Methodologies for power analysis attacks on hardware implementations of AES

Side Channel Attacks (SCA) exploit weaknesses in implementations of cryptographic functions resulting from unintended inputs and outputs such as execution timing, power consumption, electromagnetic radiation, thermal and acoustic emanations. Power Analysis Attacks (PAA) are a type of SCA in which an attacker measures the power consumption of a cryptographic device during normal execution. An attempt is then made to uncover a relationship between the instantaneous power consumption and secret key information. PAAs can be subdivided into Simple Power Analysis (SPA), Differential Power Analysis (DPA), and Correlation Power Analysis (CPA). Many attacks have been documented since PAAs were first described in 1998. But since they often vary significantly, it is difficult to directly compare the vulnerability of the implementations used in each. Research is necessary to identify and develop standard methods of evaluating the vulnerability of cryptographic implementations to PAAs. This thesis defines methodologies for performing PAAs on hardware implementations of AES. The process is divided into identification, extraction, and evaluation stages. The extraction stage is outlined for both simulated power consumption waveforms as well as for waveforms captured from physical implementations. An AES encryption hardware design is developed for the experiment. The hardware design is synthesized with the Synopsys 130-nm CMOS standard cell library. Simulated instantaneous power consumption waveforms are generated with Synopsys PrimeTime PX. Single and multiple-bit DPA attacks are performed on the waveforms. Improvements are applied in order to automate and improve the precision and performance of the system. The attacks on the simulated power waveforms are successful. The correct key byte is identified in 15 of the 16 single-bit attacks after 10,000 traces. The single-bit attack which does not uniquely identify the correct key byte becomes successful after 15,000 or more traces are applied. The key byte is found in 36 of the 38 multiple-bit attacks. The main contribution of this work is a methodology and simulation environment which can be used to design hardware which is resistant to PAA and determine and compare vulnerability

Vertically Stratified Arthropod Diversity in a Florida Upland Hardwood Forest

Species diversity is typically higher in tropical forest canopies than in ground layers, but this pattern is absent in temperate forests. However, hardwood forests of Florida are typified by the intermingling of temperate and tropical species. It is thus unclear how diversity in Florida forests might be vertically stratified. This project is one of the first investigations to compare arthropod communities at varying layers (strata) of a Florida hardwood forest, from ground to canopy habitats. We installed terrestrial and arboreal pitfall traps to survey the arthropod community along a vertical gradient from the forest ground to upper canopy. We collected 830 arthropods from the 34 traps, amounting to 103 morphospecies across 15 orders. Coleoptera was the most morphospecious order, followed by Diptera, Araneae, and Hymenoptera. Species alpha diversity, richness, and abundance all decreased with height from the ground and horizontal distance from the tree. We discuss the vertical stratification of orders in addition to diversity metrics. This study is the first to reveal canopy strata effects on arthropod diversity in a Florida forest, and shows how diversity and composition changes along within site gradients.Killgore Research Center of West Texas AM University; Department of Life, Earth & Environmental Sciences at West Texas AM UniversityOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

DYNAMICS OF ENERGY TRANSFER IN LARGE ALUMINUM NANOPARTICLES: SIZE AND SURFACE DEPENDENT PHOTORESPONSES OF SOLUTION PROCESSED PARTICLES

Novel realizations of metal nanoparticles (NPs) are of continuing interest due to their unique optical properties and potential applications in optoelectronics, sensing, and catalysis. The unique and customizable optical properties of these particles make them ideally suited to act as light harvesters across the energy spectrum. Unlike bulk materials it is possible to modify metallic NP’s absorption characteristics simply by adjusting their size, shape, and medium in which they reside. Aluminum is an inexpensive earth-abundant plasmonic material and a promising alternative to noble metals for applications requiring UV sensitivity and scalability. The plasmon resonance of bulk aluminum metal falls in the ultraviolet, but the LSPRs of aluminum NPs have been tuned successfully to the visible and NIR In this work, time-resolved ultrafast broadband transient absorption spectroscopy has been used to study the relaxation dynamics associated with photoexcitation of plasmonic aluminum NP’s. Our Lab reported the first photophysical characterization of energy-transfer dynamics in large (100 nm diameter) plasmonic aluminum nanoparticles suspended in liquid isopropanol. Using a two-interface model, we find that a rapid thermal energy transfer from particle to solvent is accounted for by the presence of a compact ~4 nm native oxide layer on the aluminum nanoparticles. Size-dependent phonon “breathing”/vibrational modes are also observed as oscillations in total cross-section. We find that both the oscillation frequency and damping rate increase as the diameter of the particles decreases. Due to their rapid cooling, these particles are expected to be rather robust and could be utilized as an effective tool to engineer heat transfer rates from large particles to the surrounding medium

