Security Management Framework for the Internet of Things

The increase in the design and development of wireless communication technologies offers multiple opportunities for the management and control of cyber-physical systems with connections between smart and autonomous devices, which provide the delivery of simplified data through the use of cloud computing. Given this relationship with the Internet of Things (IoT), it established the concept of pervasive computing that allows any object to communicate with services, sensors, people, and objects without human intervention. However, the rapid growth of connectivity with smart applications through autonomous systems connected to the internet has allowed the exposure of numerous vulnerabilities in IoT systems by malicious users. This dissertation developed a novel ontology-based cybersecurity framework to improve security in IoT systems using an ontological analysis to adapt appropriate security services addressed to threats. The composition of this proposal explores two approaches: (1) design time, which offers a dynamic method to build security services through the application of a methodology directed to models considering existing business processes; and (2) execution time, which involves monitoring the IoT environment, classifying vulnerabilities and threats, and acting in the environment, ensuring the correct adaptation of existing services. The validation approach was used to demonstrate the feasibility of implementing the proposed cybersecurity framework. It implies the evaluation of the ontology to offer a qualitative evaluation based on the analysis of several criteria and also a proof of concept implemented and tested using specific industrial scenarios. This dissertation has been verified by adopting a methodology that follows the acceptance in the research community through technical validation in the application of the concept in an industrial setting.O aumento no projeto e desenvolvimento de tecnologias de comunicação sem fio oferece múltiplas oportunidades para a gestão e controle de sistemas ciber-físicos com conexões entre dispositivos inteligentes e autônomos, os quais proporcionam a entrega de dados simplificados através do uso da computação em nuvem. Diante dessa relação com a Internet das Coisas (IoT) estabeleceu-se o conceito de computação pervasiva que permite que qualquer objeto possa comunicar com os serviços, sensores, pessoas e objetos sem intervenção humana. Entretanto, o rápido crescimento da conectividade com as aplicações inteligentes através de sistemas autônomos conectados com a internet permitiu a exposição de inúmeras vulnerabilidades dos sistemas IoT para usuários maliciosos. Esta dissertação desenvolveu um novo framework de cibersegurança baseada em ontologia para melhorar a segurança em sistemas IoT usando uma análise ontológica para a adaptação de serviços de segurança apropriados endereçados para as ameaças. A composição dessa proposta explora duas abordagens: (1) tempo de projeto, o qual oferece um método dinâmico para construir serviços de segurança através da aplicação de uma metodologia dirigida a modelos, considerando processos empresariais existentes; e (2) tempo de execução, o qual envolve o monitoramento do ambiente IoT, a classificação de vulnerabilidades e ameaças, e a atuação no ambiente garantindo a correta adaptação dos serviços existentes. Duas abordagens de validação foram utilizadas para demonstrar a viabilidade da implementação do framework de cibersegurança proposto. Isto implica na avaliação da ontologia para oferecer uma avaliação qualitativa baseada na análise de diversos critérios e também uma prova de conceito implementada e testada usando cenários específicos. Esta dissertação foi validada adotando uma metodologia que segue a validação na comunidade científica através da validação técnica na aplicação do nosso conceito em um cenário industrial

Security, privacy and safety evaluation of dynamic and static fleets of drones

Inter-connected objects, either via public or private networks are the near future of modern societies. Such inter-connected objects are referred to as Internet-of-Things (IoT) and/or Cyber-Physical Systems (CPS). One example of such a system is based on Unmanned Aerial Vehicles (UAVs). The fleet of such vehicles are prophesied to take on multiple roles involving mundane to high-sensitive, such as, prompt pizza or shopping deliveries to your homes to battlefield deployment for reconnaissance and combat missions. Drones, as we refer to UAVs in this paper, either can operate individually (solo missions) or part of a fleet (group missions), with and without constant connection with the base station. The base station acts as the command centre to manage the activities of the drones. However, an independent, localised and effective fleet control is required, potentially based on swarm intelligence, for the reasons: 1) increase in the number of drone fleets, 2) number of drones in a fleet might be multiple of tens, 3) time-criticality in making decisions by such fleets in the wild, 4) potential communication congestions/lag, and 5) in some cases working in challenging terrains that hinders or mandates-limited communication with control centre (i.e., operations spanning long period of times or military usage of such fleets in enemy territory). This self-ware, mission-focused and independent fleet of drones that potential utilises swarm intelligence for a) air-traffic and/or flight control management, b) obstacle avoidance, c) self-preservation while maintaining the mission criteria, d) collaboration with other fleets in the wild (autonomously) and e) assuring the security, privacy and safety of physical (drones itself) and virtual (data, software) assets. In this paper, we investigate the challenges faced by fleet of drones and propose a potential course of action on how to overcome them.Comment: 12 Pages, 7 Figures, Conference, The 36th IEEE/AIAA Digital Avionics Systems Conference (DASC'17

