An Efficient Collaboration and Incentive Mechanism for Internet-of-Vehicles (IoVs) with Secured Information Exchange Based on Blockchains

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordWith the rapid development of Internet-of-Things (IoT), mobile crowdsensing, i.e., outsourcing sensing tasks to mobile devices or vehicles, has been proposed to address the problem of data collection in the scenarios such as smart city. Despite its benefits for a wide range of applications, mobile crowdsensing lacks an efficient incentive mechanism, restricting the development of IoT applications, especially for Internet-ofVehicles (IoV) – a typical example of IoT applications; this is because vehicles are usually reluctant to participate these sensing tasks. Moreover, in practice some sensing tasks may arrive suddenly (called an emergent task) in the IoV environment, but the resources of a single vehicle may be insufficient to handle, and thus multi-vehicles collaboration is required. In this case, the incentive mechanisms for the participation of multiple vehicles and the task scheduling for their collaborations are collectively needed. To address this important problem, we firstly propose a new model for the scenario of two vehicles collaboration, considering the situation of emergent appearance of a task. In this model, for a general sensing task, we propose a bidding mechanism to better encourage vehicles to contribute their resources, and the tasks for those vehicles are scheduled accordingly. Secondly, for an emergent task, a novel time-window based method is devised to manage the tasks among vehicles and to incent the vehicles to participate. Finally, we develop a blockchain framework to achieve the secured information exchange through smart contract for the proposed models in IoV.National Key Research and Development Program of ChinaNational Natural Science Foundation of China (NSFC)Purple Mountain Laboratory: Networking, Communications and SecurityAcademician Expert Workstation of Bitvalue Technology (Hunan) Company Limite

From Requirements to Operation: Components for Risk Assessment in a Pervasive System of Systems

Framing Internet of Things (IoT) applications as a System of Systems (SoS) can help us make sense of complexity associated with interoperability and emergence. However, assess- ing the risk of SoSs is a challenge due to the independence of component systems, and their differing degrees of control and emergence. This paper presents three components for SoS risk assessment that integrate with existing risk assessment approaches: Human System Integration (HSI), Interoperability identification and analysis, and Emergent behaviour evaluation and control measures. We demonstrate the application of these components by assessing a pervasive SoS: a SmartPowerchair

A survey of IoT security based on a layered architecture of sensing and data analysis

The Internet of Things (IoT) is leading today’s digital transformation. Relying on a combination of technologies, protocols, and devices such as wireless sensors and newly developed wearable and implanted sensors, IoT is changing every aspect of daily life, especially recent applications in digital healthcare. IoT incorporates various kinds of hardware, communication protocols, and services. This IoT diversity can be viewed as a double-edged sword that provides comfort to users but can lead also to a large number of security threats and attacks. In this survey paper, a new compacted and optimized architecture for IoT is proposed based on five layers. Likewise, we propose a new classification of security threats and attacks based on new IoT architecture. The IoT architecture involves a physical perception layer, a network and protocol layer, a transport layer, an application layer, and a data and cloud services layer. First, the physical sensing layer incorporates the basic hardware used by IoT. Second, we highlight the various network and protocol technologies employed by IoT, and review the security threats and solutions. Transport protocols are exhibited and the security threats against them are discussed while providing common solutions. Then, the application layer involves application protocols and lightweight encryption algorithms for IoT. Finally, in the data and cloud services layer, the main important security features of IoT cloud platforms are addressed, involving confidentiality, integrity, authorization, authentication, and encryption protocols. The paper is concluded by presenting the open research issues and future directions towards securing IoT, including the lack of standardized lightweight encryption algorithms, the use of machine-learning algorithms to enhance security and the related challenges, the use of Blockchain to address security challenges in IoT, and the implications of IoT deployment in 5G and beyond

GeoCoin:supporting ideation and collaborative design with location-based smart contracts

Design and HCI researchers are increasingly working with complex digital infrastructures, such as cryptocurrencies, distributed ledgers and smart contracts. These technologies will have a profound impact on digital systems and their audiences. However, given their emergent nature and technical complexity, involving non-specialists in the design of applications that employ these technologies is challenging. In this paper, we discuss these challenges and present GeoCoin, a location-based platform for embodied learning and speculative ideating with smart contracts. In collaborative workshops with GeoCoin, participants engaged with location-based smart contracts, using the platform to explore digital `debit' and `credit' zones in the city. These exercises led to the design of diverse distributed-ledger applications, for time-limited financial unions, participatory budgeting, and humanitarian aid. These results contribute to the HCI community by demonstrating how an experiential prototype can support understanding of the complexities behind new digital infrastructures and facilitate participant engagement in ideation and design processes

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

Hands-on learning modules for upskilling in industry 4.0 technologies

The Industry 4.0 (I4.0) advent is re-shaping the way systems and processes operate by considering Cyber- Physical Systems combined with a plethora of emergent Information and Communication Technologies (ICT), e.g., Internet of Things (IoT), Artificial Intelligence, Cloud Computing and Intelligent Robotics. However, the emergence of such disruptive technologies strongly establishes a demand for upskilling and requalification of active professionals and young undergraduate students. This means that the wide adoption of the 14.0 systems and related tech-nologies is dependent on the efficient implementation of lifelong learning and training initiatives that address these challenges. Having this in mind, this paper describes the implementation of a series of short learning modules and hackathons that relies on a strong hands-on practical experimentation, regarding the upskilling in emergent ICT technologies, particularly focusing on IoT, mobile robotics and Multi-agent Systems. The preliminary efforts contributed to qualify undergraduate students and active professionals in disruptive ICT, with the attendees' feedback illustrating the importance of these kind of short and hands-on learning modules to address towards the continuous demands associated to the diaital transformation.info:eu-repo/semantics/publishedVersio

Securing intellectual capital:an exploratory study in Australian universities

Purpose – To investigate the links between IC and the protection of data, information and knowledge in universities, as organizations with unique knowledge-related foci and challenges.Design/methodology/approach – We gathered insights from existing IC-related research publications to delineate key foundational aspects of IC, identify and propose links to traditional information security that impact the protection of IC. We conducted interviews with key stakeholders in Australian universities in order to validate these links.Findings – Our investigation revealed two kinds of embeddedness characterizing the organizational fabric of universities: (1) vertical and (2) horizontal, with an emphasis on the connection between these and IC-related knowledge protection within these institutions.Research implications – There is a need to acknowledge the different roles played by actors within the university, and the relevance of information security to IC-related preservation.Practical implications – Framing information security as an IC-related issue can help IT security managers communicate the need for knowledge security with executives in higher education, and secure funding to preserve and secure such IC-related knowledge, once its value is recognized.Originality/value – This is one of the first studies to explore the connections between data and information security and the three core components of IC’s knowledge security in the university context

Security and Privacy Issues of Big Data

This chapter revises the most important aspects in how computing infrastructures should be configured and intelligently managed to fulfill the most notably security aspects required by Big Data applications. One of them is privacy. It is a pertinent aspect to be addressed because users share more and more personal data and content through their devices and computers to social networks and public clouds. So, a secure framework to social networks is a very hot topic research. This last topic is addressed in one of the two sections of the current chapter with case studies. In addition, the traditional mechanisms to support security such as firewalls and demilitarized zones are not suitable to be applied in computing systems to support Big Data. SDN is an emergent management solution that could become a convenient mechanism to implement security in Big Data systems, as we show through a second case study at the end of the chapter. This also discusses current relevant work and identifies open issues.Comment: In book Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence, IGI Global, 201