Using Alliances to Increase ICT Capabilities

Information and Communication Technology (ICT) is perhaps the most important, emblematic and ubiquitous technology of contemporary society. ICT is used increasingly in new product areas and help resolve problems and challenges to mankind; it has even gotten to a point where life without ICT is hard to imagine. Over the last decades ICT has become a core technology within the music, literature and media and many other industries, and reshaped the way we consume these services. For many incumbent firms, the infusion of ICT into their industries poses both threats and opportunities. It might drive significant shifts of financial wealth and make firm performance change drastically. It entails managerial challenges of a kind we might not have seen before, but where knowledge of what possibilities and limitations reside in ICT will be a key success factor. There are several possible ways to approach this challenge from ICT: recruitment, education, training, socialization and M&A are but a few examples. Another way is for the incumbents to team up with ICT firms and seek to learn, or at least access, the knowledge required to utilize the inherent power of ICT. This means that having an alliance, or even an alliance capability that lets you develop an ICT capability will be important. This thesis deals precisely with the challenges that arise when incumbents ally with ICT firms – our case is the security industry, which has had a strong analogue technology base in the past, but where ICT offers opportunity for business development now as well as in the foreseeable future. Based on a theoretical frame of reference, this book then uses empirical observations from four alliances within the evolving, global security industry to validate and develop an alliance framework that can be a great help to both practitioners as well as academia. Even though we suggest to approach the question of alliances with a three-legged model including Transfer Capacity, Relationship Governance and Cultural fit the framework in essence the framework caters for attempts at accessing knowledge and, thanks to the empirical conclusions made, alliances where the main benefit in the end might differ from initial aspirations. It also highlights the sometimes serendipitous and unexpected results of alliances, and that higher aspirations might have to be replaced by more modest ambitions. The fact of the matter is that that sometimes, grand visions of knowledge exchange and accumulation are simply not reachable. In fast-moving industries such as ICT, there might not be time and incentive enough to actually transfer knowledge, but instead ally to access finished products

Technological Incarceration and the End of the Prison Crisis

The United States imprisons more of its people than any nation on Earth, and by a considerable margin. Criminals attract little empathy and have no political capital. Consequently, it is not surprising that, over the past forty years, there have been no concerted or unified efforts to stem the rapid increase in incarceration levels in the United States. Nevertheless, there has recently been a growing realization that even the world’s biggest economy cannot readily sustain the $80 billion annual cost of imprisoning more than two million of its citizens. No principled, wide-ranging solution has yet been advanced, however. To resolve the crisis, this Article proposes a major revolution to the prison sector that would see technology, for the first time, pervasively incorporated into the punishment of criminals and result in the closure of nearly all prisons in the United States. The alternative to prison that we propose involves the fusion of three technological systems. First, offenders would be required to wear electronic ankle bracelets that monitor their location and ensure they do not move outside of the geographical areas to which they would be confined. Second, prisoners would be compelled to wear sensors so that unlawful or suspicious activity could be monitored remotely by computers. Third, conducted energy devices would be used remotely to immobilize prisoners who attempt to escape their areas of confinement or commit other crimes. The integrated systems described in this Article could lead to the closure of more than 95% of prisons in the United States. We demonstrate that the technological and surveillance devices can achieve all of the appropriate objectives of imprisonment, including the imposition of proportionate punishment and community protection. In our proposal, only offenders who have committed capital offenses or equivalent crimes, or who attempt to escape from technological custody, would remain in conventional brick-and-mortar prisons. As a result, our proposal would convert prisons from a major societal industry to a curious societal anomaly. If these reforms are implemented, the United States would spend a fraction of the amount currently expended on conventional prisons on a normatively superior mechanism for dealing with society’s criminals

Introducing Disruptive Technology to Criminal Sanctions: Punishment by Computer Monitoring to Enhance Sentencing Fairness and Efficiency

