IDMoB: IoT Data Marketplace on Blockchain

Today, Internet of Things (IoT) devices are the powerhouse of data generation with their ever-increasing numbers and widespread penetration. Similarly, artificial intelligence (AI) and machine learning (ML) solutions are getting integrated to all kinds of services, making products significantly more "smarter". The centerpiece of these technologies is "data". IoT device vendors should be able keep up with the increased throughput and come up with new business models. On the other hand, AI/ML solutions will produce better results if training data is diverse and plentiful. In this paper, we propose a blockchain-based, decentralized and trustless data marketplace where IoT device vendors and AI/ML solution providers may interact and collaborate. By facilitating a transparent data exchange platform, access to consented data will be democratized and the variety of services targeting end-users will increase. Proposed data marketplace is implemented as a smart contract on Ethereum blockchain and Swarm is used as the distributed storage platform.Comment: Presented at Crypto Valley Conference on Blockchain Technology (CVCBT 2018), 20-22 June 2018 - published version may diffe

Applications of Blockchain Technology to Higher Education Arena: A Bibliometric Analysis

Reis-Marques, C., Figueiredo, R., & Neto, M. D. C. (2021). Applications of Blockchain Technology to Higher Education Arena: A Bibliometric Analysis. European Journal of Investigation in Health, Psychology and Education, 11(4), 1406-1421. https://doi.org/10.3390/ejihpe11040101 ---------------------------------------------- This work is financed by national funds through FCT—Fundação para a Ciência e a Tecnologia, I. P., under the project “UIDB/04630/2020”.Research related to blockchain is rapidly gaining importance in the higher education. This opportunity collaborates with a proposal for a review of papers on the main blockchain topic. The bibliometric analysis included 61 peer-reviewed articles published in the Scopus database during the period of 2016 to 2021. This paper offers the identification of gaps in the literature enabling studies on the subject in higher education. The article identifies the main applications of blockchain technology in higher education around the world, as well as suggests future investigations. For further scientific investigation, we propose the operationalization of each of the researched approaches, especially combining the blockchain relationship, artificial intelligence, digital innovation, digital maturity, and customer experience in higher education.publishersversionpublishe

Securing the Edges of IoT Networks: a Scalable SIP DDoS Defense Framework with VNF, SDN, and Blockchain

An unintended consequence of the global deployment of IoT devices is that they provide a fertile breeding ground for IoT botnets. An adversary can take advantage of an IoT botnet to launch DDoS attacks against telecommunication services. Due to the magnitude of such an attack, legacy security systems are not able to provide adequate protection. The impact ranges from loss of revenue for businesses to endangering public safety. This risk has prompted academia, government, and industry to reevaluate the existing de- fence model. The current model relies on point solutions and the assumption that adversaries and their attacks are readily identifiable. But adversaries have challenged this assumption, building a botnet from thousands of hijacked IoT devices to launch DDoS attacks. With bot- net DDoS attacks there are no clear boundary where the attacks originate and what defensive measures to use. The research question is: in what ways programmable networks could defend against Session Initiation Protocol (SIP) Distributed Denial-of-Service (DDoS) flooding attacks from IoT botnets? My significant and original contribution to the knowledge is a scalable and collaborative defence framework that secures the edges of IoT networks with Virtual Network Function (VNF), Software-Defined Networking (SDN), and Blockchain technology to prevent, detect, and mitigate SIP DDoS flooding attacks from IoT botnets. Successful experiments were performed using VNF, SDN, and Blockchain. Three kinds of SIP attacks (scan, brute force, and DDoS) were launched against a VNF running on a virtual switch and each was successfully detected and mitigated. The SDN controller gathers threat intelligence from the switch where the attacks originate and installs them as packet filtering rules on all switches in the organisation. With the switches synchronised, the same botnet outbreak is prevented from attacking other parts of the organisation. A distributed application scales this framework further by writing the threat intelligence to a smart contract on the Ethereum Blockchain so that it is available for external organisations. The receiving organisation retrieves the threat intelligence from the smart contract and installs them as packet filtering rules on their switches. In this collaborative framework, attack detection/mitigation efforts by one organisation can be leveraged as attack prevention efforts by other organisations in the community

Cyber Security

This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

Cyber Security

This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Digital Forensics Investigation Frameworks for Cloud Computing and Internet of Things

Rapid growth in Cloud computing and Internet of Things (IoT) introduces new vulnerabilities that can be exploited to mount cyber-attacks. Digital forensics investigation is commonly used to find the culprit and help expose the vulnerabilities. Traditional digital forensics tools and methods are unsuitable for use in these technologies. Therefore, new digital forensics investigation frameworks and methodologies are required. This research develops frameworks and methods for digital forensics investigations in cloud and IoT platforms