Economic impacts of climate change on water resources in the coterminous United States

A national-scale simulation-optimization model was created to generate estimates of economic impacts associated with changes in water supply and demand as influenced by climate change. Water balances were modeled for the 99 assessment sub-regions, and are presented for 18 water resource regions in the United States. Benefit functions are developed for irrigated agriculture, municipal and domestic water use, commercial and industrial water use, and hydroelectric power generation. Environmental flows below minimal levels required for environmental needs are assessed a penalty. As a demonstration of concept for the model, future climate is projected using a climate model ensemble for two greenhouse gas (GHG) emissions scenarios: a business-as-usual (BAU) scenario in which no new GHG controls are implemented, and an exemplary mitigation policy (POL) scenario in which future GHG emissions are mitigated. Damages are projected to grow less during the 21st century under the POL scenario than the BAU scenario. The largest impacts from climate change are projected to be on non-consumptive uses (e.g., environmental flows and hydropower) and relatively lower-valued consumptive uses (e.g., agriculture), as water is reallocated during reduced water availability conditions to supply domestic, commercial, and industrial uses with higher marginal values. Lower GHG concentrations associated with a mitigation policy will result in a smaller rise in temperature and thus less extensive damage to some water resource uses. However, hydropower, environmental flow penalty, and agriculture were shown to be sensitive to the change in runoff as well.United States. Environmental Protection Agency. Office of Atmospheric Programs (Contract #EP-W-07-072

CRYOGENIC UPPER STAGE SYSTEM SAFETY

NASA s Exploration Initiative will require development of many new systems or systems of systems. One specific example is that safe, affordable, and reliable upper stage systems to place cargo and crew in stable low earth orbit are urgently required. In this paper, we examine the failure history of previous upper stages with liquid oxygen (LOX)/liquid hydrogen (LH2) propulsion systems. Launch data from 1964 until midyear 2005 are analyzed and presented. This data analysis covers upper stage systems from the Ariane, Centaur, H-IIA, Saturn, and Atlas in addition to other vehicles. Upper stage propulsion system elements have the highest impact on reliability. This paper discusses failure occurrence in all aspects of the operational phases (Le., initial burn, coast, restarts, and trends in failure rates over time). In an effort to understand the likelihood of future failures in flight, we present timelines of engine system failures relevant to initial flight histories. Some evidence suggests that propulsion system failures as a result of design problems occur shortly after initial development of the propulsion system; whereas failures because of manufacturing or assembly processing errors may occur during any phase of the system builds process, This paper also explores the detectability of historical failures. Observations from this review are used to ascertain the potential for increased upper stage reliability given investments in integrated system health management. Based on a clear understanding of the failure and success history of previous efforts by multiple space hardware development groups, the paper will investigate potential improvements that can be realized through application of system safety principles

ADEPT, A Mechanically Deployable Re-Entry Vehicle System, Enabling Interplanetary CubeSat and Small Satellite Missions

There is growing interest for utilizing Small Satellites beyond low Earth orbit. A number of secondary CubeSat payload missions are planned at Mars, cis-Lunar Space, near Earth objects, and moons of the Gas Giants. Use of smaller systems may enable utilization of otherwise unused capacity of larger “host” missions. Development of re-entry systems that leverage and accommodate Small Satellite technology will substantially expand the range of mission applications by offering the capability for high speed entry or aerocapture at destinations with atmospheres. Deployable entry vehicles (DEVs) offer benefits over traditional rigid aeroshells including volume, mass and payload form factor. The Adaptive Deployable Entry and Placement Technology (ADEPT) offers such a delivery capability for Small Sat or CubeSat orbiter(s), in-situ elements, or landers. The ADEPT system can package with off the shelf CubeSat deployment systems (1U-16U) to offer a delivery capability for a single CubeSat or constellations. Furthermore, ADEPT can deliver the same science payload to a destination with a stowed diameter a factor of 3-4 times smaller than an equivalent rigid aeroshell, alleviating volumetric constraints on the secondary payload accommodation or primary carrier spacecraft bus. This paper will describe ADEPT’s current development status and define various interplanetary mission concepts in order to provide guidelines for potential Small Satellite payload developers and mission implementers

MT-HESS: an efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissues.