Beyond the Hype: On Using Blockchains in Trust Management for Authentication

Trust Management (TM) systems for authentication are vital to the security of online interactions, which are ubiquitous in our everyday lives. Various systems, like the Web PKI (X.509) and PGP's Web of Trust are used to manage trust in this setting. In recent years, blockchain technology has been introduced as a panacea to our security problems, including that of authentication, without sufficient reasoning, as to its merits.In this work, we investigate the merits of using open distributed ledgers (ODLs), such as the one implemented by blockchain technology, for securing TM systems for authentication. We formally model such systems, and explore how blockchain can help mitigate attacks against them. After formal argumentation, we conclude that in the context of Trust Management for authentication, blockchain technology, and ODLs in general, can offer considerable advantages compared to previous approaches. Our analysis is, to the best of our knowledge, the first to formally model and argue about the security of TM systems for authentication, based on blockchain technology. To achieve this result, we first provide an abstract model for TM systems for authentication. Then, we show how this model can be conceptually encoded in a blockchain, by expressing it as a series of state transitions. As a next step, we examine five prevalent attacks on TM systems, and provide evidence that blockchain-based solutions can be beneficial to the security of such systems, by mitigating, or completely negating such attacks.Comment: A version of this paper was published in IEEE Trustcom. http://ieeexplore.ieee.org/document/8029486

Context-aware Security for Vehicles and Fleets: A Survey

Vehicles are becoming increasingly intelligent and connected. Interfaces for communication with the vehicle, such as WiFi and 5G, enable seamless integration into the user’s life, but also cyber attacks on the vehicle. Therefore, research is working on in-vehicle countermeasures such as authentication, access controls, or intrusion detection. Recently, legal regulations have also become effective that require automobile manufacturers to set up a monitoring system for fleet-wide security analysis. The growing amount of software, networking, and the automation of driving create new challenges for security. Context-awareness, situational understanding, adaptive security, and threat intelligence are necessary to cope with these ever-increasing risks. In-vehicle security should be adaptive to secure the car in an infinite number of (driving) situations. For fleet-wide analysis and alert triage, knowledge and understanding of the circumstances are required. Context-awareness, nonetheless, has been sparsely considered in the field of vehicle security. This work aims to be a precursor to context-aware, adaptive and intelligent security for vehicles and fleets. To this end, we provide a comprehensive literature review that analyzes the vehicular as well as related domains. Our survey is mainly characterized by the detailed analysis of the context information that is relevant for vehicle security in the future

Cyber security investigation for Raspberry Pi devices

Big Data on Cloud application is growing rapidly. When the cloud is attacked, the investigation relies on digital forensics evidence. This paper proposed the data collection via Raspberry Pi devices, in a healthcare situation. The significance of this work is that could be expanded into a digital device array that takes big data security issues into account. There are many potential impacts in health area. The field of Digital Forensics Science has been tagged as a reactive science by some who believe research and study in the field often arise as a result of the need to respond to event which brought about the needs for investigation; this work was carried as a proactive research that will add knowledge to the field of Digital Forensic Science. The Raspberry Pi is a cost-effective, pocket sized computer that has gained global recognition since its development in 2008; with the wide spread usage of the device for different computing purposes. Raspberry Pi can potentially be a cyber security device, which can relate with forensics investigation in the near future. This work has used a systematic approach to study the structure and operation of the device and has established security issues that the widespread usage of the device can pose, such as health or smart city. Furthermore, its evidential information applied in security will be useful in the event that the device becomes a subject of digital forensic investigation in the foreseeable future. In healthcare system, PII (personal identifiable information) is a very important issue. When Raspberry Pi plays a processor role, its security is vital; consequently, digital forensics investigation on the Raspberry Pies becomes necessary

A Comparison of Cybersecurity Risk Analysis Tools

This paper presents the ongoing work of a decision aiding software intended to support cyber risk and cyber threats analysis of an information and communications technology infrastructure. The work focuses on the evaluation of the different tools in relation to risk assessment and decision making to incorporate some of the characteristics, metrics and strategies that will help cybersecurity risk analysis, decision-making, prevention measures and risk strategies for infrastructure and the protection of an organization's information assets

Pricing cyber-insurance for systems via maturity models

Pricing insurance for risks associated with information technology systems presents a complex modelling challenge, combining the disciplines of operations management, security, and economics. This work proposes a socioeconomic model for cyber-insurance decisions compromised of entity relationship diagrams, security maturity models, and economic models, addressing a long-standing research challenge of capturing organizational structure in the design and pricing of cyber-insurance policies. Insurance pricing is usually informed by the long experience insurance companies have of the magnitude and frequency of losses that arise in organizations based on their size, industry sector, and location. Consequently, their calculations of premia will start from a baseline determined by these considerations. A unique challenge of cyber-insurance is that data history is limited and not necessarily informative of future loss risk meaning that established actuarial methodology for other lines of insurance may not be the optimal pricing strategy. The model proposed in this paper provides a vehicle for agreement between practitioners in the cyber-insurance ecosystem on cyber-security risks and allows for the users to choose their desired level of abstraction in the description of a system.Comment: 31 pages, 12 figures, 11 table