Cyber Infrastructure Protection: Vol. II

View the Executive SummaryIncreased reliance on the Internet and other networked systems raise the risks of cyber attacks that could harm our nation’s cyber infrastructure. The cyber infrastructure encompasses a number of sectors including: the nation’s mass transit and other transportation systems; banking and financial systems; factories; energy systems and the electric power grid; and telecommunications, which increasingly rely on a complex array of computer networks, including the public Internet. However, many of these systems and networks were not built and designed with security in mind. Therefore, our cyber infrastructure contains many holes, risks, and vulnerabilities that may enable an attacker to cause damage or disrupt cyber infrastructure operations. Threats to cyber infrastructure safety and security come from hackers, terrorists, criminal groups, and sophisticated organized crime groups; even nation-states and foreign intelligence services conduct cyber warfare. Cyber attackers can introduce new viruses, worms, and bots capable of defeating many of our efforts. Costs to the economy from these threats are huge and increasing. Government, business, and academia must therefore work together to understand the threat and develop various modes of fighting cyber attacks, and to establish and enhance a framework to assess the vulnerability of our cyber infrastructure and provide strategic policy directions for the protection of such an infrastructure. This book addresses such questions as: How serious is the cyber threat? What technical and policy-based approaches are best suited to securing telecommunications networks and information systems infrastructure security? What role will government and the private sector play in homeland defense against cyber attacks on critical civilian infrastructure, financial, and logistical systems? What legal impediments exist concerning efforts to defend the nation against cyber attacks, especially in preventive, preemptive, and retaliatory actions?https://press.armywarcollege.edu/monographs/1527/thumbnail.jp

Diasporic virginities: social representations of virginity and identity formation amongst British arab muslim women

This study compares how practising and non-practising British Arab Muslim women position themselves in relation to representations of virginity. Overall, in our qualitative study, we found that representations of culture and religion influenced social practices and social beliefs in different ways: non-practising Muslim women felt bound by culture to remain virgins, while practising Muslim women saw it as a religious obligation but were still governed by culture regarding the consequences of engaging in premarital sex. Interestingly, some practising Muslim participants used Mut’a (a form of temporary ‘marriage’) to justify premarital sex. This, however, did not diminish the importance of virginity in their understanding and identification as Arab women. In fact, this study found that virginity, for the British Arabs interviewed, embodied a sense of ‘Arabness’ in British society. Positioning themselves as virgins went beyond simply honour; it was a significant cultural symbol that secured their sense of cultural identity. In fact this cultural identity was often so powerful that it overrode their Islamic identities, prescribing their behaviour even if religion was seen as more ‘forgiving’

Verification of real-time DEVS models

Discrete Event System Specification (DEVS) has been widely used to describe hierarchical models of discrete systems. DEVS has also been used successfully to model with Real-Time constraints. In this paper, we introduce a methodology to verify Real-Time DEVS models, and describe the methodology by using a case study of a DEVS model of an elevator system. Our methodology applies recent advances in theoretical model checking to DEVS models. The methodology also handles the cases where theoretical approach is not feasible to cross the gap between abstract Timed Automata models and the complexity of the DEVS Real-time implementation by empirical software engineering methods. The case study is a system composed of an elevator along an elevator controller, and we show how the methodology can be applied to a real case like this one in order to improve the quality of such real-time applications

Principles of DEVS model verification for real-time embedded applications

Embedded real-time (RT) software systems are increasingly used in mission critical applications, where a failure of the system to deliver its function can be catastrophic. Currently existing RT engineering methodologies use modeling as a method to study and evaluate different system designs before building the target application. Having a system model enables the verification of system properties and functionality before building the actual system. In this way, deployed systems would have a very high reliability, as the formal verification permits detecting systems errors at the early stages of the design. To apply such methodologies for embedded control systems, a designer must abstract the physical system to be controlled and build a model for it. This model can then be combined with a model of the proposed controller design for study and evaluation

DEVS execution acceleration with machine learning

Discrete Event System Specification DEVS separates modeling and simulation execution. Simulation execution is done within a runtime environment that is often called a DEVS simulator. This separation creates an opportunity to incorporate smart algorithms in the simulator to optimize simulation execution. In this paper, we propose incorporating some predictive machine learning algorithms into the DEVS simulator that can cut simulation execution times significantly for many simulation applications without compromising the simulation accuracy. In this paper, we introduce a specific learning mechanism that can be embedded into the DEVS simulator to incrementally build a predictive model that learns from past simulations. We further look into issues related to the predictive model selection, its prediction accuracy, its effect on the overall simulation performance, and when to switch between the predictive model and the simulation during an execution

Prevalence of IgG antibodies for the West Nile virus in human population in Tripoli, Libya

Background & objectives: West Nile fever (WNF) is a mosquito-borne viral infection, circulated in natural cycles between birds and mosquitoes, particularly Culex species. It is transmitted to humans through mosquito bites, and causes a variety of clinical outcomes, ranging from asymptomatic or mild febrile illness to severe men in go encepha- litis with some fatalities observed in older or immunocompromised patients. West Nile virus (WNV) transmission is considerably influenced by environmental conditions; and abundance of avifauna and mosquitoes.There are very few reports on WNV exposure in individuals from Tripoli City in Libya. The main objective was to provide basic epidemiological information about the WNV seroprevalence in the human population of Tripoli. Methods: A total of 400 serum samples were collected from persons (123 females, 277 males; age range: 15-78 yr) approaching the Tripoli Reference Laboratory for the purpose of obtaining health certificate; during the period from August to October 2013. The presence of WNV IgG antibodies was evaluated by a commercial kit based on WNV immunoglobulin G (IgG) enzyme-linked immunosorbent assay (ELISA). Results: It was observed that 2.75% (11/400) samples were found reactive in the WNV ELISA assay. This result suggests that WNV has a low prevalence in the study area. Interpretation & conclusion: Seropositivity rates of WNV in Tripoli region of Libya were low. However, continu- ous monitoring of population is important to keep track of the disease prevalence, risk factors, reservoir hosts and vectors for better understaning of the disease epidemiology and designing appropriate control strategies