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With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy-preserving cryptosystem is necessary. Such a solution relies on chaos encryption algorithms over standard cryptographic methods that possess multistage encryption levels, including high speed, high security, low compute overheads, and procedural power, among other characteristics. In this work, a secure image encryption scheme is proposed using linear feedback shift register (LFSR) and chaos-based quantum chaotic map. The focus of the scheme is mainly dependent on the secret keys from the input of the algorithm. The threat landscape, the statistical test analysis, along critical comparisons with other schemes indicate that the presented algorithm is significantly secure and is resistant to a wide range of different attacks such as differential and statistical attacks. The proposed method has sufficiently higher sensitivity and security when compared to existing encryption algorithms. Several security parameters validated the security of proposed work such as correlation coefficient analyses among the neighboring pixels, entropy, the number of pixels change rate (NPCR), unified average change intensity (UACI), mean square error (MSE), brute force, key sensitivity, and peak signal to noise ratio (PSNR) analyses. The randomness of the ciphers produced by the proposed technique is also passed through NIST-800-22. The results of NIST indicate that the ciphers are highly random and do not produce any type of periodicity or pattern.

A substantial administrative burden is placed on healthcare professionals as they manage and progress through their careers. Identity verification, pre-employment screening and appraisals: the bureaucracy associated with each of these processes takes precious time out of a healthcare professional's day. Time that could have been spent focused on patient care. In the midst of the COVID-19 crisis, it is more important than ever to optimize these professionals' time. This paper presents the synthesis of a design workshop held at the Royal College of Physicians of Edinburgh (RCPE) and subsequent interviews with healthcare professionals. The main research question posed is whether these processes can be re-imagined using digital technologies, specifically Self-Sovereign Identity? A key contribution in the paper is the development of a set of user-led requirements and design principles for identity systems used within healthcare. These are then contrasted with the design principles found in the literature. The results of this study confirm the need and potential of professionalising identity and credential management throughout a healthcare professional's career.

We increasingly live in a world where there is a balance between the rights to privacy and the requirements for consent, and the rights of society to protect itself. Within this world, there is an ever-increasing requirement to protect the identities involved within financial transactions, but this makes things increasingly difficult for law enforcement agencies, especially in terms of financial fraud and money laundering. This paper reviews the state-of-the-art in terms of the methods of privacy that are being used within cryptocurrency transactions, and in the challenges that law enforcement face.

There are several areas of healthcare and well-being that could be enhanced using blockchain technologies. These include device tracking, clinical trials, pharmaceutical tracing, and health insurance. Within device tracking, hospitals can trace their asset within a blockchain infrastructure, including through the complete lifecycle of a device. The information gathered can then be used to improve patient safety and provide after-market analysis to improve efficiency savings. This paper outlines recent work within the areas of pharmaceutical traceability, data sharing, clinical trials, and device tracking. Keywords: Asset Tracking, Blockchain, Drug tracking, Ethereum, Healthcare, Internet of Things, IoT

A blockchain enabled ‘Digital Single Economy” can act as a catalyst for growth and could provide a platform where borderless innovative practices will thrive and create a true collaborative global economy, with shared goals and objectives for the benefit of wider community. A society where digital economy flourishes irrespective of geopolitical ideologies and where a technology like Blockchain holds transformative potential to unite the nations together. The UK currently has strong collaborations around blockchain including with the British Blockchain Association which aims to integrate with the EU on the adoption of Blockchain based methods around a range of application areas. However, at the core of these alliances must be the promotion of technology which link industry, the public sector, and academia, whilst also integrating key stakeholders, such as law enforcement, finance, health care, professional bodies and the legal industry.

In the contemporary digital landscape, security has become a vital element of our existence. The growing volume of sensitive information being stored and transmitted over networks necessitates the implementation of robust security measures. Cryptographic algorithms, which are critical for protecting user data privacy, rely on cryptographic keys to ensure data security. True Random Number Generators (TRNGs) are essential to numerous vital security applications. In this paper, we propose a novel Braided and Hybrid Cross-Coupled Entropy Source (B+HCCES) TRNG module. The proposed B+HCCES TRNG module generates random numbers based on the race hazard and jitter of braided and cross-coupled combinational logic gates. The B+HCCES architecture has been designed using VHDL, and the targeted Field-Programmable Gate Array (FPGA) is the Intel Cyclone V 5CGXFC9D6F27C7 chip. The B+HCCES module operates at a fixed sampling frequency of 300 MHz, generated by an embedded phase-locked loop. The B+HCCES module demonstrates an enhanced throughput of 3.33 times compared to the state-of-the-art, while still maintaining a comparably lightweight architecture. The experimental results demonstrate that the generated random sequence successfully passes the NIST SP800-90B and BSI AIS-31 tests.