Using Delay Tolerant Networks as a Backbone for Low-cost Smart Cities

Rapid urbanization burdens city infrastructure and creates the need for local governments to maximize the usage of resources to serve its citizens. Smart city projects aim to alleviate the urbanization problem by deploying a vast amount of Internet-of-things (IoT) devices to monitor and manage environmental conditions and infrastructure. However, smart city projects can be extremely expensive to deploy and manage. A significant portion of the expense is a result of providing Internet connectivity via 5G or WiFi to IoT devices. This paper proposes the use of delay tolerant networks (DTNs) as a backbone for smart city communication; enabling developing communities to become smart cities at a fraction of the cost. A model is introduced to aid policy makers in designing and evaluating the expected performance of such networks. Preliminary results are presented based on a public transit network data-set from Chapel Hill, North Carolina. Finally, innovative ways of improving network performance in a low-cost smart city is discussed.Comment: 3 pages, accepted to IEEE SmartComp 201

Management And Security Of Multi-Cloud Applications

Single cloud management platform technology has reached maturity and is quite successful in information technology applications. Enterprises and application service providers are increasingly adopting a multi-cloud strategy to reduce the risk of cloud service provider lock-in and cloud blackouts and, at the same time, get the benefits like competitive pricing, the flexibility of resource provisioning and better points of presence. Another class of applications that are getting cloud service providers increasingly interested in is the carriers\u27 virtualized network services. However, virtualized carrier services require high levels of availability and performance and impose stringent requirements on cloud services. They necessitate the use of multi-cloud management and innovative techniques for placement and performance management. We consider two classes of distributed applications – the virtual network services and the next generation of healthcare – that would benefit immensely from deployment over multiple clouds. This thesis deals with the design and development of new processes and algorithms to enable these classes of applications. We have evolved a method for optimization of multi-cloud platforms that will pave the way for obtaining optimized placement for both classes of services. The approach that we have followed for placement itself is predictive cost optimized latency controlled virtual resource placement for both types of applications. To improve the availability of virtual network services, we have made innovative use of the machine and deep learning for developing a framework for fault detection and localization. Finally, to secure patient data flowing through the wide expanse of sensors, cloud hierarchy, virtualized network, and visualization domain, we have evolved hierarchical autoencoder models for data in motion between the IoT domain and the multi-cloud domain and within the multi-cloud hierarchy

Architecture-centric support for security orchestration and automation

Security Orchestration, Automation and Response (SOAR) platforms leverage integration and orchestration technologies to (i) automate manual and repetitive labor-intensive tasks, (ii) provide a single panel of control to manage various types of security tools (e.g., intrusion detection system, antivirus and firewall) and (iii) streamline complex Incident Response Process (IRP) responses. SOAR platforms increase the operational efficiency of overwhelmed security teams in a Security Operation Centre (SOC) and accelerate the SOC’s defense and response capacity against ever-growing security incidents. Security tools, IRPs and security requirements form the underlying execution environment of SOAR platforms, which are changing rapidly due to the dynamic nature of security threats. A SOAR platform is expected to adapt continuously to these dynamic changes. Flexible integration, interpretation and interoperability of security tools are essential to ease the adaptation of a SOAR platform. However, most of the effort for designing and developing existing SOAR platforms are ad-hoc in nature, which introduces several engineering challenges and research challenges. For instance, the advancement of a SOAR platform increases its architectural complexity and makes the operation of such platforms difficult for end-users. These challenges come from a lack of a comprehensive view, design space and architectural support for SOAR platforms. This thesis aims to contribute to the growing realization that it is necessary to advance SOAR platforms by designing, implementing and evaluating architecture-centric support to address several of the existing challenges. The envisioned research and development activities require the identification of current practices and challenges of SOAR platforms; hence, a Multivocal Literature Review (MLR) has been designed, conducted and reported. The MLR identifies the functional and non-functional requirements, components and practices of a security orchestration domain, along with the open issues. This thesis advances the domain of a SOAR platform by providing a layered architecture, which considers the key functional and non-functional requirements of a SOAR platform. The proposed architecture is evaluated experimentally with a Proof of Concept (PoC) system, Security Tool Unifier (STUn), using seven security tools, a set of IRPs and playbooks. The research further identifies the need for and design of (i) an Artificial Intelligence (AI) based integration framework to interpret the activities of security tools and enable interoperability automatically, (ii) a semantic-based automated integration process to integrate security tools and (iii) AI-enabled design and generation of a declarative API from user query, namely DecOr, to hide the internal complexity of a SOAR platform from end-users. The experimental evaluation of the proposed approaches demonstrates that (i) consideration of architectural design decisions supports the development of an easy to interact with, modify and update SOAR platform, (ii) an AI-based integration framework and automated integration process provides effective and efficient integration and interpretation of security tools and IRPs and (iii) DecOr increases the usability and flexibility of a SOAR platform. This thesis is a useful resource and guideline for both practitioners and researchers who are working in the security orchestration domain. It provides an insight into how an architecture-centric approach, with incorporation of AI technologies, reduces the operational complexity of SOAR platforms.Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 202

Foundations of Human-Aware Planning -- A Tale of Three Models

abstract: A critical challenge in the design of AI systems that operate with humans in the loop is to be able to model the intentions and capabilities of the humans, as well as their beliefs and expectations of the AI system itself. This allows the AI system to be "human- aware" -- i.e. the human task model enables it to envisage desired roles of the human in joint action, while the human mental model allows it to anticipate how its own actions are perceived from the point of view of the human. In my research, I explore how these concepts of human-awareness manifest themselves in the scope of planning or sequential decision making with humans in the loop. To this end, I will show (1) how the AI agent can leverage the human task model to generate symbiotic behavior; and (2) how the introduction of the human mental model in the deliberative process of the AI agent allows it to generate explanations for a plan or resort to explicable plans when explanations are not desired. The latter is in addition to traditional notions of human-aware planning which typically use the human task model alone and thus enables a new suite of capabilities of a human-aware AI agent. Finally, I will explore how the AI agent can leverage emerging mixed-reality interfaces to realize effective channels of communication with the human in the loop.Dissertation/ThesisDoctoral Dissertation Computer Science 201

In the Wild:Student Insights on Innovation Practice in the Real World

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Computer Aided Verification

The open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency