ESASCF: Expertise Extraction, Generalization and Reply Framework for an Optimized Automation of Network Security Compliance

The Cyber threats exposure has created worldwide pressure on organizations to comply with cyber security standards and policies for protecting their digital assets. Vulnerability assessment (VA) and Penetration Testing (PT) are widely adopted Security Compliance (SC) methods to identify security gaps and anticipate security breaches. In the computer networks context and despite the use of autonomous tools and systems, security compliance remains highly repetitive and resources consuming. In this paper, we proposed a novel method to tackle the ever-growing problem of efficiency and effectiveness in network infrastructures security auditing by formally introducing, designing, and developing an Expert-System Automated Security Compliance Framework (ESASCF) that enables industrial and open-source VA and PT tools and systems to extract, process, store and re-use the expertise in a human-expert way to allow direct application in similar scenarios or during the periodic re-testing. The implemented model was then integrated within the ESASCF and tested on different size networks and proved efficient in terms of time-efficiency and testing effectiveness allowing ESASCF to take over autonomously the SC in Re-testing and offloading Expert by automating repeated segments SC and thus enabling Experts to prioritize important tasks in Ad-Hoc compliance tests. The obtained results validate the performance enhancement notably by cutting the time required for an expert to 50% in the context of typical corporate networks first SC and 20% in re-testing, representing a significant cost-cutting. In addition, the framework allows a long-term impact illustrated in the knowledge extraction, generalization, and re-utilization, which enables better SC confidence independent of the human expert skills, coverage, and wrong decisions resulting in impactful false negatives

Review of Natural Compounds for Potential Psoriasis Treatment

Psoriasis represents an immune-mediated disease with an unclear cause that\u27s marked by inflammation triggered by dysfunction in the immune system, which results in inflammation in various parts of the skin. There could be obvious symptoms, such as elevated plaques; these plaques may appear differently depending on the type of skin. This disease can cause inflammation in the elbows, lower back, scalp, knees, or other regions of the body. It can begin at any age, although it most commonly affects individuals between the ages of 50 and 60. Specific cells (such as T cells) have been observed to play an obvious role in the pathogenesis of psoriasis, in addition to specific immunological molecules such as TNF-, IL-12, IL-23, IL-17, and other molecules that can aid in the pathogenesis of psoriasis. So, during the past two decades, biologists have created chemical drugs that target these cells or molecules and therefore prevent the disease from occurring. Alefacept, efalizumab, Adalimumab, Ustekinumab, and Secukinumab are a few examples of chemical drugs. It was discovered that these chemical drugs have long-term side effects that can cause defects in the patient\u27s body, such as the development of the rare but life-threatening disorder progressive multifocal leukoencephalopathy (PCL). Its rapidly progressive infection of the central nervous system caused by the JC virus and other drugs may cause increased production of neutralising anti-drug antibodies (ADA) and the risk of infusion reactions like pruritus, flushing, hypertension, headache, and rash. So, our context intends to talk in our review about natural products or plants that may have therapeutic characteristics for this disease and may have few or no side effects on the patient\u27s body

Hybrid active damping of LCL-filtered grid connected converter

A method for hybrid active damping in power converters connected to a weak grid using an LCL filter is proposed. It uses feedback of the grid current and capacitor voltage and is derived as an equivalent to the capacitor current feedback active damping method. A co-design procedure for the grid current controller with the proposed hybrid active damping method is presented. The robustness, system bandwidth and harmonic rejection are studied. The proposed method is applied to a single grid connected converter with variable grid inductance to investigate its ability to damp different system resonance frequencies and its effectiveness is verified via frequency domain analysis and time domain simulation

Synthesis and Characterizations of Titanium Tungstosilicate and Tungstophosphate Mesoporous Materials

The work reports a development approach for the synthesis of novel multi-components mesoporous materials of titanium tungstate (meso-TiW) titanium tungstosilicate (meso-TiWSi) and tungstophosphate (meso-TiWP) mixed oxides that have high surface area and ordered mesoporous structures at nanometer length scale. Using the solvent evaporation-induced self-assembly (EISA) new oxides of bi- and tri-component of meso-TiW, meso-TiWSi and meso-TiWP oxides with different compositions and porosity were achieved. The physicochemical properties of the mesoporous oxides were characterized by X-ray diffraction, BET surface area analyzer, scanning, and transmission electron microscopes. Subject to the oxide composition, the obtained meso-TiW, meso-TiWSi and meso-TiWP exhibits high surface area, ordered 2D hexagonal mesostructured with order channels extended over a large area. The produced meso-TiW, meso-TiWSi, and meso-TiWP adsorbents exhibit good adsorption efficiency for the removal of Pb(II), Cd(II) and Hg(II) ions from water solution due to the presence of high surface area and accessibility of surface active sites. The adsorption efficiency of these mesoporous oxide reaches up to 95% and is found to be dependent contact time and adsorbents dose. The synthesis strategy is particularly advantageous for the production of new complex (multi-component) inorganic mesoporous materials that might have an application in the field of environmental, catalysis or energy storage and production

