Automatic security management of smart infrastructures using attack graph and risk analysis

Amid the widespread use of blockchain technology, the escalating frequency of cyberattacks exploiting its inherent security challenges underscores the critical necessity for a robust and adaptable security risk assessment approach. The distinctive attributes and intricate internal structure of blockchain not only attract malicious actors but also elevate the risk of ill-informed architectural design decisions, potentially introducing security vulnerabilities. This study addresses this imperative by conducting a systematic literature review, classifying publications that elucidate secure architectural design approaches and categorising those that delineate methods for assessing security risks associated with blockchain and smart contracts. The findings reveal four prevalent approaches supporting secure architectural design—decision models, taxonomies, design patterns and guidelines—alongside contributions in blockchain risk assessment encompassing risk identification, analysis and evaluation methods. Furthermore, the study identifies unresolved architectural design challenges and proposes future research directions in this evolving landscape.

This chapter summarizes innovations in security risk and capability assessment frameworks and methodologies to directly support dynamic decision making, forge a convergence with S&T, operations, intelligence and policy, and inform investment priorities of the Canadian Safety and Security Program (CSSP). Using a thematic approach, this paper reviews how multiple innovations were adopted as “best practices” into the conceptual design, development and implementation of security risk assessment frameworks and methodologies in the CSSP. These include the: use taxonomies to foster key stakeholder ‘buy in’; leveraging architecture frameworks to drive tools, methods and rating schema; the formulation of scenario based approaches for assessing high consequence all hazards risks; and, the application of an integrated risk and capability gap assessment model to guide investment in public safety and security S&T. In the CSSP, the innovations in security risk assessment identified best practices and common tools that supported numerous strategies and S&T portfolios (e.g., CBRNE, Critical Infrastructure Protection, all hazards safety and security; defence infrastructure/military bases), where risk assessment expertise/capability improvements that were adopted by practitioners, interdisciplinary teams and decision makers. Underpinning these innovations were strong partnerships and community-based approaches that enabled a credible risk-informed decision support environment, with consistent/scalable approaches to analysis and decision making under conditions of uncertainty.KeywordsSecurity risk assessmentVulnerability

Critical systems have very stringent requirements on both security and safety. Recent mishaps such as the missing MH370 aircraft and the sunk Korean Sewol ferry go to show that our technology in safety and security risk assessment still need a more integrated approach. Nuclear plant meltdown in the recent Fukushima accident is also a typical example of insufficient risk assessments. This work is a case study on how a unified security and safety risk assessment methodology may be applied to a High Pressure Core Flooder (HPCF) system in a nuclear power plant. Individual risk security or safety assessments may overlook the possible higher risk associated with such critical systems. The case study shows how the proposed method provides a more accurate risk assessment compared to individual assessments.

Information security management is a managerial activity that keeps the information security risk of an enterprise at some acceptable level. The process requires risk assessment iterations and non-trivial resources. At the same time, business executives compete for finite resources to invest in general business activities. The executives are motivated to intentionally reduce the resource assignment for risk assessment to broaden the estimated risk variance and then choose the lower limit to underestimate the actual risks. This study proposes a model-based risk assessment approach; it guarantees that an additional, thus expected to be costly, fine-grained risk assessment always gives a refined subset of the possible incidents compared to that of the relatively coarse-grained, therefore cheaper, risk assessment. In other words, estimated incidents roughly decrease with the growth of assessment cost. We expect this property to secure the risk management process from conflicts between the business executives and the security practitioners. Our approach introduces the concept named aggregation and segregation of facts appearing in attack graph analysis, a prominent approach in model-based network security risk analysis. This study contributes to expanding the attack graph analysis to enable secured risk assessment.

Combining the arm training practice after the Strong Army Reform, this paper put forwards using the F-ANP method for military training security risks to semi- quantitative evaluation, builds the safety risk assessment index system of military training, semi-quantitative calculation and analysis, and put forwards the opinions of the security risk prevention and control suggestions. This paper enriches the military training of security risk assessment methods, and provides the reference to the research of military training safety risk assessment.

Fuzzy theory and Bayesian network theory were based on the fault tree. The fault tree analysis method improved the fault analysis to obtain number of event's exact problem. Considering the characteristics of the fuzzy risk analysis at the same time, it also solved the problem of scale fault analysis modeling. The theory is applied to the cost of construction shield tunnel risk analysis, floating shield tunnel segments, dislocation of failure risk analysis and deep station foundation construction risk analysis. By security risk identification and evaluation process, it can be improved to subway construction process of deep foundation pit hazard anticipation. Before construction accidents to avoid and resolve security risks, thereby improving overall system safety performance. Based on this, the paper depth study the theory and methods of security risk identification and security risk assessment, further enrich the security risk management theory, and put forward to deal with the security risk response countermeasures.

Researchers have previously looked into the problem of determining the connection between invasive events and network risk, and attack graph (AG) was proposed to seek countermeasures. However, AG has proved to have various limitations in practical applications. To overcome such defects, this study presents a risk flow attack graph (RFAG)-based risk assessment approach. In particular, this approach applies a RFAG to represent network and attack scenarios, which are then fed to a network flow model for computing risk flow. A bi-objective sorting algorithm is employed to automatically infer the priority of risk paths and assist risk assessment, and a fuzzy comprehensive evaluation is performed to determine risk severity. Via the aforementioned processes, the authors simplify AG and follow the risk path of originating, transferring, redistributing and converging to assess security risk. The authors use a synthetic network scenario to illustrate this approach and evaluate its performance through a set of simulations. Experiments show that the approach is capable of effectively identifying network security situations and assessing critical risk.

Cybersecurity vulnerabilities of cardiac implantable electronic devices: Communication strategies for clinicians—Proceedings of the Heart Rhythm Society's Leadership Summit

Nowadays, the application of enterprise management information has been deeply rooted in daily business activities, and the management risk of enterprise information security (EIS) has also increased. The use of advanced means to provide security protection for it has become the top priority. To optimize the EIS management system, and carry on the risk assessment (RA), firstly, this study analyzes the current situation of the enterprise's internal information management and summarizes the shortcomings and security risks faced by the system. In the era of big data (BD), the security risks of database information systems show a diversified trend. Secondly, to explore the application of BD technology in EIS management, the characteristics of this technology and security control measures for risks are summarized to strengthen the enterprise's information management innovation and implement the application of data security technology.

Information is an essential company asset that must be protected. The value of information assets depends on the type and scale of the business and its role in delivering services. One of the primary programs that can help identify areas of improvement and guide the development of security awareness programs is risk assessment. Managing cybersecurity risks is critical to protecting enterprises from developing cyber threats and promoting resilience. This includes detecting, assessing, and mitigating risks to protect sensitive data, systems, and networks. While cybersecurity risk management is challenging, organizations may improve their security posture. This paper seeks to contribute to the field of information security risk assessment by leveraging the power of machine learning to provide quick, cost-effective, and individualized risk assessments for small and medium enterprises. Specifically, we extend the evaluation for security level classification by utilizing a support vector machine, random forest, and gradient boosting algorithms. The results demonstrate how well the model detects significant cases while reducing false positives. The model’s exceptional precision ensures that its identifications are dependable, while the high recall demonstrates that it accurately detects relevant data. Precision is critical in security risk assessment because a false positive result might have profound effects.

Visualization and graphical representation of a system can improve the understanding of the designer of a system and mitigate risks of attack to designed systems. An attack graphs documents the risks known at the time the system is designed. Attack graphs use graphical representation which assists in documenting security risks and identifying possible paths attackers may consider for attacking a system for their undesirable goal. However an attack graph does not provide facilities to perform concrete risk analysis such as what-if and scenarios analysis to test the designed system for possible risk of attacks. In this article, a fuzzy cognitive map (FCM) is used with graph attacks to provide facilities that will enable the system architects to perform what-if analysis to better understand vulnerabilities of their designed system.

Attack graphs are the graphs which describe attack scenarios, play important roles in analyzing network threats. These attack graphs are able to reveal such potential threats by evaluating the all possible sequences that an attacker can follow to compromise given critical resources or nodes. An Attack graph specifies an attack scenario that results in compromising network values. There are so many methods proposed to evaluate the network security in attack graphs. But no method specifies the overhead occurred due to the evaluation of network security at each and every node. This paper addresses the problem of overhead occurred due to the network security evaluation in Short-Normalizedattack graphs by evaluating a factor called network security risk. In this paper first the possible n valid attack paths are going to be calculated and then the security risk is going to be calculated for those n valid paths. This security risk denotes the amount of overhead occurred due to this evaluation.

The integration of Information and Communication Technology (ICT) into the existing power grid has created new problems to the grid. The grid network has become more vulnerable to security threats and risk which is a corollary to the modern data network. Smart Grid has strict latency requirement for data communication and the violation of this latency is very costly. This paper assesses the threats and vulnerabilities associated with the Smart Grid network and reviews the methods to mitigate these security risks.

The article is devoted to the assessment of information security risks of organizations for the purpose of leveling or reducing them. Approaches to the content, regulatory regulation, methods of analysis and assessment of information risks are considered. Analytical procedures for assessing and managing information security risks for a specific municipal enterprise were performed. The results obtained can be used by municipal enterprises to ensure the security of the information system and sustainable business development.

The Cloud computing is a major technological trend that continues to evolve and flourish. It has potential benefits in achieving rapid and scalable resource provisioning capabilities as well as resource sharing. However, a number of security risk are emerging in association with cloud usage that need to be assessed before cloud computing is adopted. This paper presents a review of the security risk assessment methods in cloud computing. The paper aims to summarize, organize and classify the information available in the literature to identify any gaps in current research then suggest areas for further investigation. At the end, the paper suggests to have a collaborative security risk assessment method that will add great assistance to both service providers and consumers.