Network operator intent : a basis for user-friendly network configuration and analysis

Two important network management activities are configuration (making the network behave in a desirable way) and analysis (querying the network’s state). A challenge common to these activities is specifying operator intent. Seemingly simple configurations such as “no network user should exceed their allocated bandwidth” or questions like “how many network devices are in the library?” are difficult to formulate in practice, e.g. they may require multiple tools (like access control lists, firewalls, databases, or accounting software) and a detailed knowledge of the network. This requires a high degree of expertise and experience, and even then, mistakes are common. An understanding of the core concepts that network operators manipulate and analyse is needed so that more effective, efficient, and user-friendly tools and processes can be created. To address this, we create a taxonomy of languages for configuring networks, and use it to evaluate three such languages to learn how operators can express their intent. We identify factors such as language features, testing, state modeling, documentation, and tool support. Then, we interview network operators to understand what they want to express. We analyse the interviews and identify nine orthogonal dimensions which frequently appear in expressions of operator intent. We use these concepts, and our taxonomy, as the basis for a language for querying both business- and network-domain data. We evaluate our language and find that it reduces the number and complexity of queries needed to answer questions about networks. We also conduct a user study, and find that our language reduces novices’ cognitive load while increasing their accuracy and efficiency. With our language, users better understand how to approach questions, can more easily express themselves, and make fewer mistakes when interpreting data. Overall, we find that operator intent can, at one extreme, be expressed directly, as primitives like flow rules, packet counters, or CLI commands, and at another extreme as human-readable statements which are automatically translated and implemented. The former gives operators precise control, but the latter may be easier to use. We also find that there is more to expressing intent than syntax and semantics as usability, redundancy, state manipulation, and ecosystems all play a role. Our findings also show the importance of incorporating business-domain concepts in network management tools. By understanding operator intent we can reduce errors, improve both human-human and human-computer communication, create more usable tools, and make network operators more effective

Development of a governance framework for delivery of collaborative and security-minded BIM projects

This study explores secure-collaboration for BIM projects in response to concerns as to whetherproject environments concerned with critical national infrastructure are able to govern digitalsecurity-risks whilst also reconciling tensions between collaborative motives, leading to difficultiesin sharing enough information to ensure stakeholder efficiency whilst not exposing sensitivitiesand elevating security-risk. This research aims to address these issues by: Devising a conceptualprocess and data governance framework to enable secure collaboration for BIM projects. Inachieving this aim, the study captures the framework’s requirements by answering the firstresearch question: What is the nature of tensions between collaboration and security motiveswithin security-minded BIM projects that are barriers to achieving secure-collaboration? Thisquestion’s answer is central to answering the second question: What is the nature of the processand data governance framework that is required to resolve existing tensions and enable securecollaboration?This thesis captures requirements via a thorough study (primary and secondary) in the contextof security-minded BIM projects. The design-science methodology was adopted to guide theframework development and evaluation; semi-structured interviews with 13 experts were used todiagnose the tensions concerning: security-risk governance, BIM process and technologyimplementation, alongside BIM governance limitations. Based upon findings, the framework’srequirements for comprising process and data governance concepts were developed. Theframework was evaluated with 8 experts via a qualitative feedback categorisation technique toassess its capacity to facilitate secure-collaboration.The outcome of the diagnostics process revealed that tensions arise within projects due to a lackof a holistic security-risk governance approach, and a misalignment between project collaborationand security requirements. This leads to a cascade of incompatible project implementationxviiichoices, which limits the efficacy of information governance to appropriately secure critical assets,whilst diminishing collaboration capacity to ensure a timely and cost-effective project-delivery.Stakeholders are also constrained by security-measures which are not integrated with theirinformational needs, resulting in issues such as securely coordinating sensitive informationamongst partners, or professionals being unable to access information due to inaccuratesensitivity classification and clearance constraints. These tensions are also linked to divergentcultural pressures for increased digitisation and openness, versus the need for security-mindedapproaches which are accompanied by administrative, commercial and contractual burdens.These tensions are the sources of great frustration within security-minded environmentsinterviewed in effortlessly achieving secure collaboration, whereas a bleaker picture is present forthe broader AEC sector as to whether organisations can support the secure digitisation needs ofinexperienced clients and protect their assets within an evolving digital security-risk landscape.Alleviating such tensions requires clients to apply holistic security-risk governance approachesand define integrated project requirements that reconcile security, collaboration and efficiencymotives. Findings also indicate that information-flow tensions are present for professionals to beable to seamlessly share and receive only the necessary information, when and to who necessary,at an appropriate and secured level of detail. Alleviating such tensions is difficult as they are tiedto the limitations of BIM-based governance approaches utilised within practices. To resolve suchinformation-flow tensions, findings propose that the key elements to be integrated into theprocess and data governance framework are considerations for information planning, transactionand governance concepts. At an overarching level, this is by ensuring practitioners securely shareand receive only the atomic information-sets which are necessary for them to deliver high-qualityproject outcomes. The proposed framework has been validated via a high-level qualitativetechnique as the framework is conceptual in nature. Therefore, future research is required toimplement and validate the framework in real-life project settings

Multidisciplinary perspectives on Artificial Intelligence and the law

This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio