Dynamic Analysis of Executables to Detect and Characterize Malware

It is needed to ensure the integrity of systems that process sensitive information and control many aspects of everyday life. We examine the use of machine learning algorithms to detect malware using the system calls generated by executables-alleviating attempts at obfuscation as the behavior is monitored rather than the bytes of an executable. We examine several machine learning techniques for detecting malware including random forests, deep learning techniques, and liquid state machines. The experiments examine the effects of concept drift on each algorithm to understand how well the algorithms generalize to novel malware samples by testing them on data that was collected after the training data. The results suggest that each of the examined machine learning algorithms is a viable solution to detect malware-achieving between 90% and 95% class-averaged accuracy (CAA). In real-world scenarios, the performance evaluation on an operational network may not match the performance achieved in training. Namely, the CAA may be about the same, but the values for precision and recall over the malware can change significantly. We structure experiments to highlight these caveats and offer insights into expected performance in operational environments. In addition, we use the induced models to gain a better understanding about what differentiates the malware samples from the goodware, which can further be used as a forensics tool to understand what the malware (or goodware) was doing to provide directions for investigation and remediation.Comment: 9 pages, 6 Tables, 4 Figure

Preliminary - Representative Farm Analysis of House of Representatives Draft Concept Paper for 2002 Farm Bill

Agricultural and Food Policy,

Representative Farm Analysis of the H.R. 2646 Farm Bill Proposal

Agricultural and Food Policy,

GPS phase scintillation associated with optical auroral emissions:first statistical results from the geographic South Pole

Ionospheric irregularities affect the propagation of Global Navigation Satellite System (GNSS) signals, causing radio scintillation. Particle precipitation from the magnetosphere into the ionosphere, following solar activity, is an important production mechanism for ionospheric irregularities. Particle precipitation also causes the aurorae. However, the correlation of aurorae and GNSS scintillation events is not well established in literature. This study examines optical auroral events during 2010-2011 and reports spatial and temporal correlations with Global Positioning System (GPS) L1 phase fluctuations using instrumentation located at South Pole Station. An all-sky imager provides a measure of optical emission intensities ([OI] 557.7nm and 630.0nm) at auroral latitudes during the winter months. A collocated GPS antenna and scintillation receiver facilitates superimposition of auroral images and GPS signal measurements. Correlation statistics are produced by tracking emission intensities and GPS L1 sigma indices at E and F-region heights. This is the first time that multi-wavelength auroral images have been compared with scintillation measurements in this way. Correlation levels of up to 74% are observed during 2-3hour periods of discrete arc structuring. Analysis revealed that higher values of emission intensity corresponded with elevated levels of sigma. The study has yielded the first statistical evidence supporting the previously assumed relationship between the aurorae and GPS signal propagation. The probability of scintillation-induced GPS outages is of interest for commercial and safety-critical operations at high latitudes. Results in this paper indicate that image databases of optical auroral emissions could be used to assess the likelihood of multiple satellite scintillation activity

The trajectory of fidelity in a multiyear trial of the Family Check-Up predicts change in child problem behavior

Therapist fidelity to evidence-based family interventions has consistently been linked to child and family outcomes. However, few studies evaluate the potential ebb and flow of fidelity of therapists over time. We examined therapist drift in fidelity over four years in the context of a Family Check-Up prevention services in early childhood (age 2–5). At age 2, families engaging in Women, Infants, and Children Nutritional Supplement Program (WIC) services were randomized and offered annual Family Check-Ups. Seventy-nine families with a child in the clinical range of problem behaviors at age 2 were included in this analysis. Latent growth modeling revealed a significant linear decline in fidelity over time (M = ?0.35, SD = 0.35) and steeper declines were related to less improvement in caregiver-reported problem behaviors assessed at ages 7.5/8.5 (b = ?.69, p = .003; ? = ?.95, CI: ?2.11 | ?0.22). These findings add to the literature concerning the need to continually monitor therapist fidelity to an evidence-based practice over time to optimize family benefits. Limitations and directions for future research are discussed

Representative Farms Economic Outlook for the January 2001 FAPRI/AFPC Baseline

The farm level economic impacts of projected long term prices under the Federal Agriculture Improvement and Reform Act of 1996 (FAIR) on representative crop and livestock operations are projected in this report. For this report the FAIR Act will be referred to as the 1996 Farm Bill. The analysis was conducted over the 1996-2005 planning horizon using FLIPSIM, AFPC’s whole farm simulation model. Data to simulate farming operations in the nation’s major production regions came from two sources: - Producer panel cooperation to develop economic information to describe and simulate representative crop, livestock, and dairy farms. - Projected prices, policy variables, and input inflation rates from the Food and Agricultural Policy Research Institute (FAPRI) January 2001 Baseline. The primary objective of the analysis is to determine the farms’ economic viability by region and commodity throughout the life of the 1996 Farm Bill and beyond.Agribusiness, Agricultural and Food Policy, Crop Production/Industries,

Exploring the Use of Cost-Benefit Analysis to Compare Pharmaceutical Treatments for Menorrhagia

Background: The extra-welfarist theoretical framework tends to focus on health-related quality of life, whilst the welfarist framework captures a wider notion of well-being. EQ-5D and SF-6D are commonly used to value outcomes in chronic conditions with episodic symptoms, such as heavy menstrual bleeding (clinically termed menorrhagia). Because of their narrow-health focus and the condition’s periodic nature these measures may be unsuitable. A viable alternative measure is willingness to pay (WTP) from the welfarist framework. Objective: We explore the use of WTP in a preliminary cost-benefit analysis comparing pharmaceutical treatments for menorrhagia. Methods: A cost-benefit analysis was carried out based on an outcome of WTP. The analysis is based in the UK primary care setting over a 24-month time period, with a partial societal perspective. Ninety-nine women completed a WTP exercise from the ex-ante (pre-treatment/condition) perspective. Maximum average WTP values were elicited for two pharmaceutical treatments, levonorgestrel-releasing intrauterine system (LNG-IUS) and oral treatment. Cost data were offset against WTP and the net present value derived for treatment. Qualitative information explaining the WTP values was also collected. Results: Oral treatment was indicated to be the most cost-beneficial intervention costing £107 less than LNG-IUS and generating £7 more benefits. The mean incremental net present value for oral treatment compared with LNG-IUS was £113. The use of the WTP approach was acceptable as very few protests and non-responses were observed. Conclusion: The preliminary cost-benefit analysis results recommend oral treatment as the first-line treatment for menorrhagia. The WTP approach is a feasible alternative to the conventional EQ-5D/SF-6D approaches and offers advantages by capturing benefits beyond health, which is particularly relevant in menorrhagia