Mining digital identity insights: patent analysis using NLP

The field of digital identity innovation has grown significantly over the last 30 years, with over 6000 technology patents registered worldwide. However, many questions remain about who controls and owns our digital identity and intellectual property and, ultimately, where the future of digital identity is heading. To investigate this further, this research mines digital identity patents and explores core themes such as identity, systems, privacy, security, and emerging fields like blockchain, financial transactions, and biometric technologies, utilizing natural language processing (NLP) methods including part-of-speech (POS) tagging, clustering, topic classification, noise reduction, and lemmatisation techniques. Finally, the research employs graph modelling and statistical analysis to discern inherent trends and forecast future developments. The findings significantly contribute to the digital identity landscape, identifying key players, emerging trends, and technological progress. This research serves as a valuable resource for academia and industry stakeholders, aiding in strategic decision-making and investment in emerging technologies and facilitating navigation through the dynamic realm of digital identity technologies

Embedded document security using sticky policies and identity based encryption

Data sharing domains have expanded over several, both trusted and insecure environments. At the same time, the data security boundaries have shrunk from internal network perimeters down to a single identity and a piece of information. Since new EU GDPR regulations, the personally identifiable information sharing requires data governance in favour of a data subject. Existing enterprise grade IRM solutions fail to follow open standards and lack of data sharing frameworks that could efficiently integrate with existing identity management and authentication infrastructures. IRM services that stood against cloud demands often offer a very limited access control functionality allowing an individual to store a document online giving a read or read-write permission to other individual identified by email address. Unfortunately, such limited information sharing controls are often introduced as the only safeguards in large enterprises, healthcare institutions and other organizations that should provide the highest possible personal data protection standards. The IRM suffers from a systems architecture vulnerability where IRM application installed on a semi-trusted client truly only guarantees none or full access enforcement. Since no single authority is contacted to verify each committed change the adversary having an advantage of possessing data-encrypting and key-encrypting keys could change and re-encrypt the amended content despite that read only access has been granted. Finally, the two evaluated IRM products, have either the algorithm security lifecycle (ASL) relatively short to protect the shared data, or the solution construct highly restrained secure key-encrypting key distribution and exposes a symmetric data-encrypting key over the network. Presented here sticky policy with identity-based encryption (SPIBE) solution was designed for secure cloud data sharing. SPIBE challenges are to deliver simple standardized construct that would easily integrate with popular OOXML-like document formats and provide simple access rights enforcement over protected content. It leverages a sticky policy construct using XACML access policy language to express access conditions across different cloud data sharing boundaries. XACML is a cloud-ready standard designed for a global multi-jurisdictional use. Unlike other raw ABAC implementations, the XACML offers a standardised schema and authorisation protocols hence it simplifies interoperability. The IBE is a cryptographic scheme protecting the shared document using an identified policy as an asymmetric key-encrypting a symmetric data-encrypting key. Unlike ciphertext-policy attribute-based access control (CP-ABE), the SPIBE policy contains not only access preferences but global document identifier and unique version identifier what makes each policy uniquely identifiable in relation to the protected document. In IBE scheme the public key-encrypting key is known and could be shared between the parties although the data-encrypting key is never sent over the network. Finally, the SPIBE as a framework should have a potential to protect data in case of new threats where ASL of a used cryptographic primitive is too short, when algorithm should be replaced with a new updated cryptographic primitive. The IBE like a cryptographic protocol could be implemented with different cryptographic primitives. The identity-based encryption over isogenous pairing groups (IBE-IPG) is a post-quantum ready construct that leverages the initial IBE Boneh-Franklin (IBE-BF) approach. Existing IBE implementations could be updated to IBE-IPG without major system amendments. Finally, by applying the one document versioning blockchain-like construct could verify changes authenticity and approve only legitimate document updates, where other IRM solutions fail to operate delivering the one single authority for non-repudiation and authenticity assurance

Blockchain-Based Digitalization of Logistics Processes—Innovation, Applications, Best Practices

Blockchain technology is becoming one of the most powerful future technologies in supporting logistics processes and applications. It has the potential to destroy and reorganize traditional logistics structures. Both researchers and practitioners all over the world continuously report on novel blockchain-based projects, possibilities, and innovative solutions with better logistic service levels and lower costs. The idea of this Special Issue is to provide an overview of the status quo in research and possibilities to effectively implement blockchain-based solutions in business practice. This Special Issue reprint contained well-prepared research reports regarding recent advances in blockchain technology around logistics processes to provide insights into realized maturity

Towards Secure and Intelligent Diagnosis: Deep Learning and Blockchain Technology for Computer-Aided Diagnosis Systems

