Cloud-Trust - A Security Assessment Model for Infrastructure as a Service (IaaS) Clouds

The vulnerability of Cloud Computing Systems (CCSs) to Advanced Persistent Threats (APTs) is a significant concern to government and industry. We present a cloud architecture reference model that incorporates a wide range of security controls and best practices, and a cloud security assessment model – Cloud-Trust – that estimates high level security metrics to quantify the degree of confidentiality and integrity offered by a CCS or cloud service provider (CSP). Cloud-Trust is used to assess the security level of four multi-tenant IaaS cloud architectures equipped with alternative cloud security controls and to show the probability of CCS penetration (high value data compromise) is high if a minimal set of security controls are implemented. CCS penetration probability drops substantially if a cloud defense in depth security architecture is adopted that protects virtual machine (VM) images at rest, strengthens CSP and cloud tenant system administrator access controls, and which employs other network security controls to minimize cloud network surveillance and discovery of live VMs

Organic and conventional agriculture: A comparison of conventional, manure, and legume systems on soil carbon, soil nitrogen, yield, and economic returns from a long term system in the mid-Atlantic

This thesis explores the effects and interactions of three systems of agricultural production: (1) conventional grain, (2) organic grain where fertility is supported by manure from dairy cows, and (3) organic grain where fertility is supported by leguminous crops. The data set included 28 years of comparative farming observations from the Rodale Institute\u27s Farming Systems Trial. Ordinary least squares (OLS) regressions were used to examine the effects of the cropping system on soil nitrogen and soil organic carbon. OLS regressions were used to examine the impact of the cropping systems on corn yield in conjunction with soil nitrogen and soil organic carbon. The manure and legume cropping systems were found to sequester more carbon than a conventional system. Overall, corn yields in the manure and legume systems were found to be 92.7% and 91.0% of the conventional system respectively. Following a 5 year transition period, manure and legume system yields were 95.9% 93.8% of conventional yields respectively. Corn yield was also analyzed in conjunction with plant genetics, weed pressure, and weather using a model where the weather variables were constructed based on the corn plant\u27s phenological stages of development. Conditional on these variables, the manure and legume systems were found to have 11.4% and 33.0% higher yields respectively, than the conventional system. Three years of cost and revenue data were used to estimate the level of organic premium needed for the organic and conventional systems to have economically equivalent returns. A 47.4% and 44.0% price premium was needed for the manure and legume systems respectively to maintain economic equivalence with the conventional system. Significant differences between the cropping systems were detected with respect to soil fertility, productivity and economic profitability

Future-proofing justice: building a research agenda to address the effects of technological change on the protection of constitutional rights

New technologies have changed the types of data that are routinely collected about citizens on a daily basis. For example, smart devices collect location and communication data, and fitness trackers and medical devices capture physiological and other data. As technology changes, new portable and connected devices have the potential to gather even more information. Such data have great potential utility in criminal justice proceedings, and they are already being used in case preparations, plea negotiations, and trials. But the broad expansion of technological capability also has the potential to stress approaches for ensuring that individuals\u27 constitutional rights are protected through legal processes. In an effort to consider those implications, we convened a panel of criminal justice practitioners, legal scholars, and individuals from the civil liberties community to identify research and other needs to prepare the U.S. legal system both for technologies we are seeing today and for technologies we are likely to see in the future. Through structured brainstorming, the panel explored a wide range of potential issues regarding these technologies, from evidentiary and procedural concerns to questions about the technologies\u27 accuracy and efficient use. Via a Delphi-based prioritization of the results, the panel crafted a research agenda — including best practice and training development, evaluation, and fundamental research efforts — to provide the criminal justice community with the knowledge and capabilities needed to address these important and complex technological questions going forward

Digital Forensics Compute Cluster: A High Speed Distributed Computing Capability for Digital Forensics

We have developed a distributed computing capability, Digital Forensics Compute Cluster (DFORC2) to speed up the ingestion and processing of digital evidence that is resident on computer hard drives. DFORC2 parallelizes evidence ingestion and file processing steps. It can be run on a standalone computer cluster or in the Amazon Web Services (AWS) cloud. When running in a virtualized computing environment, its cluster resources can be dynamically scaled up or down using Kubernetes. DFORC2 is an open source project that uses Autopsy, Apache Spark and Kafka, and other open source software packages. It extends the proven open source digital forensics capabilities of Autopsy to compute clusters and cloud architectures, so digital forensics tasks can be accomplished efficiently by a scalable array of cluster compute nodes. In this paper, we describe DFORC2 and compare it with a standalone version of Autopsy when both are used to process evidence from hard drives of different sizes