Fuzzy-GRA trust model for cloud risk management

Cloud computing is not adequately secure due to the currently used traditional trust methods such as global trust model and local trust model. These are prone to security vulnerabilities. This paper introduces a trust model based on the fuzzy mathematics and gray relational theory. Fuzzy mathematics and gray relational analysis (Fuzzy-GRA) aims to improve the poor dynamic adaptability of cloud computing. Fuzzy-GRA platform is used to test and validate the behavior of the model. Furthermore, our proposed model is compared to other known models. Based on the experimental results, we prove that our model has the edge over other existing models

Privacy preserving medium access control protocol for wireless body area sensor networks

Wireless Sensor Networks (WSNs) play vital role in several fields and particularly add more in the health domain. Several applications in the health domain utilize the WSNs to diagnose the disease and cure the patients. However, there is threat and risk involved for exploiting the privacy of the patient and deteriorating the performance of operating tools and systems. There are few existing approaches handling the attacks to maintain the privacy issue of wireless body area sensor networks (WBASNs). Most of the threats are expected on the Medium Access Control (MAC) sub-layer that affect the performance of WBANs. In this paper, we introduce privacy preserving Medium Access Control (PP-MAC) to detect the selfish attack. The algorithm aims to save energy because selfish attack leads to additional energy consumption. In this type of attack, the illegitimate node has edge over the legitimate nodes at the MAC sub-layer. As a result, the illegitimate node consumes the resources negatively. The effectiveness of our proposed algorithm is tested by using OMNET++ and compared with other known existing MAC protocols designed for WBANs. Based on the simulation results, our proposed protocol performs better than other protocols in detecting the rate of selfish attacks, saving the energy, and performance throughput

Бинарные концепты "любовь / love" и "ненависть / hате (hatred)" в английском и русском песенных дискурсах: сопоставительный аспект: автореферат диссертации на соискание ученой степени кандидата филологических наук: специальность 10.02.20 - сравнительно-историческое, типологическое и сопоставительное языкознание

Recently, an increasing number of cyber-attacks in the medical field has resulted in great losses in the health care industry, since medical information plays an essential role in human health. To introduce a comprehensive survey about possible cyber-attacks and solutions for these attacks, our paper first presents a brief overview of the necessary background of the dataflow in the medical domain and then identifies the vulnerabilities in each stage of the dataflow. Then, according to the weaknesses identified in the medical system, a classification of cyber-attacks is presented. Additionally, the paper presents research on previous work that focuses on solving these cyber-attacks and identifies the strengths and limitations of the solutions for each attack. More importantly, for data storage assurance, our paper discusses several cybersecurity architectures for the medical domain from the existing literature. The countermeasures from previous papers and architectures that are still weak in terms of resource depletion, attack reduction, applicability, etc. are addressed. Finally, the paper discusses and recommends solutions for future work to decrease cyber-attacks in the medical field so that human health can be guaranteed

Survey: Cybersecurity Vulnerabilities, Attacks and Solutions in the Medical Domain

Recently, an increasing number of cyber-attacks in the medical field has resulted in great losses in the health care industry, since medical information plays an essential role in human health. To introduce a comprehensive survey about possible cyber-attacks and solutions for these attacks, our paper first presents a brief overview of the necessary background of the dataflow in the medical domain and then identifies the vulnerabilities in each stage of the dataflow. Then, according to the weaknesses identified in the medical system, a classification of cyber-attacks is presented. Additionally, the paper presents research on previous work that focuses on solving these cyber-attacks and identifies the strengths and limitations of the solutions for each attack. More importantly, for data storage assurance, our paper discusses several cybersecurity architectures for the medical domain from the existing literature. The countermeasures from previous papers and architectures that are still weak in terms of resource depletion, attack reduction, applicability, etc. are addressed. Finally, the paper discusses and recommends solutions for future work to decrease cyber-attacks in the medical field so that human health can be guaranteed