In this paper, a sensor is designed using a split ring resonator with the defected ground structure to classify three different types of breast cancer cell lines. The differentiation between the three types is based on measuring the reflection coefficient for each type.
The aim of this paper is to spotlight on a novel approach for energy transfer utilizing the gas pipelines. The new proposed system will be converting the electricity from renewable energy to potential energy in the form of pressure. The exported gas in the gas pipelines can be compressed to higher pressure to act as an energy transfer medium. Later on, along the pipeline the pressure can be converted back to electrical energy. The proposed system dynamics will be analyzed and optimized using TRNSYS and MATLAB .
The paper presents a novel ultra-low power, embedded, and wearable walk-cycle monitoring system with applications in areas such as health-care, robotics, sports medicine, physical therapy, prosthesis, and animal sports. Customized shoes with sensors continuously measure the forces, and an electronic digital assistant is used to analyze the acquired measurements in real time by employing an IMU free and self-synchronizing method in order to estimate weight and study motion patterns. To achieve ultra-low power operation, the human body is used as a communication medium between the sensors and the digital assistant. The single-channel behavior of the human body is accommodated with a novel, simple yet robust single-wire signaling technique, Pulsed-Index Communication (PIC), that significantly reduces the system footprint and overall power consumption as it eliminates the need for clock and data recovery. The system prototype has been rigorously and successfully tested.
Artificial neural networks are commonly known as Universal Approximators; a property immensely useful in system identification and control applications. Traditionally, neural networks are trained with gradient-descent backpropagation algorithms. However, these algorithms are computationally burdened and slow due to the calculation of error derivatives. As a result, the research focus has shifted to develop gradient-free neural algorithms. One famous approach is to incorporate Lyapunov Functions in network parameter optimization. In this paper, we briefly discuss and analyze one such recently developed algorithm from the point-of-view of its applicability in adaptive control paradigm. It has been found that with a few proposed modifications, this algorithm can work excellently as neuro-adaptive inverse controller.
The rapid adoption of systems using IoT technologies is poised to create many exposed systems with new security vulnerabilities. IoT applications from a variety of domains may face severe security holes. Significant security risks to IoT systems come from the large number of edge devices. Edge-devices are very small, wireless-enabled microcontrollers running primitive operating systems. Their resource-constrained nature in an IoT eco-system poses a challenge to many aspects of security. The primary objective is to provide recommendations to improve an IoT system's overall security profile with minimum impact to its operations. Key use-cases in various application areas of IoT will be used to conduct an experimental evaluation of IoT systems to detect vulnerabilities. Their impact on IoT systems will be investigated, and counter measures will be proposed. Power consumption and resource utilization data will be collected and analyzed, and various networking profiles including 2G, 4G, and Wi-Fi will be simulated.
Embedded systems are being aggressively integrated in every aspect of modern life, and their uses range from personal devices for everyday use and convenience to devices deployed in critical systems, such as autonomous vehicles, aircrafts and industrial control systems. An often neglected attribute of embedded systems is cybersecurity, which often leads to an expanded attack surface in the systems they are deployed. In this paper we present a novel attack vector that enables stealthy information leakage from an embedded system. Specifically, we leverage structural components present in modern embedded systems, namely the Device Tree Blob, to extract information about the hardware profile of the system. Utilizing this information, we introduce a stealthy attack that leaks information from arbitrary memory locations taking advantage of the Direct Memory Access (DMA) controller and existing side-channels.
Privacy requirements and the need for collaborative analysis has motivated a significant amount of research on anonymization techniques and privacy-aware analysis. Anonymization techniques are typically applied to data in order to retain the privacy of the data. Some anonymization techniques preserve certain distances and properties of the original data points without revealing compromising information about it which enables performing collaborative privacy-preserving analysis. However, typical Anonymization techniques require a lot of expertise and domain knowledge in order to be applied effectively because of the effects they have on certain properties of the data. In this paper we discuss the types of Anonymization techniques according to how it transformations the type of data.
A new open source project is introduced to simplify understanding of the limitations and security levels of configurations of SSL/TLS and ciphersuites.
The cyberspace creates one of the new front lines for countries to demonstrate power. Vigilant governments and those that have successfully launched attacks could be the next global giants [1]. The UAE has been a target for most of the recent cyber-attacks due to hasty economic growth, technology and the rise of oil and gas sector accelerated by the wide spread of internet to the tune of 90% by the end of 2014 [2]. In this paper, a meticulous review of cyber-attacks has been conducted in addition to identifying factors deterring effectiveness of the available defenses. The role of technology, training, awareness, competence of staff and senior management in the prevention of cyber-attacks has been evaluated. Results reveal that senior management has the responsibility of establishing strategies and policies for prevention, detection and mitigation of cyber-attacks. Finally, a framework is proposed to help entities evaluate their cybersecurity systems.
Intelligent transportation system using intelligent vehicular ad hoc networks (inVANETs) is one the main building blocks of future smart cities. It provides wireless communication between vehicles and different objects in the road to increase efficiency and human safety using various applications. However, all the attractive features of inVANETs will increase security risks and privacy problems if security attacks is not studied and analyzed thoroughly and completely. Denial of service attack is one of the most dangerous attacks since it targets the availability of the network/target services. This paper provides a unique classification for security attacks in inVANETs as well as classifies different types of DoS forms according to the mechanisms used by each attack.
