Defense against Insider Threat: a Framework for Gathering Goal-based Requirements

Insider threat is becoming comparable to outsider threat in frequency of security events. This is a worrying situation, since insider attacks have a high probability of success because insiders have authorized access and legitimate privileges. Despite their importance, insider threats are still not properly addressed by organizations. We contribute to reverse this situation by introducing a framework composed of a method for identification and assessment of insider threat risks and of two supporting deliverables for awareness of insider threat. The deliverables are: (i) attack strategies structured in four decomposition trees, and (ii) a matrix which correlates defense strategies, attack strategies and control principles. The method output consists of goal-based requirements for the defense against insiders

An Approach Toward Implementing Continuous Security In Agile Environment

Traditionally, developers design software to accomplish a set of functions and then later add—or do not add—security measures, especially after the prevalence of the agile software development model. Consequently, there is an increased risk of security vulnerabilities that are introduced into the software in various stages of development. To avoid security vulnerabilities, there are many secure software development efforts in the directions of secure software development lifecycle process. The purpose of this thesis is to propose a software security assurance methodology and integrate it into the Msg Life organization’s development lifecycle based on security best practices that fulfill their needs in building secure software applications. Ultimately, the objective adhered to increasing the security maturity level according to the suggested security assurance roadmap and implemented partly in the context of this thesis.Tradicionalmente, os desenvolvedores projetam o software para realizar um conjunto de funções e, posteriormente, adicionam - ou não - medidas de segurança, especialmente após a prevalência do modelo de desenvolvimento ágil de software. Consequentemente, há um risco aumentado de vulnerabilidades de segurança que são introduzidas no software em vários estágios de desenvolvimento. Para evitar vulnerabilidades de segurança, existem muitos esforços no desenvolvimento de software nas direções dos processos do ciclo de vida desse mesmo software. O objetivo desta tese é propor uma metodologia de garantia de segurança de software e integrá-la ao ciclo de vida de desenvolvimento da Msg Life Company, com base nas melhores práticas de segurança que atendem às suas necessidades na criação de aplicativos de software seguros. Por fim, o objetivo aderiu ao aumento do nível de maturidade da segurança de acordo com o roteiro sugerido de garantia de segurança e implementado parcialmente no contexto desta tese

Vulnerability modelling and mitigation strategies for hybrid networks

Hybrid networks nowadays consist of traditional IT components, Internet of Things (IoT) and industrial control systems (ICS) nodes with varying characteristics, making them genuinely heterogeneous in nature. Historically evolving from traditional internet-enabled IT servers, hybrid networks allow organisations to strengthen cybersecurity, increase flexibility, improve efficiency, enhance reliability, boost remote connectivity and easy management. Though hybrid networks offer significant benefits from business and operational perspectives, this integration has increased the complexity and security challenges to all connected nodes. The IT servers of these hybrid networks are high-budget devices with tremendous processing power and significant storage capacity. In contrast, IoT nodes are low-cost devices with limited processing power and capacity. In addition, the ICS nodes are programmed for dedicated functions with the least interference. The available cybersecurity solutions for hybrid networks are either for specific node types or address particular weaknesses. Due to these distinct characteristics, these solutions may place other nodes in vulnerable positions. This study addresses this gap by proposing a comprehensive vulnerability modelling and mitigation strategy. This proposed solution equally applies to each node type of hybrid network while considering their unique characteristics. For this purpose, the industry-wide adoption of the Common Vulnerability Scoring System (CVSS) has been extended to embed the distinct characteristics of each node type in a hybrid network. To embed IoT features, the ‘attack vectors’ and ‘attack complexity vectors’ are modified and another metric “human safety index”, is integrated in the ‘Base metric group’ of CVSS. In addition, the ICS related characteristics are included in the ‘Environmental metric group’ of CVSS. This metric group is further enhanced to reflect the node resilience capabilities when evaluating the vulnerability score. The resilience of a node is evaluated by analysing the complex relationship of numerous contributing cyber security factors and practices. The evolved CVSSR-IoT-ICS framework proposed in the thesis measures the given vulnerabilities by adopting the unique dynamics of each node. These vulnerability scores are then mapped in the attack tree to reveal the critical nodes and shortest path to the target node. The mitigating strategy framework suggests the most efficient mitigation strategy to counter vulnerabilities by examining the node’s functionality, its locality, centrality, criticality, cascading impacts, available resources, and performance thresholds. Various case studies were conducted to analyse and evaluate our proposed vulnerability modelling and mitigation strategies on realistic supply chain systems. These analyses and evaluations confirm that the proposed solutions are highly effective for modelling the vulnerabilities while the mitigation strategies reduce the risks in dynamic and resource-constrained environments. The unified vulnerability modelling of hybrid networks minimises ambiguities, reduces complexities and identifies hidden deficiencies. It also improves system reliability and performance of heterogeneous networks while at the same time gaining acceptance for a universal vulnerability modelling framework across the cyber industry. The contributions have been published in reputable journals and conferences.Doctor of Philosoph

