An Integrated Cybersecurity Risk Management (I-CSRM) Framework for Critical Infrastructure Protection

Risk management plays a vital role in tackling cyber threats within the Cyber-Physical System (CPS) for overall system resilience. It enables identifying critical assets, vulnerabilities, and threats and determining suitable proactive control measures to tackle the risks. However, due to the increased complexity of the CPS, cyber-attacks nowadays are more sophisticated and less predictable, which makes risk management task more challenging. This research aims for an effective Cyber Security Risk Management (CSRM) practice using assets criticality, predication of risk types and evaluating the effectiveness of existing controls. We follow a number of techniques for the proposed unified approach including fuzzy set theory for the asset criticality, machine learning classifiers for the risk predication and Comprehensive Assessment Model (CAM) for evaluating the effectiveness of the existing controls. The proposed approach considers relevant CSRM concepts such as threat actor attack pattern, Tactic, Technique and Procedure (TTP), controls and assets and maps these concepts with the VERIS community dataset (VCDB) features for the purpose of risk predication. Also, the tool serves as an additional component of the proposed framework that enables asset criticality, risk and control effectiveness calculation for a continuous risk assessment. Lastly, the thesis employs a case study to validate the proposed i-CSRM framework and i-CSRMT in terms of applicability. Stakeholder feedback is collected and evaluated using critical criteria such as ease of use, relevance, and usability. The analysis results illustrate the validity and acceptability of both the framework and tool for an effective risk management practice within a real-world environment. The experimental results reveal that using the fuzzy set theory in assessing assets' criticality, supports stakeholder for an effective risk management practice. Furthermore, the results have demonstrated the machine learning classifiers’ have shown exemplary performance in predicting different risk types including denial of service, cyber espionage, and Crimeware. An accurate prediction can help organisations model uncertainty with machine learning classifiers, detect frequent cyber-attacks, affected assets, risk types, and employ the necessary corrective actions for its mitigations. Lastly, to evaluate the effectiveness of the existing controls, the CAM approach is used, and the result shows that some controls such as network intrusion, authentication, and anti-virus show high efficacy in controlling or reducing risks. Evaluating control effectiveness helps organisations to know how effective the controls are in reducing or preventing any form of risk before an attack occurs. Also, organisations can implement new controls earlier. The main advantage of using the CAM approach is that the parameters used are objective, consistent and applicable to CPS

Assets focus risk management framework for critical infrastructure cybersecurity risk management

Critical infrastructure (CI) is vital for the overall economic growth and its reliable and safe operation is essential for a nation's stability and people's safety. Proper operation of the assets is essential for such a system and any threats that could negatively impact the asset could have a severe disruption. Risk management is an important aspect of the protection of CI. There are several frameworks and methodologies for identifying assets, quantifying and analysing vulnerabilities. However, there is a lack of focus on the interdependencies among the assets and cascading effect of the inherent vulnerabilities on the asset. This study attempts to bridge that gap by presenting a novel asset focus risk management approach for the CI. It presents a systematic methodology for identifying and analysing critical assets, their potential vulnerabilities, threats and risks facing CI. This work taking into account cascading vulnerability impacts on assets leading to threats and causing risk. The authors use a running example from a smart grid system to demonstrate the usability of the approach. The result shows that some assets are prioritised and more vulnerable than other assets for the power grid system and it can severely impact on the overall business continuity

Cyber Threat Intelligence for Improving Cybersecurity and Risk Management in Critical Infrastructure

Cyber-attack is one of the significant threats affecting to any organisation specifically to the Critical Infrastructure (CI) organisation. These attacks are nowadays more sophisticated, multi-vectored and less predictable, which make the Cyber Security Risk Management (CSRM) task more challenging. Critical Infrastructure needs a new line of security defence to control these threats and minimise risks. Cyber Threat Intelligence (CTI) provides evidence-based information about the threats aiming to prevent threats. There are existing works and industry practice that emphasise the necessity of CTI and provides methods for threat intelligence and sharing. However, despite these significant efforts, there is a lack of focus on how CTI information can support the CSRM activities so that the organisation can undertake appropriate controls to mitigate the risk proactively. This paper aims to fill this gap by integrating CTI for improving cybersecurity risks management practice specifically focusing on the critical infrastructure. In particular, the proposed approach contributes beyond state of the art practice by incorporating CTI information for the risk management activities. This helps the organisation to provide adequate and appropriate controls from strategic, tactical and operational perspectives. We have integrated concepts relating to CTI and CSRM so that threat actor's profile, attack detailed can support calculating the risk. We consider smart grid system as a Critical Infrastructure to demonstrate the applicability of the work. The result shows that cyber risks in critical infrastructures can be minimised if CTI information is gathered and used as part of CSRM activities. CTI not only supports understanding of threat for accurate risk estimation but also evaluates the effectiveness of existing controls and recommend necessity controls to improve overall cybersecurity. Also, the result shows that our approach provides early warning about issues that need immediate attention