Grid impedance estimation for islanding detection and adaptive control of converters

The grid impedance is time varying due to the changing structure of the power system configuration and it can have a considerable influence on the control and stability of grid connected converters. This paper presents an online grid impedance estimation method using the output switching current ripple of a SVPWM based grid connected converter. The proposed impedance estimation method is derived from the discretised system model using two consecutive samples within the switching period. The estimated impedance is used for islanding detection and online current controller parameter adaptation. Theoretical analysis and MATLAB simulation results are presented to verify the proposed method. The effectiveness of the grid impedance estimator is validated using experimental results

Reinforcement Learning for Intelligent Penetration Testing

Penetration testing (PT) is an active method for assessing and evaluating the security of digital assets by planning, generating and executing all possible attacks that can exploit existing vulnerabilities. Current PT practice is becoming repetitive, complex and resource consuming despite the use of automated tools. The goal of this paper is to design an intelligent PT approach using reinforcement learning (RL) that will allow regular and systematic testing, saving human resources. The system is modelled as a partially observed Markov decision process (POMDP), and tested using an external POMDP-solver with different algorithms. Although this paper is limited to only the planning phase and not the entire PT process, the results support the hypothesis that reinforcement learning can enhance PT beyond the capabilities of any human expert in terms of accurate and reliable outputs

Pramipexole protective effect on rotenone induced neurotoxicity in mice

Introduction: 
Pramipexole is a new dopaminergic drug which has been approved for PD treatment. However, we tried to find a new capacity for this drug rather than symptomatic effect. 

Materials and Methods: 
A chronic rotenone model with daily oral dose of 30mg/kg was induced in mice. Pramipexole was tried in a new approach where the treatment began in the middle of rotenone course with oral dose 1mg/kg/day of pramipexole. 

Results: 
Further analysis of behavioral tests and immunohistochemistry revealed success of pramipexole in improving the rotenone intoxicated mice. 

Conclusion: 
These results showed possible beneficial effects of pramipexole against rotenone-induced neurotoxicity

Hierarchical reinforcement learning for efficient and effective automated penetration testing of large networks

Penetration testing (PT) is a method for assessing and evaluating the security of digital assets by planning, generating, and executing possible attacks that aim to discover and exploit vulnerabilities. In large networks, penetration testing becomes repetitive, complex and resource consuming despite the use of automated tools. This paper investigates reinforcement learning (RL) to make penetration testing more intelligent, targeted, and efficient. The proposed approach called Intelligent Automated Penetration Testing Framework (IAPTF) utilizes model-based RL to automate sequential decision making. Penetration testing tasks are treated as a partially observed Markov decision process (POMDP) which is solved with an external POMDP-solver using different algorithms to identify the most efficient options. A major difficulty encountered was solving large POMDPs resulting from large networks. This was overcome by representing networks hierarchically as a group of clusters and treating each cluster separately. This approach is tested through simulations of networks of various sizes. The results show that IAPTF with hierarchical network modeling outperforms previous approaches as well as human performance in terms of time, number of tested vectors and accuracy, and the advantage increases with the network size. Another advantage of IAPTF is the ease of repetition for retesting similar networks, which is often encountered in real PT. The results suggest that IAPTF is a promising approach to offload work from and ultimately replace human pen testing

Parkinson's Disease: Is It a Toxic Syndrome?

Parkinson's disease (PD) is one of the neurodegenerative diseases which we can by certainty identify its pathology, however, this confidence disappeares when talking about the cause. A long history of trials, suggestions, and theories tried linking PD to a specific causation. In this paper, a new suggestion is trying to find its way, could it be toxicology? Can we—in the future—look to PD as an occupational disease, in fact, many clues point to the possible toxic responsibility—either total or partial—in causing this disease. Searching for possible toxic causes for PD would help in designing perfect toxic models in animals

STUDYING THE PHENOMENON OF POVERTY IN THE COUNTRYSIDE OF THE DAHHAR DISTRICT IN YEMEN

This research aimed to study poverty in rural Yemen through the percentage, gap, and severity in addition to the standard economic analysis. The study showed that the poverty percent reached 97%, while the gap and severity reached 64, and 45% respectively. A study of the probability distribution of poverty indicators showed that the poverty percent ranged from a minimum of 95.4% to a high of 98.6% at a 95% confidence level. The poverty gap ranged from a low of 59.8% to a high of 68.2% at 95% confidence. The severity of poverty ranged from a minimum of 40.7% to a high of 49.3% at 95% confidence. These results of the study are emphasized on the need for the implementation of several policies. Among these two most important are (1) expanding the activity of NGOs to reduce poverty and hunger, (2) focusing on sustainable development and increasing the economic size of the agricultural sector and its relative importance to poverty reduction. To reduce poverty in the rural areas of the Republic of Yemen, the study recommends (1) the expansion of the activities of civil societies under government supervision to increase their ability to reduce poverty and hunger, (2) the provision of the necessary funding for the expansion of small investment projects that are commensurate with the capabilities and qualifications of poor families and (3) focusing on sustainable development of the agricultural sector is relative importance in reducing poverty