A Heuristic Featured Based Quantification Framework for Efficient Malware Detection. Measuring the Malicious intent of a file using anomaly probabilistic scoring and evidence combinational theory with fuzzy hashing for malware detection in Portable Executable files

Malware is still one of the most prominent vectors through which computer networks and systems are compromised. A compromised computer system or network provides data and or processing resources to the world of cybercrime. With cybercrime projected to cost the world $6 trillion by 2021, malware is expected to continue being a growing challenge. Statistics around malware growth over the last decade support this theory as malware numbers enjoy almost an exponential increase over the period. Recent reports on the complexity of the malware show that the fight against malware as a means of building more resilient cyberspace is an evolving challenge. Compounding the problem is the lack of cyber security expertise to handle the expected rise in incidents. This thesis proposes advancing automation of the malware static analysis and detection to improve the decision-making confidence levels of a standard computer user in regards to a file’s malicious status. Therefore, this work introduces a framework that relies on two novel approaches to score the malicious intent of a file. The first approach attaches a probabilistic score to heuristic anomalies to calculate an overall file malicious score while the second approach uses fuzzy hashes and evidence combination theory for more efficient malware detection. The approaches’ resultant quantifiable scores measure the malicious intent of the file. The designed schemes were validated using a dataset of “clean” and “malicious” files. The results obtained show that the framework achieves true positive – false positive detection rate “trade-offs” for efficient malware detection

Similarity hash based scoring of portable executable files for efficient malware detection in IoT

YesThe current rise in malicious attacks shows that existing security systems are bypassed by malicious files. Similarity hashing has been adopted for sample triaging in malware analysis and detection. File similarity is used to cluster malware into families such that their common signature can be designed. This paper explores four hash types currently used in malware analysis for portable executable (PE) files. Although each hashing technique produces interesting results, when applied independently, they have high false detection rates. This paper investigates into a central issue of how different hashing techniques can be combined to provide a quantitative malware score and to achieve better detection rates. We design and develop a novel approach for malware scoring based on the hashes results. The proposed approach is evaluated through a number of experiments. Evaluation clearly demonstrates a significant improvement (> 90%) in true detection rates of malware

Human eosinophils modulate peripheral blood mononuclear cell response to Schistosoma mansoni adult worm antigen in vitro.

High numbers of eosinophils are observed in parasitic infections and allergic diseases, where they are proposed to be terminally differentiated effector cells that play beneficial role in host defence, or cause harmful inflammatory response. Eosinophils have been associated with killing of schistosomulae in vitro, but there is growing evidence that eosinophils can play additional immuno-regulatory role. Here, we report results of a study that examines peripheral blood mononuclear cell (PBMC) cytokine responses to Schistosoma mansoni adult worm antigen (SWA) when stimulated alone or enriched with autologous eosinophils. Production of the Th-2 type cytokines interleukin (IL)-4, IL-5 and IL-13 was lower (P = 0·017, 0·018 and <0·001, respectively) in PBMC + eosinophil cultures than in PBMC-only cultures stimulated with SWA. Substantial levels of IL-13, IL-10, interferon gamma and tumour necrosis factor alpha were recorded in cultures of eosinophils, but none of these cytokines showed significant association with the observed eosinophil-induced drop in cytokine responses of PBMC. Transwell experiments suggested that the observed effect is due to soluble mediators that downmodulate production of Th-2 type cytokines. This study shows that eosinophils may down-modulate schistosome-specific Th-2 type cytokine responses in S. mansoni-infected individuals. The mechanism of this immune modulation remains to be elucidated.The study was a fellowship funded by Wellcome Trust, Makerere-UVRI Research Training Programme in Infection and Immunity (grant number 084344) and European Foundations Initiative for NTDs ‘EFINTD’ (grant ref 86 529). The study was carried out under co-infection studies programme lead by AME funded by Wellcome Trust (grant number 095778)

Cyber-Attack Modeling Analysis Techniques: An Overview

YesCyber attack is a sensitive issue in the world of Internet security. Governments and business organisations around the world are providing enormous effort to secure their data. They are using various types of tools and techniques to keep the business running, while adversaries are trying to breach security and send malicious software such as botnets, viruses, trojans etc., to access valuable data. Everyday the situation is getting worse because of new types of malware emerging to attack networks. It is important to understand those attacks both before and after they happen in order to provide better security to our systems. Understanding attack models provide more insight into network vulnerability; which in turn can be used to protect the network from future attacks. In the cyber security world, it is difficult to predict a potential attack without understanding the vulnerability of the network. So, it is important to analyse the network to identify top possible vulnerability list, which will give an intuitive idea to protect the network. Also, handling an ongoing attack poses significant risk on the network and valuable data, where prompt action is necessary. Proper utilisation of attack modelling techniques provide advance planning, which can be implemented rapidly during an ongoing attack event. This paper aims to analyse various types of existing attack modelling techniques to understand the vulnerability of the network; and the behaviour and goals of the adversary. The ultimate goal is to handle cyber attack in efficient manner using attack modelling techniques