An Integrated Cyber Security Risk Management Approach for a Cyber-Physical System

A cyber-physical system (CPS) is a combination of physical system components with cyber capabilities that have a very tight interconnectivity. CPS is a widely used technology in many applications, including electric power systems, communications, and transportation, and healthcare systems. These are critical national infrastructures. Cybersecurity attack is one of the major threats for a CPS because of many reasons, including complexity and interdependencies among various system components, integration of communication, computing, and control technology. Cybersecurity attacks may lead to various risks affecting the critical infrastructure business continuity, including degradation of production and performance, unavailability of critical services, and violation of the regulation. Managing cybersecurity risks is very important to protect CPS. However, risk management is challenging due to the inherent complex and evolving nature of the CPS system and recent attack trends. This paper presents an integrated cybersecurity risk management framework to assess and manage the risks in a proactive manner. Our work follows the existing risk management practice and standard and considers risks from the stakeholder model, cyber, and physical system components along with their dependencies. The approach enables identification of critical CPS assets and assesses the impact of vulnerabilities that affect the assets. It also presents a cybersecurity attack scenario that incorporates a cascading effect of threats and vulnerabilities to the assets. The attack model helps to determine the appropriate risk levels and their corresponding mitigation process. We present a power grid system to illustrate the applicability of our work. The result suggests that risk in a CPS of a critical infrastructure depends mainly on cyber-physical attack scenarios and the context of the organization. The involved risks in the studied context are both from the technical and nontechnical aspects of the CPS

Determination of activity concentration level of 226RA, 40K and 232TH in soil within Igabi Local Government Area of Kaduna State, Nigeria

This paper is aimed at determining the levels of primordial radionuclides 226Ra, 232Th, and 40K in selected sampling sites within Igabi local government area of Kaduna state, Nigeria using Gamma Ray Spectrometry. Radioactivity levels of fifteen samples taken from seven different locations within Igabi local Government area of Kaduna state, Nigeria were measured by means of gamma-ray spectrometry with () detector to determine activity concentration of 40K, 226Ra and 232Th. Results obtained indicate highest activity concentration of 40K, 226Ra and 232Th from soil samples collected from NOU (502.4883 −1), BP1 (759.0962 −1) and EC2 (127.5941−1).The mean activity of 40K (237.4184 −1)was found to be lower than the world average of 420 −1; that of 232Th (86.2182 −1) was found to be above the world average of 50 −1; and that of 226Ra (128.3507 −1) was found to be lower than the world average of 370 −1.

Single-track sequencing for genotyping of multiple SNPs in the N-acetyltransferase 1 (NAT1) gene

BACKGROUND: Fast, cheap and reliable methods are needed to identify large populations, which may be at risk in relation to environmental exposure. Polymorphisms in NAT1 (N-acetyl transferase) may be suitable markers to identify individuals at risk. RESULTS: A strategy allowing to address simultaneously 24 various genetic variants in the NAT1 gene using the single sequencing reaction method on the same PCR product is described. A modified automated DNA sequencing using only one of the sequence terminators was used to genotype PCR products in single-track sequencing reactions of NAT1 and was shown to be universal for both DNA sequencing using labeled primers and labeled nucleotides. By this method we detected known SNPs at site T640G, which confers the NAT1*11 allele with frequency of 0.036, further T1088A and C1095A with frequency of 0.172 and 0.188, respectively and a deletion of TAATAATAA in the poly A signal area with a frequency 0.031. All observed frequencies were in Hardy Weinberg equilibrium and comparable to those in Caucasian population. The single-track signatures of the variant genotypes were verified on samples previously genotyped by RLFP. CONCLUSIONS: The method could be of great help to scientists in the field of molecular epidemiology of screening of large populations for known informative biomarkers of susceptibility, such as NAT1

