclear pore complexes

Sun1 and 2 are A-type lamin-binding proteins that, in association with nesprins, form a link between the inner nuclear membranes (INMs) and outer nuclear membranes of mammalian nuclear envelopes. Both immunofluorescence and immunoelectron microscopy reveal that Sun1 but not Sun2 is intimately associated with nuclear pore complexes (NPCs). Topological analyses indicate that Sun1 is a type II integral protein of the INM. Localization of Sun1 to the INM is defined by at least two discrete regions within its nucleoplasmic domain. However, association with NPCs is dependent on the synergy of both nucleoplasmic and lumenal domains. Cells that are either depleted of Sun1 by RNA interference or that overexpress dominant-negative Sun1 fragments exhibit clustering of NPCs. The implication is that Sun1 represents an important determinant of NPC distribution across the nuclear surface

Patient Visit Efficiency

By July 15, 2018 we will identify ways to decrease the amount of time our defined patient population spends in the practice for an appointment

Hybrid MM/SVM structural sensors for stochastic sequential data

In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-Intron (5' and 3') splice sites. We present the use of Markov based statistical methods, in a log likelihood discriminator framework, to create a non-summed, fixed-length, feature vector for SVM-based classification. We also explore the use of Shannon-entropy based analysis for automated identification of minimal-size models (where smaller models have known information loss according to the specified Shannon entropy representation). We evaluate a variety of kernels and kernel parameters in the classification effort. We present results of the algorithms for splice-site datasets consisting of sequences from a variety of species for comparison

Metatranscriptomic Sequencing of a Cyanobacterial Soil-Surface Consortium with and without a Diverse Underlying Soil Microbiome.

Soil surface consortia are easily observed and sampled, allowing examination of their interactions with soil microbiomes. Here, we present metatranscriptomic sequences from Dark Green 1 (DG1), a cyanobacterium-based soil surface consortium, in the presence and absence of an underlying soil microbiome and/or urea