The United States criminal justice system is the most punitive on earth. The total correctional population is nearly seven million, equating to a staggering one in thirty-eight adults. Most of the correctional population comprises offenders who are on parole or probation, and a high portion of these defendants who are on parole or probation reoffend during the sanction period. There has been a growing consensus among lawmakers and the wider community that reforms need to be implemented to reduce the cost of criminal sanctions and to improve their effectiveness. For example, the United States Sentencing Commission has recently proposed an amendment to increase the availability of sentences as alternatives to incarceration. Yet, with little hint of exaggeration, the sentencing system remains in a primitive state when it comes to adopting technological advances. This article seeks to address this failing as a means of overcoming the main shortcomings of current common criminal sanctions. Forty years ago, it was suggested that the most effective way to deal with crime was to assign a police officer to watch over each offender’s every move. The proposal was dubbed “cop-a-con,” and was unviable due to its excessive costs. Yet, technological advances now make this concept, or a similar concept, achievable in a cost-effective manner. This article argues that the sanctions that are currently utilized to deal with the most serious offenders—namely imprisonment, probation, and parole—can be replaced with technological monitoring, which can more efficiently, effectively, and humanely achieve the appropriate objectives of sentencing. Technological disruption in the criminal justice sector is not only desirable, but it is also imperative. Financial pressures and normative principles mandate that the United States can no longer remain the world’s most punitive nation. This article proposes a monitoring sanction using technological advances. This solution has the potential to more efficiently and economically impose proportionate punishment than current probation and parole systems do, while enhancing public safety

Demystifying Internet of Things Security

Break down the misconceptions of the Internet of Things by examining the different security building blocks available in Intel Architecture (IA) based IoT platforms. This open access book reviews the threat pyramid, secure boot, chain of trust, and the SW stack leading up to defense-in-depth. The IoT presents unique challenges in implementing security and Intel has both CPU and Isolated Security Engine capabilities to simplify it. This book explores the challenges to secure these devices to make them immune to different threats originating from within and outside the network. The requirements and robustness rules to protect the assets vary greatly and there is no single blanket solution approach to implement security. Demystifying Internet of Things Security provides clarity to industry professionals and provides and overview of different security solutions What You'll Learn Secure devices, immunizing them against different threats originating from inside and outside the network Gather an overview of the different security building blocks available in Intel Architecture (IA) based IoT platforms Understand the threat pyramid, secure boot, chain of trust, and the software stack leading up to defense-in-depth Who This Book Is For Strategists, developers, architects, and managers in the embedded and Internet of Things (IoT) space trying to understand and implement the security in the IoT devices/platforms

Cyber-Physical Threat Intelligence for Critical Infrastructures Security

Modern critical infrastructures comprise of many interconnected cyber and physical assets, and as such are large scale cyber-physical systems. Hence, the conventional approach of securing these infrastructures by addressing cyber security and physical security separately is no longer effective. Rather more integrated approaches that address the security of cyber and physical assets at the same time are required. This book presents integrated (i.e. cyber and physical) security approaches and technologies for the critical infrastructures that underpin our societies. Specifically, it introduces advanced techniques for threat detection, risk assessment and security information sharing, based on leading edge technologies like machine learning, security knowledge modelling, IoT security and distributed ledger infrastructures. Likewise, it presets how established security technologies like Security Information and Event Management (SIEM), pen-testing, vulnerability assessment and security data analytics can be used in the context of integrated Critical Infrastructure Protection. The novel methods and techniques of the book are exemplified in case studies involving critical infrastructures in four industrial sectors, namely finance, healthcare, energy and communications. The peculiarities of critical infrastructure protection in each one of these sectors is discussed and addressed based on sector-specific solutions. The advent of the fourth industrial revolution (Industry 4.0) is expected to increase the cyber-physical nature of critical infrastructures as well as their interconnection in the scope of sectorial and cross-sector value chains. Therefore, the demand for solutions that foster the interplay between cyber and physical security, and enable Cyber-Physical Threat Intelligence is likely to explode. In this book, we have shed light on the structure of such integrated security systems, as well as on the technologies that will underpin their operation. We hope that Security and Critical Infrastructure Protection stakeholders will find the book useful when planning their future security strategies

Intelligent Systems Supporting the Use of Energy Systems and Other Complex Technical Objects, Modeling, Testing and Analysis of Their Reliability in the Operation Process