MOTIVATION: Analysing the joint association between a large set of responses and predictors is a fundamental statistical task in integrative genomics, exemplified by numerous expression Quantitative Trait Loci (eQTL) studies. Of particular interest are the so-called ': hotspots ': , important genetic variants that regulate the expression of many genes. Recently, attention has focussed on whether eQTLs are common to several tissues, cell-types or, more generally, conditions or whether they are specific to a particular condition. RESULTS: We have implemented MT-HESS, a Bayesian hierarchical model that analyses the association between a large set of predictors, e.g. SNPs, and many responses, e.g. gene expression, in multiple tissues, cells or conditions. Our Bayesian sparse regression algorithm goes beyond ': one-at-a-time ': association tests between SNPs and responses and uses a fully multivariate model search across all linear combinations of SNPs, coupled with a model of the correlation between condition/tissue-specific responses. In addition, we use a hierarchical structure to leverage shared information across different genes, thus improving the detection of hotspots. We show the increase of power resulting from our new approach in an extensive simulation study. Our analysis of two case studies highlights new hotspots that would remain undetected by standard approaches and shows how greater prediction power can be achieved when several tissues are jointly considered. AVAILABILITY AND IMPLEMENTATION: C[Formula: see text] source code and documentation including compilation instructions are available under GNU licence at http://www.mrc-bsu.cam.ac.uk/software/

Targeted genomic analysis reveals widespread autoimmune disease association with regulatory variants in the TNF superfamily cytokine signalling network.

BACKGROUND: Tumour necrosis factor (TNF) superfamily cytokines and their receptors regulate diverse immune system functions through a common set of signalling pathways. Genetic variants in and expression of individual TNF superfamily cytokines, receptors and signalling proteins have been associated with autoimmune and inflammatory diseases, but their interconnected biology has been largely unexplored. METHODS: We took a hypothesis-driven approach using available genome-wide datasets to identify genetic variants regulating gene expression in the TNF superfamily cytokine signalling network and the association of these variants with autoimmune and autoinflammatory disease. Using paired gene expression and genetic data, we identified genetic variants associated with gene expression, expression quantitative trait loci (eQTLs), in four peripheral blood cell subsets. We then examined whether eQTLs were dependent on gene expression level or the presence of active enhancer chromatin marks. Using these eQTLs as genetic markers of the TNF superfamily signalling network, we performed targeted gene set association analysis in eight autoimmune and autoinflammatory disease genome-wide association studies. RESULTS: Comparison of TNF superfamily network gene expression and regulatory variants across four leucocyte subsets revealed patterns that differed between cell types. eQTLs for genes in this network were not dependent on absolute gene expression levels and were not enriched for chromatin marks of active enhancers. By examining autoimmune disease risk variants among our eQTLs, we found that risk alleles can be associated with either increased or decreased expression of co-stimulatory TNF superfamily cytokines, receptors or downstream signalling molecules. Gene set disease association analysis revealed that eQTLs for genes in the TNF superfamily pathway were associated with six of the eight autoimmune and autoinflammatory diseases examined, demonstrating associations beyond single genome-wide significant hits. CONCLUSIONS: This systematic analysis of the influence of regulatory genetic variants in the TNF superfamily network reveals widespread and diverse roles for these cytokines in susceptibility to a number of immune-mediated diseases.The Intramural Research Program of the National Institute of Arthritis and Musculoskeletal and Skin Diseases and the National Library of Medicine of the US National Institutes of Health (Intramural Research Program) , Wellcome Trust (080327/Z/06/Z, 087007/Z/08/Z, 094227/Z/10/Z, Clinical PhD Programme, 079895, 076113 and 085475) , Medical Research Council (G0400929) , National Institute for Health Research , National Institutes of Health (Oxford-Cambridge Scholars Program) , Istanbul University Research Fund and UK Behcet’s Syndrome Society.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13073-016-0329-