DASS-CARE 2.0: Blockchain-Based Healthcare Framework for Collaborative Diagnosis in CIoMT Ecosystem

Due to current Covid-19 pandemic, several countries enforce lock-down to prevent pandemic outspread. Hence, the mode of delivery of health services shall change as physical visits are not allowed. As such, the need of tele-medicine service and remote diagnosis have become a necessity. To provide reliable, safe, secure, and sustainable tele-medicine consultancy services, the supporting IT infrastructure need to be transformed. Therefore, it is necessary to use new generation of information technologies such as loT, Blockchain, and cloud computing to transform the traditional medical systems to smart healthcare systems. In this paper, we propose a proof of concept (PoC) of an ameliorated version of our DASS-CARE framework that supports decentralized, accessible, scalable, and secure access to healthcare services based on Internet of Medical things (IoMT) and Artificial Intelligence (AI). In this paper, we propose DASS-CARE 2.0 that offers more medical services including: (a) the real time health monitoring, (b) the collaborative and secure access to medical records, (c) the storage of medical history diagnosis and prescriptions, and (d)the patient\u27s discharge and bills\u27 payments. The paper concludes with future changes to the framework that can furnish further services

Statistical analysis of factors associated with recent traffic accidents dataset: a practical study

In this paper, we propose a logistic model to fit accidents dataset of 10,000 road crash incidents for the Emirate of Abu Dhabi published in 2020. After cleaning up the dataset, we use descriptive and inferential statistical tools to study the attributes of each variable. Then, we identify the main independent variables that can be incorporated in a general logistic regression model which also includes the interactions between them. Our analysis using the significance level of (alpha = 0.05) found that there is a reduced logistic regression model that can fit the data in which the ‘location of accident’ can be represented using ‘type of accident’ and the ‘age’ of people involved in the accidents. Moreover, the results show that the interaction terms are not significant to be included in the model. Furthermore, the study shows that the odds for accidents by young age group (less than 40 years old) in external streets is 27% higher than the odds for internal streets, and that the odds for sequential type accidents in external streets is 13% higher than the odds for internal streets

An efficient design of 45-nm CMOS low-noise charge sensitive amplifier for wireless receivers

Amplifiers are widely used in signal receiving circuits, such as antennas, medical imaging, wireless devices and many other applications. However, one of the most challenging problems when building an amplifier circuit is the noise, since it affects the quality of the intended received signal in most wireless applications. Therefore, a preamplifier is usually placed close to the main sensor to reduce the effects of interferences and to amplify the received signal without degrading the signal-to-noise ratio. Although different designs have been optimized and tested in the literature, all of them are using larger than 100 nm technologies which have led to a modest performance in terms of equivalent noise charge (ENC), gain, power consumption, and response time. In contrast, we consider in this paper a new amplifier design technology trend and move towards sub 100 nm to enhance its performance. In this work, we use a pre-well-known design of a preamplifier circuit and rebuild it using 45 nm CMOS technology, which is made for the first time in such circuits. Performance evaluation shows that our proposed scaling technology, compared with other scaling technology, extremely reduces ENC of the circuit by more than 95%. The noise spectral density and time resolution are also reduced by 25% and 95% respectively. In addition, power consumption is decreased due to the reduced channel length by 90%. As a result, all of those enhancements make our proposed circuit more suitable for medical and wireless devices

Probabilistic analysis of security attacks in cloud environment using hidden Markov models

