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

The Vital Network: An Algorithmic Milieu of Communication and Control

The biological turn in computing has influenced the development of algorithmic control and what I call the vital network: a dynamic, relational, and generative assemblage that is self-organizing in response to the heterogeneity of contemporary network processes, connections, and communication. I discuss this biological turn in computation and control for communication alongside historically significant developments in cybernetics that set out the foundation for the development of self-regulating computer systems. Control is shifting away from models that historically relied on the human-animal model of cognition to govern communication and control, as in early cybernetics and computer science, to a decentred, nonhuman model of control by algorithm for communication and networks. To illustrate the rise of contemporary algorithmic control, I outline a particular example, that of the biologically-inspired routing algorithm known as a ‘quorum sensing’ algorithm. The increasing expansion of algorithms as a sense-making apparatus is important in the context of social media, but also in the subsystems that coordinate networked flows of information. In that domain, algorithms are not inferring categories of identity, sociality, and practice associated with Internet consumers, rather, these algorithms are designed to act on information flows as they are transmitted along the network. The development of autonomous control realized through the power of the algorithm to monitor, sort, organize, determine, and transmit communication is the form of control emerging as a postscript to Gilles Deleuze’s ‘postscript on societies of control.

Future Roles for Autonomous Vertical Lift in Disaster Relief and Emergency Response

System analysis concepts are applied to the assessment of potential collaborative contributions of autonomous system and vertical lift (a.k.a. rotorcraft, VTOL, powered-lift, etc.) technologies to the important, and perhaps underemphasized, application domain of disaster relief and emergency response. In particular, an analytic framework is outlined whereby system design functional requirements for an application domain can be derived from defined societal good goals and objectives

An Embryonics Inspired Architecture for Resilient Decentralised Cloud Service Delivery

Data-driven artificial intelligence applications arising from Internet of Things technologies can have profound wide-reaching societal benefits at the cross-section of the cyber and physical domains. Usecases are expanding rapidly. For example, smart-homes and smart-buildings provide intelligent monitoring, resource optimisation, safety, and security for their inhabitants. Smart cities can manage transport, waste, energy, and crime on large scales. Whilst smart-manufacturing can autonomously produce goods through the self-management of factories and logistics. As these use-cases expand further, the requirement to ensure data is processed accurately and timely is ever crucial, as many of these applications are safety critical. Where loss off life and economic damage is a likely possibility in the event of system failure. While the typical service delivery paradigm, cloud computing, is strong due to operating upon economies of scale, their physical proximity to these applications creates network latency which is incompatible with these safety critical applications. To complicate matters further, the environments they operate in are becoming increasingly hostile. With resource-constrained and mobile wireless networking, commonplace. These issues drive the need for new service delivery architectures which operate closer to, or even upon, the network devices, sensors and actuators which compose these IoT applications at the network edge. These hostile and resource constrained environments require adaptation of traditional cloud service delivery models to these decentralised mobile and wireless environments. Such architectures need to provide persistent service delivery within the face of a variety of internal and external changes or: resilient decentralised cloud service delivery. While the current state of the art proposes numerous techniques to enhance the resilience of services in this manner, none provide an architecture which is capable of providing data processing services in a cloud manner which is inherently resilient. Adopting techniques from autonomic computing, whose characteristics are resilient by nature, this thesis presents a biologically-inspired platform modelled on embryonics. Embryonic systems have an ability to self-heal and self-organise whilst showing capacity to support decentralised data processing. An initial model for embryonics-inspired resilient decentralised cloud service delivery is derived according to both the decentralised cloud, and resilience requirements given for this work. Next, this model is simulated using cellular automata, which illustrate the embryonic concept’s ability to provide self-healing service delivery under varying system component loss. This highlights optimisation techniques, including: application complexity bounds, differentiation optimisation, self-healing aggression, and varying system starting conditions. All attributes of which can be adjusted to vary the resilience performance of the system depending upon different resource capabilities and environmental hostilities. Next, a proof-of-concept implementation is developed and validated which illustrates the efficacy of the solution. This proof-of-concept is evaluated on a larger scale where batches of tests highlighted the different performance criteria and constraints of the system. One key finding was the considerable quantity of redundant messages produced under successful scenarios which were helpful in terms of enabling resilience yet could increase network contention. Therefore balancing these attributes are important according to use-case. Finally, graph-based resilience algorithms were executed across all tests to understand the structural resilience of the system and whether this enabled suitable measurements or prediction of the application’s resilience. Interestingly this study highlighted that although the system was not considered to be structurally resilient, the applications were still being executed in the face of many continued component failures. This highlighted that the autonomic embryonic functionality developed was succeeding in executing applications resiliently. Illustrating that structural and application resilience do not necessarily coincide. Additionally, one graph metric, assortativity, was highlighted as being predictive of application resilience, although not structural resilience

