Quantifying Information Leaks Using Reliability Analysis

acmid: 2632367 keywords: Model Counting, Quantitative Information Flow, Reliability Analysis, Symbolic Execution location: San Jose, CA, USA numpages: 4acmid: 2632367 keywords: Model Counting, Quantitative Information Flow, Reliability Analysis, Symbolic Execution location: San Jose, CA, USA numpages: 4acmid: 2632367 keywords: Model Counting, Quantitative Information Flow, Reliability Analysis, Symbolic Execution location: San Jose, CA, USA numpages: 4We report on our work-in-progress into the use of reliability analysis to quantify information leaks. In recent work we have proposed a software reliability analysis technique that uses symbolic execution and model counting to quantify the probability of reaching designated program states, e.g. assert violations, under uncertainty conditions in the environment. The technique has many applications beyond reliability analysis, ranging from program understanding and debugging to analysis of cyber-physical systems. In this paper we report on a novel application of the technique, namely Quantitative Information Flow analysis (QIF). The goal of QIF is to measure information leakage of a program by using information-theoretic metrics such as Shannon entropy or Renyi entropy. We exploit the model counting engine of the reliability analyzer over symbolic program paths, to compute an upper bound of the maximum leakage over all possible distributions of the confidential data. We have implemented our approach into a prototype tool, called QILURA, and explore its effectiveness on a number of case studie

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Gravitational waves from spinning eccentric binaries

This paper is to introduce a new software called CBwaves which provides a fast and accurate computational tool to determine the gravitational waveforms yielded by generic spinning binaries of neutron stars and/or black holes on eccentric orbits. This is done within the post-Newtonian (PN) framework by integrating the equations of motion and the spin precession equations while the radiation field is determined by a simultaneous evaluation of the analytic waveforms. In applying CBwaves various physically interesting scenarios have been investigated. In particular, we have studied the appropriateness of the adiabatic approximation, and justified that the energy balance relation is indeed insensitive to the specific form of the applied radiation reaction term. By studying eccentric binary systems it is demonstrated that circular template banks are very ineffective in identifying binaries even if they possess tiny residual orbital eccentricity. In addition, by investigating the validity of the energy balance relation we show that, on contrary to the general expectations, the post-Newtonian approximation should not be applied once the post-Newtonian parameter gets beyond the critical value $\sim 0.08-0.1$. Finally, by studying the early phase of the gravitational waves emitted by strongly eccentric binary systems---which could be formed e.g. in various many-body interactions in the galactic halo---we have found that they possess very specific characteristics which may be used to identify these type of binary systems.Comment: 37 pages, 18 figures, submitted to Class. Quantum Gra

Effect of Selected Volatiles on Two Stored Pests: The Fungus Fusarium verticillioides and the Maize Weevil Sithophilus zeamais

New agronomic practices and technology enabled Argentina a larger production of cereal grains, reaching a harvest yield of 26.5 million metric tons of maize, of which, about 40% was exported. However, much of the maize production is lost annually by the attack of fungi and insects (2.6 million tons). In this study, the antifungal effect of selected volatiles on Fusarium verticillioides, its mycotoxin production, and the repellent and insecticidal activities against the weevill Sithophilus zeamais, an insect vector of F. verticillioides, were evaluated. The compounds tested were (2E)-2-hexenal, (2E)-2-nonenal,(2E,6Z)-2,6-nonadienal, 1-pentanol, 1-hexanol, 1-butanol, 3-methyl-1-butanol, pentanal, 2-decanone, and 3-decanone, which occur in the blend of volatile compounds emitted by various cereal grains. The most active antifungals were the aldehydes (2E)-2-nonenal, (2E)-2-hexenal, and (2E,6Z)-2,6-nonadienal (minimum inhibitory concentration values of <0.03, 0.06, and 0.06 mM,respectively). The occurrence of fumonisin B1 also was prevented because these compounds completely inhibited fungal growth.The best insecticidal fumigant activities against the maize weevil were shown by 2-decanone and 3-decanone (lethal concentration ≤ 54.6 μL/L (<0.28 mM)). Although, all tested compounds showed repellent activity against S. zeamais at a concentration of 4 μL/L, (2E,6Z)-2,6-nonadienal was the most active repellent compound. These results demonstrate the potential of (2E,6Z)-2,6-nonadienal to be used as a natural alternative to synthetic pesticides on F. verticillioides and S. zeamais.Fil: Zunino, María Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Herrera, Jimena María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); ArgentinaFil: Pizzolitto, Romina Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Rubinstein, Héctor Ramón. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones En Bioquímica Clínica E Inmunología; Argentina; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Zygadlo, Julio Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Dambolena, Jose Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); Argentina. Universidad Nacional de Córdoba; Argentin

Health inequalities in European cities: perceptions and beliefs among local policymakers

Objective: To describe the knowledge and beliefs of public policymakers on social inequalities in health and policies to reduce them in cities from different parts of Europe during 2010 and 2011. Design: Phenomenological qualitative study. Setting: 13 European cities. Participants: 19 elected politicians and officers with a directive status from 13 European cities. Main outcome: Policymaker’s knowledge and beliefs. Results: Three emerging discourses were identified among the interviewees, depending on the city of the interviewee. Health inequalities were perceived by most policymakers as differences in life-expectancy between population with economic, social and geographical differences. Reducing health inequalities was a priority for the majority of cities which use surveys as sources of information to analyse these. Bureaucracy, funding and population beliefs were the main barriers. Conclusions: The majority of the interviewed policymakers gave an account of interventions focusing on the immediate determinants and aimed at modifying lifestyles and behaviours in the more disadvantaged classes. More funding should be put towards academic research on effective universal policies, evaluation of their impact and training policymakers and officers on health inequalities in city government

Health System Support for Childbirth care in Southern Tanzania: Results from a Health Facility Census.

Progress towards reaching Millennium Development Goals four (child health) and five (maternal health) is lagging behind, particularly in sub-Saharan Africa, despite increasing efforts to scale up high impact interventions. Increasing the proportion of birth attended by a skilled attendant is a main indicator of progress, but not much is known about the quality of childbirth care delivered by these skilled attendants. With a view to reducing maternal mortality through health systems improvement we describe the care routinely offered in childbirth offered at dispensaries, health centres and hospitals in five districts in rural Southern Tanzania. We use data from a health facility census assessing 159 facilities in five districts in early 2009. A structural and operational assessment was undertaken based on staff reports using a modular questionnaire assessing staffing, work load, equipment and supplies as well as interventions routinely implemented during childbirth. Health centres and dispensaries attended a median of eight and four deliveries every month respectively. Dispensaries had a median of 2.5 (IQR 2--3) health workers including auxiliary staff instead of the recommended four clinical officer and certified nurses. Only 28% of first-line facilities (dispensaries and health centres) reported offering active management in the third stage of labour (AMTSL). Essential childbirth care comprising eight interventions including AMTSL, infection prevention, partograph use including foetal monitoring and newborn care including early breastfeeding, thermal care at birth and prevention of ophthalmia neonatorum was offered by 5% of dispensaries, 38% of health centres and 50% of hospitals consistently. No first-line facility had provided all signal functions for emergency obstetric complications in the previous six months. Essential interventions for childbirth care are not routinely implemented in first-line facilities or hospitals. Dispensaries have both low staffing and low caseload which constraints the ability to provide high-quality childbirth care. Improvements in quality of care are essential so that women delivering in facility receive "skilled attendance" and adequate care for common obstetric complications such as post-partum haemorrhage

SF Box - A tool for evaluating the effects on soil functions in remediation projects

Although remediation is usually aimed at reducing the risks posed by contaminants to human health and the environment, it is also desirable that the remediated soil within future green spaces is capable of providing relevant ecological functions, e.g. basis for primary production. While addressing a contamination problem by reducing contaminant concentration/amounts in the soil, the remedial action itself can lead to soil structure disturbances, decline in organic matter and nutrient deficiencies, and in turn affect a soil's capacity to carry out its ecological soil functions. This paper presents the SF Box (Soil Function Box) tool that is aimed to facilitate integration of information from suggested soil quality indicators (SQIs) into a management process in remediation using a scoring method. The scored SQIs are integrated into a soil quality index corresponding to one of five classes. SF Box is applied on two cases from Sweden (Kvillebäcken and Hexion), explicitly taking into consideration uncertainties in the results by means of Monte Carlo simulations. At both sites the generated soil quality indices corresponded to a medium soil performance (soil class 3) with a high certainty. The main soil constraints at both Kvillebäcken and Hexion were associated with biological activity in the soil, as soil organisms were unable to supply plant-available nitrogen. At the Kvillebäcken site the top layer had a content of coarse fragment (ø > 2mm) higher than 35%, indicating plant rooting limitations. At the Hexion site, the soil had limited amount of organic matter, thus poor aggregate stability and nutrient cycling potential. In contrast, the soil at Kvillebäcken was rich in organic matter. The soils at both sites were capable to store a sufficient amount of water for soil organisms between precipitations

Predictive Cyber Situational Awareness and Personalized Blacklisting: A Sequential Rule Mining Approach

Cybersecurity adopts data mining for its ability to extract concealed and indistinct patterns in the data, such as for the needs of alert correlation. Inferring common attack patterns and rules from the alerts helps in understanding the threat landscape for the defenders and allows for the realization of cyber situational awareness, including the projection of ongoing attacks. In this paper, we explore the use of data mining, namely sequential rule mining, in the analysis of intrusion detection alerts. We employed a dataset of 12 million alerts from 34 intrusion detection systems in 3 organizations gathered in an alert sharing platform, and processed it using our analytical framework. We execute the mining of sequential rules that we use to predict security events, which we utilize to create a predictive blacklist. Thus, the recipients of the data from the sharing platform will receive only a small number of alerts of events that are likely to occur instead of a large number of alerts of past events. The predictive blacklist has the size of only 3 % of the raw data, and more than 60 % of its entries are shown to be successful in performing accurate predictions in operational, real-world settings