Ploidy level of the banana (Musa spp.) accessions at the germplasm collection centre for the East and Central Africa

Banana germplasm collections serves as a source of useful genes for banana breeding. However, insufficient and/or inaccurate information on the ploidy level of the germplasm renders its utilization in breeding difficult. The objective of this study was to determine and validate the ploidy level of 120 banana accessions in the ex situ germplasm collection centre for the East and Central Africa, located in Mbarara, Uganda. Flow cytometric analysis of the nuclear DNA content was used to determine the ploidy level of the accessions. Results indicate that accessions: Bura, Diana, Kambani-Rungwe, Paji and Pagatau, and Rungwe that were previously classified as diploids are actually triploids, whereas Selangor previously known to be a diploid is a tetraploid. Accessions such as Galeo, Mwitupemba and Ntindi 1 that were previously classified as triploids were found diploids. GT, FHIA 25 and Muzungu Mwekundu that were considered as tetraploids, were found triploids. The information generated will guide correct placement of these accessions in the regional germplasm collection centre for the East and Central Africa and their utilization in banana breeding

Selection of cooking banana genotypes for yield and black Sigatoka resistance in different locations in Uganda

It is imperative to systematically evaluate new banana genotypes in different locations before national release. This enables selection and recommendation of superior genotypes as new varieties for a wider range of environments. The objective of the present study was to select banana genotypes with stable and high performance for bunch yield and leaf black Sigatoka resistance. Eleven cooking banana genotypes developed by the Uganda National Agricultural Research Organization in collaboration with Bioversity International, and two check varieties were evaluated in multi-location preliminary yield trials in Uganda. Data collected were analyzed using Additive Main Effects and Multiplicative Interaction (AMMI) model, AMMI Stability Value, and Genotype Selection Index (GSI). Genotype × location interaction was significant for all the traits assessed. Most of the new genotypes had low interaction effects with locations for bunch yield (69.2%) and black Sigatoka (92.3%). The most stable genotypes for bunch yield were NABIO815, NABIO1117, NABIO216 and NABIO306 whereas for black Sigatoka resistance, were NABIO1011, NABIO815, NABIO1009 and NABIO216. Using the GSI that defines the most desirable genotypes as those that combine high agronomic performance and stability across environments, four genotypes (NABIO306, NABIO1011, NABIO808 and NABIO1009) were selected. These genotypes, in addition to their high performance for agronomic traits and stability, had soft and yellow fruit pulp on cooking, and will be advanced on farm for further evaluatio

Socio-economic and environmental factors affecting breastfeeding and complementary feeding practices among Batwa and Bakiga communities in south-western Uganda

Improving breastfeeding and complementary feeding practices is needed to support good health, enhance child growth, and reduce child mortality. Limited evidence is available on child feeding among Indigenous communities and in the context of environmental changes. We investigate past and present breastfeeding and complementary feeding practices within Indigenous Batwa and neighbouring Bakiga populations in south-western Uganda. Specifically, we describe the demographic and socio-economic characteristics of breastfeeding mothers and their children, and individual experiences of breastfeeding and complementary feeding practices. We investigate the factors that have an impact on breastfeeding and complementary feeding at community and societal levels, and we analysed how environments, including weather variability, affect breastfeeding and complementary feeding practices. We applied a mixed-method design to the study, and we used a community-based research approach. We conducted 94 individual interviews (n = 47 Batwa mothers/caregivers & n = 47 Bakiga mothers/caregivers) and 12 focus group discussions (n = 6 among Batwa & n = 6 among Bakiga communities) from July to October 2019. Ninety-nine per cent of mothers reported that their youngest child was currently breastfed. All mothers noted that the child experienced at least one episode of illness that had an impact on breastfeeding. From the focus groups, we identified four key factors affecting breastfeeding and nutrition practices: marginalisation and poverty; environmental change; lack of information; and poor support. Our findings contribute to the field of global public health and nutrition among Indigenous communities, with a focus on women and children. We present recommendations to improve child feeding practices among the Batwa and Bakiga in south-western Uganda. Specifically, we highlight the need to engage with local and national authorities to improve breastfeeding and complementary feeding practices, and work on food security, distribution of lands, and the food environment. Also, we recommend addressing the drivers and consequences of alcoholism, and strengthening family planning programs

