Assessing network security through automated attack graph based multi-level penetration testing

Assessing network security can be done in many different ways like applying penetration testing against target network. Penetration testing follows actual steps like reconnaissance, scanning, exploit and logical access to compromised hosts. When attacker compromises a machine, he uses it as a pivot for attacking other machines and getting access to them. An attacker continues in this process till he explores the entire target network or till he reaches his endeavor. This shows that attacks are not a single step but, to reach attackers\u27 goal, the attacker has to go through multiple steps. Many of the available exploitation tools depend on single step that is to compromise the first vulnerable host and then deploy the attacking tools on the newly compromised host. Such tools use the compromised host as pivots to begin the attack steps again from the beginning. ft is as if the attacker moved with his attack tools arsenal from his current position to the new compromised hosts. In this thesis we are presenting a methodology that assists system administrators and penetration testers to secure their network by exploring and understanding their systems\u27 vulnerabilities and their inter-relations in an ethical way. A breadth-first search algorithm is used to automate penetration testing process to discover and compromise hosts on the target network. Hosts are compromised one after the other in a sequential manner so that we can build an attack graph that shows the actual attack path an attacker can take and the weak points in the network under evaluation. We have compared our methodology with other relevant methodologies and showed that we can automatically build a dynamic and realistic attack graph based on actual and current vulnerabilities with no prior information about the target network under evaluation

FAIR and bias-free network modules for mechanism-based disease redefinitions

Even though chronic diseases are the cause of 60% of all deaths around the world, the underlying causes for most of them are not fully understood. Hence, diseases are defined based on organs and symptoms, and therapies largely focus on mitigating symptoms rather than cure. This is also reflected in the most commonly used disease classifications. The complex nature of diseases, however, can be better defined in terms of networks of molecular interactions. This research applies the approaches of network medicine – a field that uses network science for identifying and treating diseases – to multiple diseases with highly unmet medical need such as stroke and hypertension. The results show the success of this approach to analyse complex disease networks and predict drug targets for different conditions, which are validated through preclinical experiments and are currently in human clinical trials

Autotransfusion in penetrating chest war trauma with haemothorax: The Keysaney Hospital experience

Background: In 1991 civil war broke out in Somalia and Mogadishu was divided into two areas, occupied by different clans. No hospital facility was available in  Mogadishu North to take care of the war wounded. The International Committee of the Red Cross (ICRC), together with the Somalia Red Crescent Society found a new building, 7 km North of the town, intended to be a prison: Keysaney Hospital was thus inaugurated in February 1992. It was soon established as The War Surgery Hospital in Somalia.Methods: This was a retrospective study. From 1992 to 2001,45,900 war-wounded patients were admitted and treated; among whom 13770 had chest injuries. Due to lack of a blood bank, insufficient number of donors, continuous need in emergency, life threatening situations and following previous positive experiences, a system was set up for immediate auto transfusion in patients with massive haemothorax from penetrating chest war wounds. To reduce the risk of the 2 major complications of sepsis and coagulopathy, each patient received antibiotic prophylaxis and only cases with a maximum delay of one hour were subjected to this form of management.Results: 137 patients had this kind of auto transfusion. There were five deaths (3.6% Mortality rate) No major complications were detected in the auto-transfused patients that survived.Key words: Auto transfusion, penetrating, chest, war wounds and haemothorax

The Relationship Between Metacognition and Self-regulation in Young Children

AbstractThe purpose of this study was to explore the relationship between theory of mind (ToM) (intention and false belief), metacognition, and self-regulation in preschool children. A related purpose was to investigate the gender and age differences. The sample of the study consisted of 87 preschool children in Southern Egypt. The instruments consisted of two theory-of-mind tasks (intention and false-belief situations), three tasks of metacognition and self- regulation (puzzle arrangement and sorting tasks). Metacognition and self-regulation tasks were evaluated using The Checklist of Independent Learning Development (CHILD, Whitebread et al., 2009). Correlations, t-test, and stepwise multiple regression analyses, using SPSS 18.0, were employed to answer the questions of the study. The results indicated no gender differences in the overall performance on the study variables. A developmental effect was found in favour of the older children in the intention task, puzzle arrangement task, and the total score of ToM. The second task predicted the false-belief task. The findings of the study are discussed and further venues for future research in this area are suggested

HEMA: A Proposed Robot for Improving Healthcare Access in Underserved Communities

