Biblio

The most significant threats to networks usually originate from external entities. As such, the Northbound interface of SDN networks which ensures communication with external applications requires particularly close attention. In this paper we propose the Risk Assessment and Management approach to SEcure SDN (RAMSES). This novel solution is able to estimate the risk associated with traffic demand requests received via the Northbound-API in SDN networks. RAMSES quantifies the impact on network cost incurred by expected traffic demands and specifies the likelihood of adverse requests estimated using the reputation system. Accurate risk estimation allows SDN network administrators to make the right decisions and mitigate potential threat scenarios. This can be observed using extensive numerical verification based on an network optimization tool and several scenarios related to the reputation of the sender of the request. The verification of RAMSES confirmed the usefulness of its risk assessment approach to protecting SDN networks against threats associated with the Northbound-API.

Regulatory efforts such as the General Data Protection Regulation (GDPR) embody a notion of privacy risk that is centered around the fundamental rights of data subjects. This is, however, a fundamentally different notion of privacy risk than the one commonly used in threat modeling which is largely agnostic of involved data subjects. This mismatch hampers the applicability of privacy threat modeling approaches such as LINDDUN in a Data Protection by Design (DPbD) context. In this paper, we present a data subject-aware privacy risk assessment model in specific support of privacy threat modeling activities. This model allows the threat modeler to draw upon a more holistic understanding of privacy risk while assessing the relevance of specific privacy threats to the system under design. Additionally, we propose a number of improvements to privacy threat modeling, such as enriching Data Flow Diagram (DFD) system models with appropriate risk inputs (e.g., information on data types and involved data subjects). Incorporation of these risk inputs in DFDs, in combination with a risk estimation approach using Monte Carlo simulations, leads to a more comprehensive assessment of privacy risk. The proposed risk model has been integrated in threat modeling tool prototype and validated in the context of a realistic eHealth application.

Measures and methods used in financial sector to quantify risk, have been recently applied to cyber world. The aim is to help organizations to improve risk management strategies and to wisely plan investments in cyber security. On the other hand, they are useful instruments for insurance companies in pricing cyber insurance contracts and setting the minimum capital requirements defined by the regulators. In this paper we propose an estimation of Value at Risk (VaR), referred to as Cyber Value at Risk in cyber security domain, and Tail Value at risk (TVaR). The data breach information we use is obtained from the “Chronology of data breaches” compiled by the Privacy Rights Clearinghouse.

The article deals with the aspects of IT-security of business processes, using a variety of methodological tools, including Integrated Management Systems. Currently, all IMS consist of at least 2 management systems, including the IT-Security Management System. Typically, these IMS cover biggest part of the company business processes, but in practice, there are examples of different scales, even within a single facility. However, it should be recognized that the total number of such projects both in the Russian Federation and in the World is small. The security of business processes will be considered on the example of the incident of Norsk Hydro. In the article the main conclusions are given to confirm the possibility of security, continuity and recovery of critical business processes on the example of this incident.

In the network security risk assessment on critical information infrastructure of smart city, to describe attack vectors for predicting possible initial access is a challenging task. In this paper, an attack vector evaluation model based on weakness, path and action is proposed, and the formal representation and quantitative evaluation method are given. This method can support the assessment of attack vectors based on known and unknown weakness through combination of depend conditions. In addition, defense factors are also introduced, an attack vector evaluation model of integrated defense is proposed, and an application example of the model is given. The research work in this paper can provide a reference for the vulnerability assessment of attack vector.

Safety and security of complex critical infrastructures are very important for economic, environmental and social reasons. The complexity of these systems introduces difficulties in the identification of safety and security risks that emerge from interdisciplinary interactions and dependencies. The discovery of safety and security design weaknesses late in the design process and during system operation can lead to increased costs, additional system complexity, delays and possibly undesirable compromises to address safety and security weaknesses.

The last decade has witnessed a growing interest in exploiting the advantages of Cloud Computing technology. However, the full migration of services and data to the Cloud is still cautious due to the lack of security assurance. Cloud Service Providers (CSPs)are urged to exert the necessary efforts to boost their reputation and improve their trustworthiness. Nevertheless, the uniform implementation of advanced security solutions across all their data centers is not the ideal solution, since customers' security requirements are usually not monolithic. In this paper, we aim at integrating the Cloud security risk into the process of resource provisioning to increase the security of Cloud data centers. First, we propose a quantitative security risk evaluation approach based on the definition of distinct security metrics and configurations adapted to the Cloud Computing environment. Then, the evaluated security risk levels are incorporated into a resource provisioning model in an InterCloud setting. Finally, we adopt two different metaheuristics approaches from the family of evolutionary computation to solve the security risk-aware resource provisioning problem. Simulations show that our model reduces the security risk within the Cloud infrastructure and demonstrate the efficiency and scalability of proposed solutions.

