TACTICAL BLOCKCHAIN TO PROVIDE DATA PROVENANCE IN SUPPORT OF INTERNET OF BATTLEFIELD THINGS AND BIG DATA ANALYTICS

This capstone project evaluated the use of blockchain technology to address a number of challenges with increasing amounts of disparate sensor data and an information-rich landscape that can quickly overwhelm effective decision-making processes. The team explored how blockchain can be used in a variety of defense applications to verify users, validate sensor data fed into artificial intelligence models, limit access to data, and provide an audit trail across the data life cycle. The team developed a conceptual design for implementing blockchain for tactical data, artificial intelligence, and machine learning applications; identified challenges and limitations involved in implementing blockchain for the tactical domain; described the benefits of blockchain for these various applications; and evaluated this project’s findings to propose future research into a wider set of blockchain applications. The team did this through the development of three use cases. One use case demonstrated the use of blockchain at the tactical edge in a “data light” information environment. The second use case explored the use of blockchain in securing medical information in the electronic health record. The third use case studied blockchain’s application in the use of multiple sensors collecting data for chemical weapons defense to support measurement and signature intelligence analysis using artificial intelligence and machine learning.Civilian, Department of the ArmyCivilian, Department of the ArmyCivilian, Department of the ArmyCivilian, Department of the ArmyCivilian, Department of the ArmyApproved for public release. Distribution is unlimited

Cyber Supply Chain Risk Management: Implications for the SOF Future Operating Environment

The emerging Cyber Supply Chain Risk Management (C-SCRM) concept assists at all levels of the supply chain in managing and mitigating risks, and the authors define C-SCRM as the process of identifying, assessing, and mitigating the risks associated with the distributed and interconnected nature of information and operational technology products and service supply chains. As Special Operations Forces increasingly rely on sophisticated hardware and software products, this quick, well-researched monograph provides a detailed accounting of C-SCRM associated laws, regulations, instructions, tools, and strategies meant to mitigate vulnerabilities and risks—and how we might best manage the evolving and ever-changing array of those vulnerabilities and risks

Why the Failure? How Adversarial Examples Can Provide Insights for Interpretable Machine Learning

Recent advances in Machine Learning (ML) have profoundly changed many detection, classification, recognition and inference tasks. Given the complexity of the battlespace, ML has the potential to revolutionise how Coalition Situation Understanding is synthesised and revised. However, many issues must be overcome before its widespread adoption. In this paper we consider two - interpretability and adversarial attacks. Interpretability is needed because military decision-makers must be able to justify their decisions. Adversarial attacks arise because many ML algorithms are very sensitive to certain kinds of input perturbations. In this paper, we argue that these two issues are conceptually linked, and insights in one can provide insights in the other. We illustrate these ideas with relevant examples from the literature and our own experiments

THE INTERNET OF THINGS (IOT) IN DISASTER RESPONSE

Disaster management is a complex practice that relies on access to and the usability of critical information to develop strategies for effective decision-making. The emergence of wearable internet of things (IoT) technology has attracted the interests of several major industries, making it one of the fastest-growing technologies to date. This thesis asks, How can disaster management incorporate wearable IoT technology in operations and decision-making practices in disaster response? How IoT is applied in other prominent industries, including construction, manufacturing and distribution, the Department of Defense, and public safety, provides a basis for furthering its application to challenges affecting agency coordination. The critical needs of disaster intelligence in the context of hurricanes, structural collapses, and wildfires are scrutinized to identify gaps that wearable technology could address in terms of information-sharing in multi-agency coordination and the decision-making practices that routinely occur in disaster response. Last, the specifics of wearable technology from the perspective of the private consumer and commercial industry illustrate its potential to improve disaster response but also acknowledge certain limitations including technical capabilities and information privacy and security.Civilian, Virginia Beach Fire Department / FEMA - USAR VATF-2Approved for public release. Distribution is unlimited

Optimizing the treatment of locally advanced and recurrent rectal cancer

An important goal in the treatment of locally advanced rectal cancer is to reduce the risk of metastases and increase quality of life. Four chapters of this dissertation describe the results of the RAPIDO trial. This study compares 2 types of treatment for locally advanced rectal cancer. The standard treatment consists of long-term chemoradiotherapy, surgery, and possibly chemotherapy. The experimental treatment consists of short-course radiation followed by chemotherapy and then surgery. The experimental treatment showed a significant improvement in disease-related treatment failure at 3 and 5 years after surgery. This difference was explained by a significant decrease in the number of metastases. However, after 5 years, there are a fraction more patients with local recurrence of disease in the experimental treatment. In addition, this study shows that there is no difference in quality of life after 3 years. However, those in the experimental group do experience tingling in the toes and fingers more often. Furthermore, this dissertation shows that during surgery in case of the primary tumour in 58.3% of cases we gave radiotherapy too often when it was not necessary, and in the case of recurrence of disease in 26.5% of cases we gave it too little.In addition, we have shown that it is safe to provide chemoradiotherapy again to a patient who has local recurrence of disease and has also initially received chemoradiotherapy for their primary tumour

A systematic literature review of blockchain cyber security

Since the publication of Satoshi Nakamoto's white paper on Bitcoin in 2008, blockchain has (slowly) become one of the most frequently discussed methods for securing data storage and transfer through decentralized, trustless, peer-to-peer systems. This research identifies peer-reviewed literature that seeks to utilize blockchain for cyber security purposes and presents a systematic analysis of the most frequently adopted blockchain security applications. Our findings show that the Internet of Things (IoT) lends itself well to novel blockchain applications, as do networks and machine visualization, public key cryptography, web applications, certification schemes and the secure storage of Personally Identifiable Information (PII). This timely systematic review also sheds light on future directions of research, education and practices in the blockchain and cyber security space, such as security of blockchain in IoT, security of blockchain for AI data, and sidechain security,etc

IoT trust and reputation: a survey and taxonomy

IoT is one of the fastest-growing technologies and it is estimated that more than a billion devices would be utilized across the globe by the end of 2030. To maximize the capability of these connected entities, trust and reputation among IoT entities is essential. Several trust management models have been proposed in the IoT environment; however, these schemes have not fully addressed the IoT devices features, such as devices role, device type and its dynamic behavior in a smart environment. As a result, traditional trust and reputation models are insufficient to tackle these characteristics and uncertainty risks while connecting nodes to the network. Whilst continuous study has been carried out and various articles suggest promising solutions in constrained environments, research on trust and reputation is still at its infancy. In this paper, we carry out a comprehensive literature review on state-of-the-art research on the trust and reputation of IoT devices and systems. Specifically, we first propose a new structure, namely a new taxonomy, to organize the trust and reputation models based on the ways trust is managed. The proposed taxonomy comprises of traditional trust management-based systems and artificial intelligence-based systems, and combine both the classes which encourage the existing schemes to adapt these emerging concepts. This collaboration between the conventional mathematical and the advanced ML models result in design schemes that are more robust and efficient. Then we drill down to compare and analyse the methods and applications of these systems based on community-accepted performance metrics, e.g. scalability, delay, cooperativeness and efficiency. Finally, built upon the findings of the analysis, we identify and discuss open research issues and challenges, and further speculate and point out future research directions.Comment: 20 pages, 5 Figures, 3 tables, Journal of cloud computin