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

Software security requirements management as an emerging cloud computing service

© 2016 Elsevier Ltd. All rights reserved.Emerging cloud applications are growing rapidly and the need for identifying and managing service requirements is also highly important and critical at present. Software Engineering and Information Systems has established techniques, methods and technology over two decades to help achieve cloud service requirements, design, development, and testing. However, due to the lack of understanding of software security vulnerabilities that should have been identified and managed during the requirements engineering phase, we have not been so successful in applying software engineering, information management, and requirements management principles that have been established for the past at least 25 years, when developing secure software systems. Therefore, software security cannot just be added after a system has been built and delivered to customers as seen in today's software applications. This paper provides concise methods, techniques, and best practice requirements engineering and management as an emerging cloud service (SSREMaaES) and also provides guidelines on software security as a service. This paper also discusses an Integrated-Secure SDLC model (IS-SDLC), which will benefit practitioners, researchers, learners, and educators. This paper illustrates our approach for a large cloud system Amazon EC2 service

Risk Assessment Framework for Evaluation of Cybersecurity Threats and Vulnerabilities in Medical Devices

Medical devices are vulnerable to cybersecurity exploitation and, while they can provide improvements to clinical care, they can put healthcare organizations and their patients at risk of adverse impacts. Evidence has shown that the proliferation of devices on medical networks present cybersecurity challenges for healthcare organizations due to their lack of built-in cybersecurity controls and the inability for organizations to implement security controls on them. The negative impacts of cybersecurity exploitation in healthcare can include the loss of patient confidentiality, risk to patient safety, negative financial consequences for the organization, and loss of business reputation. Assessing the risk of vulnerabilities and threats to medical devices can inform healthcare organizations toward prioritization of resources to reduce risk most effectively. In this research, we build upon a database-driven approach to risk assessment that is based on the elements of threat, vulnerability, asset, and control (TVA-C). We contribute a novel framework for the cybersecurity risk assessment of medical devices. Using a series of papers, we answer questions related to the risk assessment of networked medical devices. We first conducted a case study empirical analysis that determined the scope of security vulnerabilities in a typical computerized medical environment. We then created a cybersecurity risk framework to identify threats and vulnerabilities to medical devices and produce a quantified risk assessment. These results supported actionable decision making at managerial and operational levels of a typical healthcare organization. Finally, we applied the framework using a data set of medical devices received from a partnering healthcare organization. We compare the assessment results of our framework to a commercial risk assessment vulnerability management system used to analyze the same assets. The study also compares our framework results to the NIST Common Vulnerability Scoring System (CVSS) scores related to identified vulnerabilities reported through the Common Vulnerability and Exposure (CVE) program. As a result of these studies, we recognize several contributions to the area of healthcare cybersecurity. To begin with, we provide the first comprehensive vulnerability assessment of a robotic surgical environment, using a da Vinci surgical robot along with its supporting computing assets. This assessment supports the assertion that networked computer environments are at risk of being compromised in healthcare facilities. Next, our framework, known as MedDevRisk, provides a novel method for risk quantification. In addition, our assessment approach uniquely considers the assets that are of value to a medical organization, going beyond the medical device itself. Finally, our incorporation of risk scenarios into the framework represents a novel approach to medical device risk assessment, which was synthesized from other well-known standards. To our knowledge, our research is the first to apply a quantified assessment framework to the problem area of healthcare cybersecurity and medical networked devices. We would conclude that a reduction in the uncertainty about the riskiness of the cybersecurity status of medical devices can be achieved using this framework

DAG-Based Attack and Defense Modeling: Don't Miss the Forest for the Attack Trees

This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions. Methods based on threat trees and Bayesian networks are two well-known approaches to security modeling. However there exist more than 30 DAG-based methodologies, each having different features and goals. The objective of this survey is to present a complete overview of graphical attack and defense modeling techniques based on DAGs. This consists of summarizing the existing methodologies, comparing their features and proposing a taxonomy of the described formalisms. This article also supports the selection of an adequate modeling technique depending on user requirements

Design of risk assessment methodology for IT/OT systems : Employment of online security catalogues in the risk assessment process

The revolution brought about with the transition from Industry 1.0 to 4.0 has expanded the cyber threats from Information Technology (IT) to Operational Technology (OT) systems. However, unlike IT systems, identifying the relevant threats in OT is more complex as penetration testing applications highly restrict OT availability. The complexity is enhanced by the significant amount of information available in online security catalogues, like Common Weakness Enumeration, Common Vulnerabilities and Exposures and Common Attack Pattern Enumeration and Classification, and the incomplete organisation of their relationships. These issues hinder the identification of relevant threats during risk assessment of OT systems. In this thesis, a methodology is proposed to reduce the aforementioned complexities and improve relationships among online security catalogues to identify the cybersecurity risk of IT/OT systems. The weaknesses, vulnerabilities and attack patterns stored in the online catalogues are extracted and categorised by mapping their potential mitigations to their security requirements, which are introduced on security standards that the system should comply with, like the ISA/IEC 62443. The system's assets are connected to the potential threats through the security requirements, which, combined with the relationships established among the catalogues, offer the basis for graphical representation of the results by employing tree-shaped graphical models. The methodology is tested on the components of an Information and Communication Technology system, whose results verify the simplification of the threat identification process but highlight the need for an in-depth understanding of the system. Hence, the methodology offers a significant basis on which further work can be applied to standardise the risk assessment process of IT/OT systems