Stitched Transmission Line for Broadband Operations

Wearable stitched transmission lines made from stripped RG174 and textile materials are introduced for broadband operations. The stitched transmission lines which are 150 mm long consists of an inner conductor surrounded by a tubular insulating layer. For shielding purposes, the structures are stitched into a denim material with conductive threads. The performances of the stitched transmission lines with three different stitch patterns, Double Overlock, Flatlock stitch and Ric-Rac stitch were investigated and results obtained confirm that Ric-Rac stitched transmission line has fewer DC losses than the three stitched transmission lines for frequencies up to 1 . However, beyond that up to 2.4 and above, it was observed that the Flatlock stitched transmission line and the Double Overlock stitched transmission line have fewer radiation losses compared to the Ric-Rac stitched transmission line. Similarly, the performance of the stitched transmission line when bent through curved angles of 90° and 180° was considered, and a much better 21 was observed with a curved angle of 180° for frequencies below 2.1 , with radiation loss increasing afterwards. Finally, the sensitivity of the design to manufacturing tolerances, with changes in cross-sectional dimensions of the stitched transmission line and the transmission characteristics with different textile substrates were both considered. While simulated results showed that the stitched transmission line is sensitive to small variations in its circular dimensions, measured results conversely showed that Denim and Felt materials can be used as a substrate without any significant effect on its propagation characteristics

Confirmation of Genetic Associations at ELMO1 in the GoKinD Collection Supports Its Role as a Susceptibility Gene in Diabetic Nephropathy

Objective: To examine the association between single nucleotide polymorphisms (SNPs) in the engulfment and cell motility 1 (ELMO1) gene, a locus previously shown to be associated with diabetic nephropathy in two ethnically distinct type 2 diabetic populations, and the risk of nephropathy in type 1 diabetes. Research Design and Methods: Genotypic data from a genome-wide association scan (GWAS) of the Genetics of Kidneys in Diabetes (GoKinD) study collection were analyzed for associations across the ELMO1 locus. In total, genetic associations were assessed using 118 SNPs and 1,705 individuals of European ancestry with type 1 diabetes (885 normoalbuminuric control subjects and 820 advanced diabetic nephropathy case subjects). Results: The strongest associations in ELMO1 occurred at rs11769038 (odds ratio [OR] 1.24; P = 1.7 × 10−3) and rs1882080 (OR 1.23; P = 3.2 × 10−3) located in intron 16. Two additional SNPs, located in introns 18 and 20, respectively, were also associated with diabetic nephropathy. No evidence of association for variants previously reported in type 2 diabetes was observed in our collection. Conclusions: Using GWAS data from the GoKinD collection, we comprehensively examined evidence of association across the ELMO1 locus. Our investigation marks the third report of associations in ELMO1 with diabetic nephropathy, further establishing its role in the susceptibility of this disease. There is evidence of allelic heterogeneity, contributed by the diverse genetic backgrounds of the different ethnic groups examined. Further investigation of SNPs at this locus is necessary to fully understand the commonality of these associations and the mechanism(s) underlying their role in diabetic nephropathy

PET brain imaging in HIV-associated neurocognitive disorders (HAND) in the era of combination antiretroviral therapy

Effective combination antiretroviral therapy (cART) has lead to a significant reduction in the prevalence and incidence of central nervous system (CNS) HIV-associated brain disease, particularly CNS opportunistic infections and HIV encephalitis. Despite this, cognitive deficits in people living with HIV, also known as HIV-associated neurocognitive disorders (HAND) have become more prevalent in recent years. The pathogenesis of HAND is likely to be multifactorial, however recent evidence suggests that brain microglial activation is the most likely pathogenic mechanism. Recent developments in positron emission tomography (PET) brain neuroimaging using novel brain radioligands targeting a variety of physiological changes in the brains of HIV-positive individuals have improved our understanding of the mechanisms associated with the development of HAND. This review will highlight recent PET brain neuroimaging studies in the cART era, focusing on physiological and neurochemical changes associated with HAND in people living with HIV