Using Deep Learning Model for Network Scanning Detection

In recent years, new and devastating cyber attacks amplify the need for robust cybersecurity practices. Preventing novel cyber attacks requires the invention of Intrusion Detection Systems (IDSs), which can identify previously unseen attacks. Many researchers have attempted to produce anomaly - based IDSs, however they are not yet able to detect malicious network traffic consistently enough to warrant implementation in real networks. Obviously, it remains a challenge for the security community to produce IDSs that are suitable for implementation in the real world. In this paper, we propose a new approach using a Deep Belief Network with a combination of supervised and unsupervised machine learning methods for port scanning attacks detection - the task of probing enterprise networks or Internet wide services, searching for vulnerabilities or ways to infiltrate IT assets. Our proposed approach will be tested with network security datasets and compared with previously existing methods

Behaviour-aware Malware Classification: Dynamic Feature Selection

Despite the continued advancements in security research, malware persists as being a major threat in this digital age. Malware detection is a primary defence strategy for most networks but the identification of malware strains is becoming increasingly difficult. Reliable identification is based upon characteristic features being detectable within an object. However, the limitations and expense of current malware feature extraction methods is significantly hindering this process. In this paper, we present a new method for identifying malware based on behavioural feature extraction. Our proposed method has been evaluated using seven classification methods whilst analysing 2,068 malware samples from eight different families. The results achieved thus far have demonstrated promising improvements over existing approaches

Efficient methane dry reforming process with low nickel loading for greenhouse gas mitigation

In this study, a series of nickels supported on gamma alumina with a metal dosage ranging from 0.5 to 3 wt.% were prepared and employed as the catalysts. The effect of nickel dosage on material properties, reaction performance, and catalyst deactivation was investigated. At a low dosage, the nickel-free having low metal-support interaction contributed significantly to the total active site. The basicity of the material was enhanced along with the increase in nickel loading. The presence of active metal showed a great impact at the beginning leading to big improvements in feedstock conversion. However, beyond a nickel dosage of 2 wt.%, further additions did not noticeably influence the reaction performance. Regarding catalyst deactivation, different carbon species were observed on catalyst surface, depending on the nickel dosage. Catalysts with less than 2 wt.% nickel exhibited amorphous carbon as the dominant morphology on the spent catalyst. In contrast, catalysts with 2Ni/Al2O3 and 3Ni/Al2O3 compositions showed graphitic carbon as the main side product. These findings provide insights into the relationship between nickel dosage, catalyst properties, and catalytic performance in methane dry reforming. By understanding the effects of nickel loading on material properties and reaction behavior, researchers can optimize catalyst design and develop more efficient and stable catalysts for sustainable syngas production

Carbon dioxide reforming of methane over modified iron-cobalt alumina catalyst : Role of promoter

Cobalt-based catalysts are widely employed in methane dry reforming but tend to deactivate quickly due to coke deposits and metal sintering. To enhance the performance, iron, a cost-effective promoter, is added, improving cobalt's metal dispersibility, reducibility, and basicity on the support. This addition accelerates carbon gasification, effectively inhibiting coke deposition. Methods: A series of iron-doped cobalt alumina MFe-5Co/Al2O3 (M= 0, 0.4, 0.8, 1, 2 wt.%) were prepared via simple incipient-wetness impregnation. The catalysts were thoroughly characterized via modern techniques including BET, XRD, H2-TPR, CO2-TPD. Significant findings: The addition of iron had a minimal impact on the properties of γ-Al2O3, but it significantly affected the dispersibility of cobalt. At an optimal dosage of 0.8 wt.%, there was a notable decrease of 29.44% in Co3O4 particle size. However, excessive iron loading induced agglomeration of Co3O4, which was reversible. The presence of iron also resulted in a decrease in the reduction temperature of Co3O4. The material's basicity was primarily influenced by the loading of iron, reaching its highest value of 705.7 μmol CO2 g−1 in the 2Fe-5Co/Al2O3. The correlation between catalytic activity and the physicochemical properties of the material was established. The 0.8Fe-5Co/Al2O3 sample exhibited excellent performance due to the favorable dispersibility of cobalt, its reducibility, and its affordable basicity

Dual Supramolecular Nanoparticle Vectors Enable CRISPR/Cas9-Mediated Knockin of Retinoschisin 1 Gene-A Potential Nonviral Therapeutic Solution for X-Linked Juvenile Retinoschisis.