© 2020 John Wiley & Sons, Ltd. The rapidly growing cloud computing paradigm provides a cost-effective platform for storing, sharing, and delivering data and computation through internet connectivity. However, one of the biggest barriers for massive cloud adoption is the growing cybersecurity threats/risks that influence its confidence and feasibility. Existing threat models for clouds may not be able to capture complex attacks. For example, an attacker may combine multiple security vulnerabilities into an intelligent, persistent, and sequence of attack behaviors that will continuously act to compromise the target on clouds. Hence, new models for detection of complex and diversified network attacks are needed. In this article, we introduce an effective threat modeling approach that has the ability to predict and detect the probability of occurrence of various security threats and attacks within the cloud environment using hidden Markov models (HMMs). The HMM is a powerful statistical analysis technique and is used to create a probability matrix based on the sensitivity of the data and possible system components that can be attacked. In addition, the HMM is used to provide supplemental information to discover a trend attack pattern from the implicit (or hidden) raw data. The proposed model is trained to identify anomalous sequences or threats so that accurate and up-to-date information on risk exposure of cloud-hosted services are properly detected. The proposed model would act as an underlying framework and a guiding tool for cloud systems security experts and administrators to secure processes and services over the cloud. The performance evaluation shows the effectiveness of the proposed approach to find attack probability and the number of correctly detected attacks in the presence of multiple attack scenarios

A trust-based authentication framework for security of WPAN using network slicing

New technologies bring along many challenges including security and privacy. Wireless personal area networks (WPANs) are characterized by limited energy resources and computing power that calls for lightweight security mechanisms in these networks as a mandatory requirement. In this paper, a lightweight trust-based framework for node authentication in WPAN is proposed. Our main objective is to minimise the effort in distinguishing valid requests of trustworthy nodes from invalid requests of malicious nodes that can result in network compromises. We achieve this through network slicing which divides the network into virtually primary and secondary networks. The proposed framework has three-fold benefits. First, it authenticates nodes’ requests based on a novel method of trust value calculation. Second, the framework maintains energy efficiency while authenticating nodes’ requests to access WPAN resources. Finally, the framework provides a solution for biasing problem that can arise due to unexpected behaviour of malicious users in WPANs. The framework efficacy is illustrated on a case study to shown how it can accurately capture trust relations among nodes while preventing malicious behavior

A Lightweight and Efficient Digital Image Encryption Using Hybrid Chaotic Systems for Wireless Network Applications

Due to limited processing capabilities and other constraints of most wireless networks, many existing security algorithms do not consider the network efficiency. This is because most of these security solutions exhibit intolerable overhead and consider only securing scalar data, which are not suitable for other data types such as digital images, hence affecting the provided security level and network performance. Thus, in this paper, we propose a lightweight and efficient security scheme based on chaotic algorithms to efficiently encrypt digital images. Our proposed algorithm handles digital images in two phases: Firstly, digital images are split into blocks and compressed by processing them in frequency domain instead of Red-Green-Blue (RGB) domain. The ultimate goal is to reduce their sizes to speed up the encryption process and to break the correlation among image pixel values. Secondly, 2D Logistic chaotic map is deployed in key generation, permutation, and substitution stages for image pixel shuffling and transposition. In addition, 2D Henon chaotic map is deployed to change the pixel values in the diffusion stage in order to enhance the required level of security and resist various security attacks. Security performance analysis based on standard test images shows that our proposed scheme overcomes the performance of other existing techniques

A Secure Cluster-Based Multipath Routing Protocol for WMSNs

The new characteristics of Wireless Multimedia Sensor Network (WMSN) and its design issues brought by handling different traffic classes of multimedia content (video streams, audio, and still images) as well as scalar data over the network, make the proposed routing protocols for typical WSNs not directly applicable for WMSNs. Handling real-time multimedia data requires both energy efficiency and QoS assurance in order to ensure efficient utility of different capabilities of sensor resources and correct delivery of collected information. In this paper, we propose a Secure Cluster-based Multipath Routing protocol for WMSNs, SCMR, to satisfy the requirements of delivering different data types and support high data rate multimedia traffic. SCMR exploits the hierarchical structure of powerful cluster heads and the optimized multiple paths to support timeliness and reliable high data rate multimedia communication with minimum energy dissipation. Also, we present a light-weight distributed security mechanism of key management in order to secure the communication between sensor nodes and protect the network against different types of attacks. Performance evaluation from simulation results demonstrates a significant performance improvement comparing with existing protocols (which do not even provide any kind of security feature) in terms of average end-to-end delay, network throughput, packet delivery ratio, and energy consumption