A policy-based security framework for ad-hoc networks

Imperial Users onl

Societal issues in machine learning: when learning from data is not enough

It has been argued that Artificial Intelligence (AI) is experiencing a fast process of commodification. Such characterization is on the interest of big IT companies, but it correctly reflects the current industrialization of AI. This phenomenon means that AI systems and products are reaching the society at large and, therefore, that societal issues related to the use of AI and Machine Learning (ML) cannot be ignored any longer. Designing ML models from this human-centered perspective means incorporating human-relevant requirements such as safety, fairness, privacy, and interpretability, but also considering broad societal issues such as ethics and legislation. These are essential aspects to foster the acceptance of ML-based technologies, as well as to ensure compliance with an evolving legislation concerning the impact of digital technologies on ethically and privacy sensitive matters. The ESANN special session for which this tutorial acts as an introduction aims to showcase the state of the art on these increasingly relevant topics among ML theoreticians and practitioners. For this purpose, we welcomed both solid contributions and preliminary relevant results showing the potential, the limitations and the challenges of new ideas, as well as refinements, or hybridizations among the different fields of research, ML and related approaches in facing real-world problems involving societal issues.Peer ReviewedPostprint (published version

LCT: A Lightweight Cross-domain Trust Model for the Mobile Distributed Environment

In the mobile distributed environment, an entity may move across domains with great frequency. How to utilize the trust information in the previous domains and quickly establish trust relationships with others in the current domain remains a challenging issue. The classic trust models do not support cross-domain and the existing cross-domain trust models are not in a fully distributed way

An investigation of issues of privacy, anonymity and multi-factor authentication in an open environment

This thesis performs an investigation into issues concerning the broad area ofIdentity and Access Management, with a focus on open environments. Through literature research the issues of privacy, anonymity and access control are identified. The issue of privacy is an inherent problem due to the nature of the digital network environment. Information can be duplicated and modified regardless of the wishes and intentions ofthe owner of that information unless proper measures are taken to secure the environment. Once information is published or divulged on the network, there is very little way of controlling the subsequent usage of that information. To address this issue a model for privacy is presented that follows the user centric paradigm of meta-identity. The lack of anonymity, where security measures can be thwarted through the observation of the environment, is a concern for users and systems. By an attacker observing the communication channel and monitoring the interactions between users and systems over a long enough period of time, it is possible to infer knowledge about the users and systems. This knowledge is used to build an identity profile of potential victims to be used in subsequent attacks. To address the problem, mechanisms for providing an acceptable level of anonymity while maintaining adequate accountability (from a legal standpoint) are explored. In terms of access control, the inherent weakness of single factor authentication mechanisms is discussed. The typical mechanism is the user-name and password pair, which provides a single point of failure. By increasing the factors used in authentication, the amount of work required to compromise the system increases non-linearly. Within an open network, several aspects hinder wide scale adoption and use of multi-factor authentication schemes, such as token management and the impact on usability. The framework is developed from a Utopian point of view, with the aim of being applicable to many situations as opposed to a single specific domain. The framework incorporates multi-factor authentication over multiple paths using mobile phones and GSM networks, and explores the usefulness of such an approach. The models are in tum analysed, providing a discussion into the assumptions made and the problems faced by each model.Adobe Acrobat Pro 9.5.1Adobe Acrobat 9.51 Paper Capture Plug-i

Understanding blockchain applications in Industry 4.0: From information technology to manufacturing and operations management

The current literature regarding blockchain-based applications in the context of Industry 4.0 has rapidly grown during the last decade. However, a systematic literature review that summarizes the main contributions, findings, and implications from a managerial perspective of the blockchain technology adoption in the specific context of Industry 4.0 is still missing. The present article aims to fill this research gap by examining and elaborating on the extant literature to develop a literature-grounded framework (WHY-HOW-WHAT) that helps better understand the management issues that blockchain technology can help resolve in the context of Industry 4.0, as well as identify the main features of blockchain-based solutions in various areas of Industry 4.0. Furthermore, the proposed framework is useful to understand how ten Industry 4.0 enabling technologies combine with the blockchain technology to implement efficient and effective blockchain-based solutions in Industry 4.0 settings. Finally, based on this framework we conjecture the trajectories of the evolution of blockchain technology in Industry 4.0 settings, and highlight the relevant research gaps that both academics and practitioners working on this field should address in the near future