In enterprise environments, the amount of managed assets and vulnerabilities that can be exploited is staggering. Hackers' lateral movements between such assets generate a complex big data graph, that contains potential hacking paths. In this vision paper, we enumerate risk-reduction security requirements in large scale environments, then present the Agile Security methodology and technologies for detection, modeling, and constant prioritization of security requirements, agile style. Agile Security models different types of security requirements into the context of an attack graph, containing business process targets and critical assets identification, configuration items, and possible impacts of cyber-attacks. By simulating and analyzing virtual adversary attack paths toward cardinal assets, Agile Security examines the business impact on business processes and prioritizes surgical requirements. Thus, handling these requirements backlog that are constantly evaluated as an outcome of employing Agile Security, gradually increases system hardening, reduces business risks and informs the IT service desk or Security Operation Center what remediation action to perform next. Once remediated, Agile Security constantly recomputes residual risk, assessing risk increase by threat intelligence or infrastructure changes versus defender's remediation actions in order to drive overall attack surface reduction.

Software-Defined Network (SDN) is the dynamic network technology to address the issues of traditional networks. It provides centralized view of the whole network through decoupling the control planes and data planes of a network. Most SDN-based security services globally detect and block a malicious host based on IP address. However, the IP address is not verified during the forwarding process in most cases and SDN-based security service may block a normal host with forged IP address in the whole network, which means false-positive. In this paper, we introduce an attack scenario that uses forged packets to make the security service consider a victim host as an attacker so that block the victim. We also introduce cost-effective risk avoidance strategy.

In order to improve the information security level of intelligent substation, this paper proposes an intelligent substation information security assessment tool through the research and analysis of intelligent substation information security risk and information security assessment method, and proves that the tool can effectively detect it. It is of great significance to carry out research on industrial control systems, especially intelligent substation information security.

This research explored how cyber security risks are managed across UK Critical National Infrastructure (CNI) sectors following implementation of the 2018 Networks and Information Security (NIS) legislation. Being in its infancy, there has been limited study into the effectiveness of this national framework for cyber risk management. The analysis of data gathered through interviews with key stakeholders against the NIS objectives indicated a collaborative implementation approach to improve cyber-risk management capabilities in CNI sectors. However, more work is required to bridge the gaps in the NIS framework to ensure holistic security across cyber spaces as well as non-cyber elements: cyber-physical security, cross-sector CNI service security measures, outcome-based regulatory assessments and risks due to connected smart technology implementations alongside legacy systems. This paper proposes ten key recommendations to counter the danger of not meeting the NIS key strategic objectives. In particular, it recommends that the approach to NIS implementation needs further alignment with its objectives, such as bringing a step-change in the cyber-security risk management capabilities of the CNI sectors.

In order to effectively assess the security risks in multimodal transport networks, a security risk assessment method based on WBS-RBS and Pythagorean Fuzzy Weighted Average (PFWA) operator is proposed. The risk matrix 0-1 assignment of WBS-RBS is replaced by the Pythagorean Fuzzy Number (PFLN) scored by experts. The security risk ranking values of multimodal transport network are calculated from two processes of whole-stage and phased, respectively, and the security risk assessment results are obtained. Finally, an example of railway-highway-waterway intermodal transportation process of automobile parts is given to verify the validity of the method, the results show that the railway transportation is more stable than the waterway transportation, and the highway transportation has the greatest security risk, and for different security risk factors, personnel risk has the greatest impact. The risk of goods will change with the change of the attributes of goods, and the security risk of storage facilities is the smallest.

The security of an organization lies not only in physical buildings, but also in its information assets. Safeguarding information assets requires further study to establish optimal security mitigation steps. In determining the appropriate mitigation of information assets, both an information security risk assessment and a clear and measurable rating are required. Most risk management methods do not provide the right focus on ranking the critical information assets of an organization. This paper proposes a framework approach for ranking critical information assets. The proposed framework uses the OCTAVE Allegro method, which focuses on profiling information assets by combining ranking priority measurements using decision support system methods, such as Simple Additive Weighting (SAW) and Analytic Hierarchy Process (AHP). The combined OCTAVE Allegro-SAW and OCTAVE Allegro-AHP methods are expected to better address risk priority as an input to making mitigation decisions for critical information assets. These combinations will help management to avoid missteps in adjusting budget needs allocation or time duration by selecting asset information mitigation using the ranking results of the framework.

In this study, the enactment of information security risk management by novice practitioners is studied by applying an analytical lens of security-related stress. Two organisations were targeted in the study using a case study approach to obtain data about their practices. The study identifies stressors and stress inhibitors in the ISRM process and the supporting ISRM tools and discusses the implications for practitioners. For example, a mismatch between security standards and how they are interpreted in practice has been identified. This mismatch was further found to be strengthened by the design of the used ISRM tools. Those design shortcomings hamper agility since they may enforce a specific workflow or may restrict documentation. The study concludes that security-related stress can provide additional insight into security-novice practitioners' ISRM challenges.

While the general idea of Intelligent Transportation System (ITS) is to employ suitable, sophisticated information and communications technologies, however, such tool also encompass many system complexities. Fittingly, this paper aims to highlight the most contemporary system complications of ITS and in doing so, will also underline the safety, security and risk management concerns. More importantly, effectively treating such issues will ultimately improve the reliability and efficiency of transportation systems. Whereas such issues are among the most significant subjects for any intelligent system, for ITS in particular they the most dominant. For such intelligent systems, the safety, security and risk management issues must not only be decidedly prioritized, but also methodically integrated. As a part of such ITS integration, this paper will delicately examine the Emergency Management System (EMS) development and application. Accurate EMS is not only a mandatory feature of intelligent systems, but it is a fundamental component of ITS which will vigilantly respond to safety, security and risk management apprehensions. To further substantiate such scheme, the Sydney Metro's EMS will be also conferred. It was determined that, the Sydney Metro's EMS although highly advanced, it was also vigilantly aligned with specific designated safety, security and risk management strategies.

The endeavor to achieving software security consists of a set of risk-based security engineering processes during software development. In iterative software development, the software design typically evolves as the project matures, and the technical environment may undergo considerable changes. This increases the work load of identifying, assessing and managing the security risk by each iteration, and after every change. Besides security risk, the changes also accumulate technical debt, an allegory for postponed or sub-optimally performed work. To manage the security risk in software development efficiently, and in terms and definitions familiar to software development organizations, the concept of technical debt is extended to contain security debt. To accommodate new technical debt with potential security implications, a security debt management approach is introduced. The selected approach is an extension to portfolio-based technical debt management framework. This includes identifying security risk in technical debt, and also provides means to expose debt by security engineering techniques that would otherwise remained hidden. The proposed approach includes risk-based extensions to prioritization mechanisms in existing technical debt management systems. Identification, management and repayment techniques are presented to identify, assess, and mitigate the security debt.

Strategic management and security risk management are part of the general government of the country, and therefore it is not possible to examine it separately and even if it was, one separate examination would not have give us a complete idea of how to implement this process. A modern understanding of the strategic security management requires not only continuous efforts to improve security policy formation and implementation but also new approaches and particular solutions to modernize the security system by making it adequate to the requirements of the dynamic security environment.

The work defines a multi-factor authentication model in case the application supports multiple authentication factors. The aim of this modeling is to find acceptable authentication methods sufficient to access specifically qualified information. The core of the proposed model is risk-based authentication. Results of simulations of some key scenarios often used in practice are also presented.

The potential risk of agricultural product supply chain is huge because of the complex attributes specific to it. Actually the safety incidents of edible agricultural product emerge frequently in recent years, which expose the fragility of the agricultural product supply chain. In this paper the possible risk factors in agricultural product supply chain is analyzed in detail, the agricultural product supply chain risk evaluation index system and evaluation model are established, and an empirical analysis is made using BP neural network method. The results show that the risk ranking of the simulated evaluation is consistent with the target value ranking, and the risk assessment model has a good generalization and extension ability, and the model has a good reference value for preventing agricultural product supply chain risk.

Currently, organisations find it difficult to design a Decision Support System (DSS) that can predict various operational risks, such as financial and quality issues, with operational risks responsible for significant economic losses and damage to an organisation's reputation in the market. This paper proposes a new DSS for risk assessment, called the Fuzzy Inference DSS (FIDSS) mechanism, which uses fuzzy inference methods based on an organisation's big data collection. It includes the Emerging Association Patterns (EAP) technique that identifies the important features of each risk event. Then, the Mamdani fuzzy inference technique and several membership functions are evaluated using the firm's data sources. The FIDSS mechanism can enhance an organisation's decision-making processes by quantifying the severity of a risk as low, medium or high. When it automatically predicts a medium or high level, it assists organisations in taking further actions that reduce this severity level.

Cloud computing is widely believed to be the future of computing. It has grown from being a promising idea to one of the fastest research and development paradigms of the computing industry. However, security and privacy concerns represent a significant hindrance to the widespread adoption of cloud computing services. Likewise, the attributes of the cloud such as multi-tenancy, dynamic supply chain, limited visibility of security controls and system complexity, have exacerbated the challenge of assessing cloud risks. In this paper, we conduct a real-world case study to validate the use of a supply chaininclusive risk assessment model in assessing the risks of a multicloud SaaS application. Using the components of the Cloud Supply Chain Cyber Risk Assessment (CSCCRA) model, we show how the model enables cloud service providers (CSPs) to identify critical suppliers, map their supply chain, identify weak security spots within the chain, and analyse the risk of the SaaS application, while also presenting the value of the risk in monetary terms. A key novelty of the CSCCRA model is that it caters for the complexities involved in the delivery of SaaS applications and adapts to the dynamic nature of the cloud, enabling CSPs to conduct risk assessments at a higher frequency, in response to a change in the supply chain.

We address the need for security requirements to take into account risks arising from complex supply chains underpinning cyber-physical infrastructures such as industrial control systems (ICS). We present SEISMiC (SEcurity Industrial control SysteM supply Chains), a framework that takes into account the whole spectrum of security risks - from technical aspects through to human and organizational issues - across an ICS supply chain. We demonstrate the effectiveness of SEISMiC through a supply chain risk assessment of Natanz, Iran's nuclear facility that was the subject of the Stuxnet attack.

The Risk Management system should help customs to more easily and effectively detect irregularities in import, export or transit of goods. Customs administrations today are required to provide extensive facilitation while maintaining control over the international movement of goods, means of transport and persons. The level of risk is determined in the context of the priorities of the Customs administrations e.g. whether the priority is collection of duties and taxes or checking prohibitions and restrictions or any other specific area that has been identified. The aim of the proposed platform in this paper is to achieve a high-quality, multi-layered approach to risk management that is effective and efficient, i.e. the platform is built on decoupled microservices, the different components are working together and an interruption in one segment does not have major effect on the overall system. The main motivation behind this case study is the hands-on experience we have and the close proximity to the project, i.e. information exchange and team discussions as the main available resources.

The constant changing of technologies have brought to critical infrastructure organisations numerous information security threats such as insider threat. Critical infrastructure organisations have difficulties to early detect and capture the possible vital signs of insider threats due sometimes to lack of effective methodologies or frameworks. It is from this viewpoint that, this paper proposes a symptomatic insider threat risk assessments framework known as Insider Threat Framework for Namibia Critical Infrastructure Organization (ITFNACIO), aimed to predict the probable signs of insider threat based on Symptomatic Analysis (SA), and develop a prototype as a proof of concept. A case study was successfully used to validate and implement the proposed framework; hence, qualitative methodology was employed throughout the whole research process where two (2) insider threats were captured. The proposed insider threat framework can be further developed in multiple cases and a more automated system able to trigger an early warning system of possible insider threat events.

By accurately measuring risk for enterprise networks, attack graphs allow network defenders to understand the most critical threats and select the most effective countermeasures. This paper describes substantial enhancements to the NetSPA attack graph system required to model additional present-day threats (zero-day exploits and client-side attacks) and countermeasures (intrusion prevention systems, proxy firewalls, personal firewalls, and host-based vulnerability scans). Point-to-point reachability algorithms and structures were extensively redesigned to support "reverse" reachability computations and personal firewalls. Host-based vulnerability scans are imported and analyzed. Analysis of an operational network with 84 hosts demonstrates that client-side attacks pose a serious threat. Experiments on larger simulated networks demonstrated that NetSPA's previous excellent scaling is maintained. Less than two minutes are required to completely analyze a four-enclave simulated network with more than 40,000 hosts protected by personal firewalls.