Self-Organization and Resilience for Networked Systems:Design Principles and Open Research Issues

Networked systems form the backbone of modern society, underpinning critical infrastructures such as electricity, water, transport and commerce, and other essential services (e.g., information, entertainment, and social networks). It is almost inconceivable to contemplate a future without even more dependence on them. Indeed, any unavailability of such critical systems is--even for short periods--a rather bleak prospect. However, due to their increasing size and complexity, they also require some means of autonomic formation and self-organization. This paper identifies the design principles and open research issues in the twin fields of self-organization and resilience for networked systems. In combination, they offer the prospect of combating threats and allowing essential services that run on networked systems to continue operating satisfactorily. This will be achieved, on the one hand, through the (self-)adaptation of networked systems and, on the other hand, through structural and operational resilience techniques to ensure that they can detect, defend against, and ultimately withstand challenges

Autonomic and Apoptotic, Aeronautical and Aerospace Systems, and Controlling Scientific Data Generated Therefrom

A self-managing system that uses autonomy and autonomicity is provided with the self-* property of autopoiesis (self-creation). In the event of an agent in the system self-destructing, autopoiesis auto-generates a replacement. A self-esteem reward scheme is also provided and can be used for autonomic agents, based on their performance and trust. Art agent with greater self-esteem may clone at a greater rate compared to the rate of an agent with lower self-esteem. A self-managing system is provided for a high volume of distributed autonomic/self-managing mobile agents, and autonomic adhesion is used to attract similar agents together or to repel dissimilar agents from an event horizon. An apoptotic system is also provided that accords an "expiry date" to data and digital objects, for example, that are available on the internet, which finds usefulness not only in general but also for controlling the loaning and use of space scientific data

BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK

With the explosive development of the critical services network systems and Internet, the need for networks security systems have become even critical with the enlargement of information technology in everyday life. Intrusion Prevention System (IPS) provides an in-line mechanism focus on identifying and blocking malicious network activity in real time. This thesis presents new intrusion prevention and self-healing system (SH) for critical services network security. The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. Firstly, the current intrusions preventions systems, biological innate and adaptive immune systems, autonomic computing and self-healing mechanisms are studied and analyzed. The importance of intrusion prevention system recommends that artificial immune systems (AIS) should incorporate abstraction models from innate, adaptive immune system, pattern recognition, machine learning and self-healing mechanisms to present autonomous IPS system with fast and high accurate detection and prevention performance and survivability for critical services network system. Secondly, specification language, system design, mathematical and computational models for IPS and SH system are established, which are based upon nonlinear classification, prevention predictability trust, analysis, self-adaptation and self-healing algorithms. Finally, the validation of the system carried out by simulation tests, measuring, benchmarking and comparative studies. New benchmarking metrics for detection capabilities, prevention predictability trust and self-healing reliability are introduced as contributions for the IPS and SH system measuring and validation. Using the software system, design theories, AIS features, new nonlinear classification algorithm, and self-healing system show how the use of presented systems can ensure safety for critical services networks and heal the damage caused by intrusion. This autonomous system improves the performance of the current intrusion prevention system and carries on system continuity by using self-healing mechanism

Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems