Identity resilience in the digital health ecosystem: A key recovery-enabled framework.

In response to the evolving landscape of digital technology in healthcare, this study addresses the multifaceted challenges pertaining to identity and data privacy. The core of our key recovery-enabled framework revolves around the establishment of a robust identity verification system, leveraging the World Wide Web Consortium(W3C) standard for verifiable credentials(VC) and a test blockchain network. The approach leverages cryptographic proofs embedded within credentials issued by various entities to securely validate the legitimacy of identities.

A Systematic Review of Data-Driven Attack Detection Trends in IoT.

The Internet of Things is perhaps a concept that the world cannot be imagined without today, having become intertwined in our everyday lives in the domestic, corporate and industrial spheres. However, irrespective of the convenience, ease and connectivity provided by the Internet of Things, the security issues and attacks faced by this technological framework are equally alarming and undeniable. In order to address these various security issues, researchers race against evolving technology, trends and attacker expertise.

Cloud Enterprise Dynamic Risk Assessment (CEDRA): a dynamic risk assessment using dynamic Bayesian networks for cloud environment.

Cloud computing adoption has been increasing rapidly amid COVID-19 as organisations accelerate the implementation of their digital strategies. Most models adopt traditional dynamic risk assessment, which does not adequately quantify or monetise risks to enable business-appropriate decision-making. In view of this challenge, a new model is proposed in this paper for assignment of monetary losses terms to the consequences nodes, thereby enabling experts to understand better the financial risks of any consequence.

Ransomware detection using deep learning based unsupervised feature extraction and a cost sensitive Pareto Ensemble classifier.

Ransomware attacks pose a serious threat to Internet resources due to their far-reaching effects. It's Zero-day variants are even more hazardous, as less is known about them. In this regard, when used for ransomware attack detection, conventional machine learning approaches may become data-dependent, insensitive to error cost, and thus may not tackle zero-day ransomware attacks.

Privacy-preserving clinical decision support system using Gaussian kernel-based classification.

A clinical decision support system forms a critical capability to link health observations with health knowledge to influence choices by clinicians for improved healthcare. Recent trends toward remote outsourcing can be exploited to provide efficient and accurate clinical decision support in healthcare. In this scenario, clinicians can use the health knowledge located in remote servers via the Internet to diagnose their patients.

Label-free slot-waveguide biosensor for the detection of DNA hybridization.

A finite element method based on the full-vectorial H-field formulation has been employed to achieve the maximum field penetration in the sensing medium of the slot-waveguide-based ring resonator biosensor. The use of nanometer scale guiding structure where optical mode is confined in a low-index region permits a very compact sensor with high optical intensity in the region, which makes it possible to detect minimum refractive index change, and offers higher sensitivities. We analyze the change in effective refractive index of mode, sensitivity, and power confinement of the proposed slot-waveguide-based ring resonator biosensor for the detection of DNA hybridization.

Securing electronic health records with novel mobile encryption schemes.

Mobile devices have penetrated the healthcare sector due to their increased functionality, low cost, high reliability and easy-to-use nature. However, in healthcare applications the privacy and security of the transmitted information must be preserved. Therefore applications require a concrete security framework based on long-term security keys, such as the security key that can be found in a mobile Subscriber Identity Module (SIM).

Rigorous comparison of parabolically tapered and conventional multimode-interference-based 3-dB power splitters in InGaAsP/InP waveguides.

Design issues such as optical transmission, interference mechanisms, the splitting ratio, the polarization dependence, and the fabrication tolerances of a compact parabolically tapered multimode-interference (MMI)-based 3-dB power splitter on an InP-based deeply etched ridge waveguide, by use of the finite-element-based beam-propagation method, are presented. The benefits and drawbacks of the use of the tapered structure, in comparison with an untapered MMI-based 3-dB splitter, have also been investigated.