The homology-independent targeted integration (HITI) strategy enables effective CRISPR/Cas9-mediated knockin of therapeutic genes in nondividing cells in vivo, promising general therapeutic solutions for treating genetic diseases like X-linked juvenile retinoschisis. Herein, supramolecular nanoparticle (SMNP) vectors are used for codelivery of two DNA plasmids-CRISPR-Cas9 genome-editing system and a therapeutic gene, Retinoschisin 1 (RS1)-enabling clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 9 (CRISPR/Cas9) knockin of the RS1 gene with HITI. Through small-scale combinatorial screenings, two SMNP vectors, with Cas9 and single guide RNA (sgRNA)-plasmid in one and Donor-RS1 and green fluorescent protein (GFP)-plasmid in the other, with optimal delivery performances are identified. These SMNP vectors are then employed for CRISPR/Cas9 knockin of RS1/GFP genes into the mouse Rosa26 safe-harbor site in vitro and in vivo. The in vivo study involves intravitreally injecting the two SMNP vectors into the mouse eyes, followed by repeated ocular imaging by fundus camera and optical coherence tomography, and pathological and molecular analyses of the harvested retina tissues. Mice ocular organs retain their anatomical integrity, a single-copy 3.0-kb RS1/GFP gene is precisely integrated into the Rosa26 site in the retinas, and the integrated RS1/GFP gene is expressed in the retinas, demonstrating CRISPR/Cas9 knockin of RS1/GFP gene

Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: a comparative risk assessment

Background High blood pressure, blood glucose, serum cholesterol, and BMI are risk factors for cardiovascular diseases and some of these factors also increase the risk of chronic kidney disease and diabetes. We estimated mortality from cardiovascular diseases, chronic kidney disease, and diabetes that was attributable to these four cardiometabolic risk factors for all countries and regions from 1980 to 2010. Methods We used data for exposure to risk factors by country, age group, and sex from pooled analyses of populationbased health surveys. We obtained relative risks for the eff ects of risk factors on cause-specifi c mortality from metaanalyses of large prospective studies. We calculated the population attributable fractions for- each risk factor alone, and for the combination of all risk factors, accounting for multicausality and for mediation of the eff ects of BMI by the other three risks. We calculated attributable deaths by multiplying the cause-specifi c population attributable fractions by the number of disease-specifi c deaths. We obtained cause-specifi c mortality from the Global Burden of Diseases, Injuries, and Risk Factors 2010 Study. We propagated the uncertainties of all the inputs to the fi nal estimates. Findings In 2010, high blood pressure was the leading risk factor for deaths due to cardiovascular diseases, chronic kidney disease, and diabetes in every region, causing more than 40% of worldwide deaths from these diseases; high BMI and glucose were each responsible for about 15% of deaths, and high cholesterol for more than 10%. After accounting for multicausality, 63% (10\ub78 million deaths, 95% CI 10\ub71\u201311\ub75) of deaths from these diseases in 2010 were attributable to the combined eff ect of these four metabolic risk factors, compared with 67% (7\ub71 million deaths, 6\ub76\u20137\ub76) in 1980. The mortality burden of high BMI and glucose nearly doubled from 1980 to 2010. At the country level, age-standardised death rates from these diseases attributable to the combined eff ects of these four risk factors surpassed 925 deaths per 100 000 for men in Belarus, Kazakhstan, and Mongolia, but were less than 130 deaths per 100 000 for women and less than 200 for men in some high-income countries including Australia, Canada, France, Japan, the Netherlands, Singapore, South Korea, and Spain. Interpretation The salient features of the cardiometabolic disease and risk factor epidemic at the beginning of the 21st century are high blood pressure and an increasing eff ect of obesity and diabetes. The mortality burden of cardiometabolic risk factors has shifted from high-income to low-income and middle-income countries. Lowering cardiometabolic risks through dietary, behavioural, and pharmacological interventions should be a part of the globalresponse to non-communicable diseases