The book focuses on a novel application of Intelligent Systems for supporting the operation and maintenance of power systems or other technical facilities within wind farms. Indicating a different perception of the reliability of wind farm facilities led to the possibility of extending the operation lifetime and operational readiness of wind farm equipment. Additionally, the presented approach provides a basis for extending its application to the testing and analysis of other technical facilities

Robots learn to behave: improving human-robot collaboration in flexible manufacturing applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Safe navigation and human-robot interaction in assistant robotic applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Profiling IoT botnet activity

Undoubtedly, Internet of Things (IoT) devices have evolved into a necessity within our modern lifestyles. Nonetheless, IoT devices have proved to pose significant security risks due to their vulnerabilities and susceptibility to malware. Evidently, vulnerable IoT devices are enlisted by attackers to participate into Internet-wide botnets in order to instrument large-scale cyber-attacks and disrupt critical Internet services. Tracking these botnets is challenging due to their varying structural characteristics, and also due to the fact that malicious actors continuously adopt new evasion and propagation strategies. This thesis develops BotPro framework, a novel data-driven approach for profiling IoT botnet behaviour. BotPro provides a comprehensive approach for capturing and highlighting the behavioural properties of IoT botnets with respect to their structural and propagation properties across the global Internet. We implement the proposed framework using real-world data obtained from the measurement infrastructure that was designed in this thesis. Our measurement infrastructure gathers data from various sources, including globally distributed honeypots, regional Internet registries, global IP blacklists and routing topology. This diverse dataset forms a strong foundation for profiling IoT botnet activity, ensuring that our analysis accurately reflects behavioural patterns of botnets in real-world scenarios. BotPto encompasses diverse methods to profile IoT botnets, including information theory, statistical analysis, natural language processing, machine learning and graph theory. The framework’s results provide insights related to the structural properties as well as the evolving scanning and propagation strategies of IoT botnets. It also provides evidence on concentrated botnet activities and determines the effectiveness of widely used IP blacklists on capturing their evolving behaviour. In addition, the insights reveal the strategy adopted by IoT botnets in expanding their network and increasing their level of resilience. The results provide a compilation of the most important autonomous system(AS) attributes that frequently embrace IoT botnet activity as well as provide a novel macroscopic view on the influence of AS-level relationships with respect to IoT botnet propagation. Furthermore, It provides insights into the structural properties of botnet loaders with respect to the distribution of malware binaries of various strains. The insights generated by BotPro are essential to equip next generation automated cyber threat intelligence, intrusion detection systems and anomaly detection mechanisms with enriched information regarding evolving scanning, establishment and propagation strategies of new botnet variants. Industry will be equipped with even more improved ways to defend against emerging threats in the domains of cyber warfare, cyber tourism and cybercrime. The BotPro framework provides a comprehensive platform for stakeholders, including cybersecurity researchers, security analysts and network administrators to gain deep and meaningful insights into the sophisticated activities and behaviour exhibited by IoT botnets

Unusual event detection in real-world surveillance applications

Given the near-ubiquity of CCTV, there is significant ongoing research effort to apply image and video analysis methods together with machine learning techniques towards autonomous analysis of such data sources. However, traditional approaches to scene understanding remain dependent on training based on human annotations that need to be provided for every camera sensor. In this thesis, we propose an unusual event detection and classification approach which is applicable to real-world visual monitoring applications. The goal is to infer the usual behaviours in the scene and to judge the normality of the scene on the basis on the model created. The first requirement for the system is that it should not demand annotated data to train the system. Annotation of the data is a laborious task, and it is not feasible in practice to annotate video data for each camera as an initial stage of event detection. Furthermore, even obtaining training examples for the unusual event class is challenging due to the rarity of such events in video data. Another requirement for the system is online generation of results. In surveillance applications, it is essential to generate real-time results to allow a swift response by a security operator to prevent harmful consequences of unusual and antisocial events. The online learning capabilities also mean that the model can be continuously updated to accommodate natural changes in the environment. The third requirement for the system is the ability to run the process indefinitely. The mentioned requirements are necessary for real-world surveillance applications and the approaches that conform to these requirements need to be investigated. This thesis investigates unusual event detection methods that conform with real-world requirements and investigates the issue through theoretical and experimental study of machine learning and computer vision algorithms