Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

Nature-inspired survivability: Prey-inspired survivability countermeasures for cloud computing security challenges

As cloud computing environments become complex, adversaries have become highly sophisticated and unpredictable. Moreover, they can easily increase attack power and persist longer before detection. Uncertain malicious actions, latent risks, Unobserved or Unobservable risks (UUURs) characterise this new threat domain. This thesis proposes prey-inspired survivability to address unpredictable security challenges borne out of UUURs. While survivability is a well-addressed phenomenon in non-extinct prey animals, applying prey survivability to cloud computing directly is challenging due to contradicting end goals. How to manage evolving survivability goals and requirements under contradicting environmental conditions adds to the challenges. To address these challenges, this thesis proposes a holistic taxonomy which integrate multiple and disparate perspectives of cloud security challenges. In addition, it proposes the TRIZ (Teorija Rezbenija Izobretatelskib Zadach) to derive prey-inspired solutions through resolving contradiction. First, it develops a 3-step process to facilitate interdomain transfer of concepts from nature to cloud. Moreover, TRIZ’s generic approach suggests specific solutions for cloud computing survivability. Then, the thesis presents the conceptual prey-inspired cloud computing survivability framework (Pi-CCSF), built upon TRIZ derived solutions. The framework run-time is pushed to the user-space to support evolving survivability design goals. Furthermore, a target-based decision-making technique (TBDM) is proposed to manage survivability decisions. To evaluate the prey-inspired survivability concept, Pi-CCSF simulator is developed and implemented. Evaluation results shows that escalating survivability actions improve the vitality of vulnerable and compromised virtual machines (VMs) by 5% and dramatically improve their overall survivability. Hypothesis testing conclusively supports the hypothesis that the escalation mechanisms can be applied to enhance the survivability of cloud computing systems. Numeric analysis of TBDM shows that by considering survivability preferences and attitudes (these directly impacts survivability actions), the TBDM method brings unpredictable survivability information closer to decision processes. This enables efficient execution of variable escalating survivability actions, which enables the Pi-CCSF’s decision system (DS) to focus upon decisions that achieve survivability outcomes under unpredictability imposed by UUUR

Security analysis and modelling framework for critical infrastructure systems

The provision and delivery of many of the services that modern society enjoys are the result of ubiquitous critical infrastructure systems that permeate across many sectors of the Australian community. Moreover, the integration of technological enhancements and networking interconnections between critical infrastructure systems has heightened system interdependence, availability and resilience, including the efficient delivery of services to consumers within Australia\u27s industrialised society. This research delivers a system security analysis and system modelling framework tool based on an associated conceptual methodology as the basis for assessing security and conceptually modelling a critical infrastructure system incident. The intent to identify potential system security issues and gain operational insights that will contribute to improving system resilience, contingency planning development applicable to disaster recovery and ameliorating incident management responses for Australian critical infrastructure system incidents.<br /

Autonomic computing meets SCADA security

© 2017 IEEE. National assets such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks are critical infrastructures. The cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. Cyber security conventional measures have proved useful in the past but increasing sophistication of attacks dictates the need for newer measures. The autonomic computing paradigm mimics the autonomic nervous system and is promising to meet the latest challenges in the cyber threat landscape. This paper provides a brief review of autonomic computing applications for SCADA systems and proposes architecture for cyber security

A holistic approach for measuring the survivability of SCADA systems

Supervisory Control and Data Acquisition (SCADA) systems are responsible for controlling and monitoring Industrial Control Systems (ICS) and Critical Infrastructure Systems (CIS) among others. Such systems are responsible to provide services our society relies on such as gas, electricity, and water distribution. They process our waste; manage our railways and our traffic. Nevertheless to say, they are vital for our society and any disruptions on such systems may produce from financial disasters to ultimately loss of lives. SCADA systems have evolved over the years, from standalone, proprietary solutions and closed networks into large-scale, highly distributed software systems operating over open networks such as the internet. In addition, the hardware and software utilised by SCADA systems is now, in most cases, based on COTS (Commercial Off-The-Shelf) solutions. As they evolved they became vulnerable to malicious attacks. Over the last few years there is a push from the computer security industry on adapting their security tools and techniques to address the security issues of SCADA systems. Such move is welcome however is not sufficient, otherwise successful malicious attacks on computer systems would be non-existent. We strongly believe that rather than trying to stop and detect every attack on SCADA systems it is imperative to focus on providing critical services in the presence of malicious attacks. Such motivation is similar with the concepts of survivability, a discipline integrates areas of computer science such as performance, security, fault-tolerance and reliability. In this thesis we present a new concept of survivability; Holistic survivability is an analysis framework suitable for a new era of data-driven networked systems. It extends the current view of survivability by incorporating service interdependencies as a key property and aspects of machine learning. The framework uses the formalism of probabilistic graphical models to quantify survivability and introduces new metrics and heuristics to learn and identify essential services automatically. Current definitions of survivability are often limited since they either apply performance as measurement metric or use security metrics without any survivability context. Holistic survivability addresses such issues by providing a flexible framework where performance and security metrics can be tailored to the context of survivability. In other words, by applying performance and security our work aims to support key survivability properties such as recognition and resistance. The models and metrics here introduced are applied to SCADA systems as such systems insecurity is one of the motivations of this work. We believe that the proposed work goes beyond the current status of survivability models. Holistic survivability is flexible enough to support the addition of other metrics and can be easily used with different models. Because it is based on a well-known formalism its definition and implementation are easy to grasp and to apply. Perhaps more importantly, this proposed work is aimed to a new era where data is being produced and consumed on a large-scale. Holistic survivability aims to be the catalyst to new models based on data that will provide better and more accurate insights on the survivability of systems

