Sensitivity analysis for vulnerability mitigation in hybrid networks

The development of cyber‐assured systems is a challenging task, particularly due to the cost and complexities associated with the modern hybrid networks architectures, as well as the recent advancements in cloud computing. For this reason, the early detection of vulnerabilities and threat strategies are vital for minimising the risks for enterprise networks configured with a variety of node types, which are called hybrid networks. Existing vulnerability assessment techniques are unable to exhaustively analyse all vulnerabilities in modern dynamic IT networks, which utilise a wide range of IoT and industrial control devices (ICS). This could lead to having a less optimal risk evaluation. In this paper, we present a novel framework to analyse the mitigation strategies for a variety of nodes, including traditional IT systems and their dependability on IoT devices, as well as industrial control systems. The framework adopts avoid, reduce, and manage as its core principles in characterising mitigation strategies. Our results confirmed the effectiveness of our mitigation strategy framework, which took node types, their criticality, and the network topology into account. Our results showed that our proposed framework was highly effective at reducing the risks in dynamic and resource constraint environments, in contrast to the existing techniques in the literature. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

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