Cancer is the second leading cause of death across the world after cardiovascular disease. The survival rate of patients with cancerous tissue can significantly decrease due to late-stage diagnosis. Nowadays, advancements of whole slide imaging scanners have resulted in a dramatic increase of patient data in the domain of digital pathology. Large-scale histopathology images need to be analyzed promptly for early cancer detection which is critical for improving patient's survival rate and treatment planning. Advances of medical image processing and deep learning methods have facilitated the extraction and analysis of high-level features from histopathological data that could assist in life-critical diagnosis and reduce the considerable healthcare cost associated with cancer. In clinical trials, due to the complexity and large variance of collected image data, developing computer-aided diagnosis systems to support quantitative medical image analysis is an area of active research. The first goal of this research is to automate the classification and segmentation process of cancerous regions in histopathology images of different cancer tissues by developing models using deep learning-based architectures. In this research, a framework with different modules is proposed, including (1) data pre-processing, (2) data augmentation, (3) feature extraction, and (4) deep learning architectures. Four validation studies were designed to conduct this research. (1) differentiating benign and malignant lesions in breast cancer (2) differentiating between immature leukemic blasts and normal cells in leukemia cancer (3) differentiating benign and malignant regions in lung cancer, and (4) differentiating benign and malignant regions in colorectal cancer. Training machine learning models, disease diagnosis, and treatment often requires collecting patients' medical data. Privacy and trusted authenticity concerns make data owners reluctant to share their personal and medical data. Motivated by the advantages of Blockchain technology in healthcare data sharing frameworks, the focus of the second part of this research is to integrate Blockchain technology in computer-aided diagnosis systems to address the problems of managing access control, authentication, provenance, and confidentiality of sensitive medical data. To do so, a hierarchical identity and attribute-based access control mechanism using smart contract and Ethereum Blockchain is proposed to securely process healthcare data without revealing sensitive information to an unauthorized party leveraging the trustworthiness of transactions in a collaborative healthcare environment. The proposed access control mechanism provides a solution to the challenges associated with centralized access control systems and ensures data transparency and traceability for secure data sharing, and data ownership

A critical literature review of security and privacy in smart home healthcare schemes adopting IoT & blockchain: problems, challenges and solutions

Protecting private data in smart homes, a popular Internet-of-Things (IoT) application, remains a significant data security and privacy challenge due to the large-scale development and distributed nature of IoT networks. Recently, smart healthcare has leveraged smart home systems, thereby compounding security concerns in terms of the confidentiality of sensitive and private data and by extension the privacy of the data owner. However, PoA-based Blockchain DLT has emerged as a promising solution for protecting private data from indiscriminate use and thereby preserving the privacy of individuals residing in IoT-enabled smart homes. This review elicits some concerns, issues, and problems that have hindered the adoption of blockchain and IoT (BCoT) in some domains and suggests requisite solutions using the aging-in-place scenario. Implementation issues with BCoT were examined as well as the combined challenges BCoT can pose when utilised for security gains. The study discusses recent findings, opportunities, and barriers, and provide recommendations that could facilitate the continuous growth of blockchain application in healthcare. Lastly, the study then explored the potential of using a PoA-based permission blockchain with an applicable consent-based privacy model for decision-making in the information disclosure process, including the use of publisher-subscriber contracts for fine-grained access control to ensure secure data processing and sharing, as well as ethical trust in personal information disclosure, as a solution direction. The proposed authorisation framework could guarantee data ownership, conditional access management, scalable and tamper-proof data storage, and a more resilient system against threat models such as interception and insider attacks

Cybersecurity and the Digital Health: An Investigation on the State of the Art and the Position of the Actors

Cybercrime is increasingly exposing the health domain to growing risk. The push towards a strong connection of citizens to health services, through digitalization, has undisputed advantages. Digital health allows remote care, the use of medical devices with a high mechatronic and IT content with strong automation, and a large interconnection of hospital networks with an increasingly effective exchange of data. However, all this requires a great cybersecurity commitment—a commitment that must start with scholars in research and then reach the stakeholders. New devices and technological solutions are increasingly breaking into healthcare, and are able to change the processes of interaction in the health domain. This requires cybersecurity to become a vital part of patient safety through changes in human behaviour, technology, and processes, as part of a complete solution. All professionals involved in cybersecurity in the health domain were invited to contribute with their experiences. This book contains contributions from various experts and different fields. Aspects of cybersecurity in healthcare relating to technological advance and emerging risks were addressed. The new boundaries of this field and the impact of COVID-19 on some sectors, such as mhealth, have also been addressed. We dedicate the book to all those with different roles involved in cybersecurity in the health domain

Big Data and Large-scale Data Analytics: Efficiency of Sustainable Scalability and Security of Centralized Clouds and Edge Deployment Architectures

One of the significant shifts of the next-generation computing technologies will certainly be in the development of Big Data (BD) deployment architectures. Apache Hadoop, the BD landmark, evolved as a widely deployed BD operating system. Its new features include federation structure and many associated frameworks, which provide Hadoop 3.x with the maturity to serve different markets. This dissertation addresses two leading issues involved in exploiting BD and large-scale data analytics realm using the Hadoop platform. Namely, (i)Scalability that directly affects the system performance and overall throughput using portable Docker containers. (ii) Security that spread the adoption of data protection practices among practitioners using access controls. An Enhanced Mapreduce Environment (EME), OPportunistic and Elastic Resource Allocation (OPERA) scheduler, BD Federation Access Broker (BDFAB), and a Secure Intelligent Transportation System (SITS) of multi-tiers architecture for data streaming to the cloud computing are the main contribution of this thesis study