A HOLISTIC APPROACH FOR SECURITY REQUIREMENT SPECIFICATION FOR LOW-COST, DISTRIBUTED UBIQUITOUS SYSTEMS

The class of low-cost, distributed ubiquitous systems represents a computing mode where a system has small, inexpensive networked processing devices, distributed at all scales throughout business activities and everyday life. The unique features of such a class of ubiquitous systems make the security analysis different from that for the centralized computing paradigms. This paper presents a holistic approach for security requirement analysis for low cost, distributed ubiquitous systems. Rigorous security analysis needs both quantitative and qualitative approaches to produce the holistic view and the robust data regarding the security features that a system must have in order to meet users’ security expectations. Our framework can assist system administrators to specify key security properties for a low-cost, distributed ubiquitous system and to define the specific security requirements for such a system. We applied Bayesian network and stochastic process algebra to incorporate probabilistic analysis to the framework

Increasing resilience of ATM networks using traffic monitoring and automated anomaly analysis

Systematic network monitoring can be the cornerstone for the dependable operation of safety-critical distributed systems. In this paper, we present our vision for informed anomaly detection through network monitoring and resilience measurements to increase the operators' visibility of ATM communication networks. We raise the question of how to determine the optimal level of automation in this safety-critical context, and we present a novel passive network monitoring system that can reveal network utilisation trends and traffic patterns in diverse timescales. Using network measurements, we derive resilience metrics and visualisations to enhance the operators' knowledge of the network and traffic behaviour, and allow for network planning and provisioning based on informed what-if analysis

Towards a Virtualized Next Generation Internet

A promising solution to overcome the Internet ossification is network virtualization in which Internet Service Providers (ISPs) are decoupled into two tiers: service providers (SPs), and infrastructure providers (InPs). The former maintain and customize virtual network(s) to meet the service requirement of end-users, which is mapped to the physical network infrastructure that is managed and deployed by the latter via the Virtual Network Embedding (VNE) process. VNE consists of two major components: node assignment, and link mapping, which can be shown to be NP-Complete. In the first part of the dissertation, we present a path-based ILP model for the VNE problem. Our solution employs a branch-and-bound framework to resolve the integrity constraints, while embedding the column generation process to effectively obtain the lower bound for branch pruning. Different from existing approaches, the proposed solution can either obtain an optimal solution or a near-optimal solution with guarantee on the solution quality. A common strategy in VNE algorithm design is to decompose the problem into two sequential sub-problems: node assignment (NA) and link mapping (LM). With this approach, it is inexorable to sacrifice the solution quality since the NA is not holistic and not-reversible. In the second part, we are motivated to answer the question: Is it possible to maintain the simplicity of the Divide-and-Conquer strategy while still achieving optimality? Our answer is based on a decomposition framework supported by the Primal-Dual analysis of the path-based ILP model. This dissertation also attempts to address issues in two frontiers of network virtualization: survivability, and integration of optical substrate. In the third part, we address the survivable network embedding (SNE) problem from a network flow perspective, considering both splittable and non-splittable flows. In addition, the explosive growth of the Internet traffic calls for the support of a bandwidth abundant optical substrate, despite the extra dimensions of complexity caused by the heterogeneities of optical resources, and the physical feature of optical transmission. In this fourth part, we present a holistic view of motivation, architecture, and challenges on the way towards a virtualized optical substrate that supports network virtualization

A Holistic Approach to Service Survivability

We present SABER (Survivability Architecture: Block, Evade, React), a proposed survivability architecture that blocks, evades and reacts to a variety of attacks by using several security and survivability mechanisms in an automated and coordinated fashion. Contrary to the ad hoc manner in which contemporary survivable systems are built--using isolated, independent security mechanisms such as firewalls, intrusion detection systems and software sandboxes--SABER integrates several different technologies in an attempt to provide a unified framework for responding to the wide range of attacks malicious insiders and outsiders can launch. This coordinated multi-layer approach will be capable of defending against attacks targeted at various levels of the network stack, such as congestion-based DoS attacks, software-based DoS or code-injection attacks, and others. Our fundamental insight is that while multiple lines of defense are useful, most conventional, uncoordinated approaches fail to exploit the full range of available responses to incidents. By coordinating the response, the ability to survive even in the face of successful security breaches increases substantially. We discuss the key components of SABER, how they will be integrated together, and how we can leverage on the promising results of the individual components to improve survivability in a variety of coordinated attack scenarios. SABER is currently in the prototyping stages, with several interesting open research topics