A Community-Based Approach to Integrating Socio, Cultural and Environmental Contexts in the Development of a Food Database for Indigenous and Rural Populations: The Case of the Batwa and Bakiga in South-Western Uganda

Comprehensive food lists and databases are a critical input for programs aiming to alleviate undernutrition. However, standard methods for developing them may produce databases that are irrelevant for marginalised groups where nutritional needs are highest. Our study provides a method for identifying critical contextual information required to build relevant food lists for Indigenous populations. For our study, we used mixed-methods study design with a community-based approach. Between July and October 2019, we interviewed 74 participants among Batwa and Bakiga communities in south-western Uganda. We conducted focus groups discussions (FGDs), individual dietary surveys and markets and shops assessment. Locally validated information on foods consumed among Indigenous populations can provide results that differ from foods listed in the national food composition tables; in fact, the construction of food lists is influenced by multiple factors such as food culture and meaning of food, environmental changes, dietary transition, and social context. Without using a community-based approach to understanding socio-environmental contexts, we would have missed 33 commonly consumed recipes and foods, and we would not have known the variety of ingredients’ quantity in each recipe, and traditional foraged foods. The food culture, food systems and nutrition of Indigenous and vulnerable communities are unique, and need to be considered when developing food lists

Understanding Weather and Hospital Admissions Patterns to Inform Climate Change Adaptation Strategies in the Healthcare Sector in Uganda

Background: Season and weather are associated with many health outcomes, which can influence hospital admission rates. We examined associations between hospital admissions (all diagnoses) and local meteorological parameters in Southwestern Uganda, with the aim of supporting hospital planning and preparedness in the context of climate change. Methods: Hospital admissions data and meteorological data were collected from Bwindi Community Hospital and a satellite database of weather conditions, respectively (2011 to 2014). Descriptive statistics were used to describe admission patterns. A mixed-effects Poisson regression model was fitted to investigate associations between hospital admissions and season, precipitation, and temperature. Results: Admission counts were highest for acute respiratory infections, malaria, and acute gastrointestinal illness, which are climate-sensitive diseases. Hospital admissions were 1.16 (95% CI: 1.04, 1.31; p = 0.008) times higher during extreme high temperatures (i.e., >95th percentile) on the day of admission. Hospital admissions association with season depended on year; admissions were higher in the dry season than the rainy season every year, except for 2014. Discussion: Effective adaptation strategy characteristics include being low-cost and quick and practical to implement at local scales. Herein, we illustrate how analyzing hospital data alongside meteorological parameters may inform climate-health planning in low-resource contexts

Developing an online food composition database for an Indigenous population in south-western Uganda

Objective: To develop an online food composition database of locally consumed foods among an Indigenous population in south-western Uganda. Design: Using a community-based approach and collaboration with local nutritionists, we collected a list of foods for inclusion in the database through focus group discussions, an individual dietary survey and markets and shops assessment. The food database was then created using seven steps: identification of foods for inclusion in the database; initial data cleaning and removal of duplicate items; linkage of foods to existing generic food composition tables; mapping and calculation of the nutrient content of recipes and foods; allocating portion sizes and accompanying foods; quality checks with local and international nutritionists; and translation into relevant local languages. Setting: Kanungu District, south-western Uganda. Participants: Seventy-four participants, 36 Indigenous Batwa and 38 Bakiga, were randomly selected and interviewed to inform the development of a food list prior the construction of the food database. Results: We developed an online food database for south-western Uganda including 148 commonly consumed foods complete with values for 120 micronutrients and macronutrients. This was for use with the online dietary assessment tool myfood24. Of the locally reported foods included, 56 % (n 82 items) of the items were already available in the myfood24 database, while 25 % (n 37 items) were found in existing Ugandan and Tanzanian food databases, 18 % (n 27 items) came from generated recipes and 1 % (n 2 items) from food packaging labels. Conclusion: Locally relevant food databases are sparse for African Indigenous communities. Here, we created a tool that can be used for assessing food intake and for tracking undernutrition among the communities living in Kanungu District. This will help to develop locally relevant food and nutrition policies