Abstract- Healthcare access is a major challenge in underserved communities, where people often face barriers such as distance, cost, and lack of transportation. HEMA (Horus Expert Medical Assistant Robot) is a new technology with the potential to revolutionize healthcare access in underserved communities by providing basic healthcare services on-site. HEMA is a mobile, affordable, and easy-to-use robot that can collect patient data, diagnose common diseases, and provide basic treatment.HEMA can address the challenges of healthcare access in underserved communities in a number of ways. First, HEMA can provide healthcare services to people who live in remote areas and who may not have access to a traditional healthcare facility. Second, HEMA can provide affordable healthcare services to people who may not be able to afford to pay for healthcare out-of-pocket or who may not have health insurance. Third, HEMA can provide healthcare services to people who may have difficulty traveling to a traditional healthcare facility due to a disability or lack of transportation.HEMA has the potential to make a significant impact on the future of healthcare delivery in underserved communities. By providing basic healthcare services on-site, HEMA can help to improve access to care, reduce disparities in health outcomes, and improve the overall health and well-being of people in underserved communitie

HEMA: A Proposed Robot for Improving Healthcare Access in Underserved Communities

Abstract- Healthcare access is a major challenge in underserved communities, where people often face barriers such as distance, cost, and lack of transportation. HEMA (Horus Expert Medical Assistant Robot) is a new technology with the potential to revolutionize healthcare access in underserved communities by providing basic healthcare services on-site. HEMA is a mobile, affordable, and easy-to-use robot that can collect patient data, diagnose common diseases, and provide basic treatment.HEMA can address the challenges of healthcare access in underserved communities in a number of ways. First, HEMA can provide healthcare services to people who live in remote areas and who may not have access to a traditional healthcare facility. Second, HEMA can provide affordable healthcare services to people who may not be able to afford to pay for healthcare out-of-pocket or who may not have health insurance. Third, HEMA can provide healthcare services to people who may have difficulty traveling to a traditional healthcare facility due to a disability or lack of transportation.HEMA has the potential to make a significant impact on the future of healthcare delivery in underserved communities. By providing basic healthcare services on-site, HEMA can help to improve access to care, reduce disparities in health outcomes, and improve the overall health and well-being of people in underserved communitie

Evaluation of Carbon Dioxide sequestration in Malaysian coal seams

Sequestration projects are attempting to prevent the release oflarge quantities of C02 into the atmosphere from fossil fuel use in power generation and other industries by capturing C02, transporting it and ultimately, pumping it into underground geologic formations to securely store it away from the atmosphere. It is a potential means of mitigating the contribution of fossil fuel emissions to global warming. The process is based on capturing carbon dioxide (C02) from large point sources, such as fossil fuel power plants, and storing it where it will not enter the atmosphere. The interactions of C02 with coal will be investigated under a set of conditions to determine the effects of the nature of the coal and the sequestration environment including parameters such as rank and moisture content of the coal, the temperature, and pressure, And the effect of these parameters on the C02 adsorption capacity. Some sets of experiments are conducted based on the coal collected from two different basins across Malaysia and the best isotherm obtained based on the best adsorption capacity is selected to be the major basin where the carbon dioxide gas is to be sequestrated. Adsorption experiments were favorable at high pressure and low temperature conditions and the Temkin isotherm was selected to represent the adsorption behavior

Drivers of guest loyalty in the hotel industry in New Zealand: The role of staff loyalty, service quality, guest satisfaction and commitment, and the influence of loyalty programmes

This study focused on investigating the drivers of guest loyalty in the hotel industry. Specifically, the study further explored the role of staff loyalty, service quality, guest satisfaction and commitment, and the influence of loyalty programmes. The research methodology used both qualitative and quantitative methods in a two-step process comprising focus groups and self-administered surveys. Data collected from the focus groups were analyzed using CATPAC. The survey was developed from the information collected from the focus groups and a review of the literature. Data collected from the survey were analyzed using both regression and structural equation modeling. A model of guest loyalty drivers (GLDM) was proposed and validated in the study. The study contributes to the present body of knowledge in hospitality management theory as it investigated the drivers of guest loyalty. Results from the survey showed that loyalty programmes have a significant impact on guest loyalty more than staff loyalty and staff interaction, but guest satisfaction and guest affective commitment had more significant impact on guest loyalty than loyalty programmes. This study suggests some implications for hotel managers to consider before introducing or developing a loyalty programme. For example, the research shows that there are some gender differences in relation to loyalty programmes. Male guests look for better service, special treatment and collecting points, while female guests look mainly for price incentives and experiencing a unique stay. These findings indicate that hotel managers need to consider the use of different loyalty schemes for different guests. The model proposed in the study (GLDM) provided a new insight for academics and practitioners. Although, it was evident from the study that staff loyalty, staff interaction (as a dimension of service quality), guest satisfaction and commitment, and loyalty programmes are directly linked to and are capable of predicting guest loyalty in the hotel industry as drivers for guest loyalty. The study also indicates that hotel managers should not overlook staff attitude in preference to loyalty programmes; in the sense that, hotels should focus on developing interpersonal relationships between staff and guests. This study demonstrates that hotels should allocate more resources to relational marketing at both the beginning and throughout the relational exchange. The new model is of considerable interest to both academics and practioners alike; as it gives a new dimension to the interelationship between service, staff, satisfaction and guest loyalty, and lends itself to further research which will help gain a greater understanding of this interrelationship