Due to the broadcast nature of radio propagation, the wireless air interface is open and accessible to both authorized and illegitimate users. This completely differs from a wired network, where communicating devices are physically connected through cables and a node without direct association is unable to access the network for illicit activities. The open communications environment makes wireless transmissions more vulnerable than wired communications to malicious attacks, including both the passive eavesdropping for data interception and the active jamming for disrupting legitimate transmissions. Therefore, this paper is motivated to examine the security vulnerabilities and threats imposed by the inherent open nature of wireless communications and to devise efficient defense mechanisms for improving the wireless network security. We first summarize the security requirements of wireless networks, including their authenticity, confidentiality, integrity, and availability issues. Next, a comprehensive overview of security attacks encountered in wireless networks is presented in view of the network protocol architecture, where the potential security threats are discussed at each protocol layer. We also provide a survey of the existing security protocols and algorithms that are adopted in the existing wireless network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term evolution (LTE) systems. Then, we discuss the state of the art in physical-layer security, which is an emerging technique of securing the open communications environment against eavesdropping attacks at the physical layer. Several physical-layer security techniques are reviewed and compared, including information-theoretic security, artificial-noise-aided security, security-oriented beamforming, diversity-assisted security, and physical-layer key generation approaches. Since a jammer emitting radio signals can readily interfere with the legitimate wireless users, we also introduce the family of various jamming attacks and their countermeasures, including the constant jammer, intermittent jammer, reactive jammer, adaptive jammer, and intelligent jammer. Additionally, we discuss the integration of physical-layer security into existing authentication and cryptography mechanisms for further securing wireless networks. Finally, some technical challenges which remain unresolved at the time of writing are summarized and the future trends in wireless security are discussed.

/pdf/a-survey-on-wireless-security-technical-challenges-recent-3uamoalvot.pdf

A Survey on Wireless Security: Technical Challenges, Recent Advances, and Future Trends

This paper examines the security vulnerabilities and threats imposed by the inherent open nature of wireless communications and to devise efficient defense mechanisms for improving the wireless network security. We first summarize the security requirements of wireless networks, including their authenticity, confidentiality, integrity and availability issues. Next, a comprehensive overview of security attacks encountered in wireless networks is presented in view of the network protocol architecture, where the potential security threats are discussed at each protocol layer. We also provide a survey of the existing security protocols and algorithms that are adopted in the existing wireless network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term evolution (LTE) systems. Then, we discuss the state-of-the-art in physical-layer security, which is an emerging technique of securing the open communications environment against eavesdropping attacks at the physical layer. We also introduce the family of various jamming attacks and their counter-measures, including the constant jammer, intermittent jammer, reactive jammer, adaptive jammer and intelligent jammer. Additionally, we discuss the integration of physical-layer security into existing authentication and cryptography mechanisms for further securing wireless networks. Finally, some technical challenges which remain unresolved at the time of writing are summarized and the future trends in wireless security are discussed.

/pdf/a-survey-on-wireless-security-technical-challenges-recent-k705wofne7.pdf

A Survey on Wireless Security: Technical Challenges, Recent Advances and Future Trends

An automated irrigation system was developed to optimize water use for agricultural crops. The system has a distributed wireless network of soil-moisture and temperature sensors placed in the root zone of the plants. In addition, a gateway unit handles sensor information, triggers actuators, and transmits data to a web application. An algorithm was developed with threshold values of temperature and soil moisture that was programmed into a microcontroller-based gateway to control water quantity. The system was powered by photovoltaic panels and had a duplex communication link based on a cellular-Internet interface that allowed for data inspection and irrigation scheduling to be programmed through a web page. The automated system was tested in a sage crop field for 136 days and water savings of up to 90% compared with traditional irrigation practices of the agricultural zone were achieved. Three replicas of the automated system have been used successfully in other places for 18 months. Because of its energy autonomy and low cost, the system has the potential to be useful in water limited geographically isolated areas.

Automated Irrigation System Using a Wireless Sensor Network and GPRS Module

Blended learning has become an increasingly popular form of e-learning, and is particularly suitable to the process of transitioning towards e-learning from traditional forms of learning and teaching. This paper describes the use of the blended e-learning model, which is based on a mixture of collaborative learning, problem-based learning (PBL) and independent learning, in a course ldquoTeaching Methods in Information Science,rdquo given at the University of Rijeka, Rijeka, Croatia. This model is realized as a combination of a face-to-face environment and online learning, using a proprietary learning management system (LMS) named adaptive hypermedia courseware (AHyCo). AHyCo is based on adaptive hypermedia and in addition to supporting learning and testing, introduces completely new constructivist and cognitivist elements to education. By supporting collaborative and project-oriented activities AHyCo promotes students' motivation for learning and establishes learning as an active and interactive process. This paper describes both the technology for, and the methodological approach to, course design and development which is aimed at supporting the evolution from traditional teaching to active learning, and raising interest in the topics of e-learning and Web courseware development among IT students. A survey conducted in the end of the course showed that students were satisfied with the pedagogical approach, and their academic achievements were also better than expected. Particularly important is that the dropout rate was greatly diminished, which could be related to students' satisfaction with the support they received from the instructor and the system.

A Blended Learning Approach to Course Design and Implementation

Structural health monitoring (SHM) using wireless sensor networks (WSNs) has gained research interest due to its ability to reduce the costs associated with the installation and maintenance of SHM systems. SHM systems have been used to monitor critical infrastructure such as bridges, high-rise buildings, and stadiums and has the potential to improve structure lifespan and improve public safety. The high data collection rate of WSNs for SHM pose unique network design challenges. This paper presents a comprehensive survey of SHM using WSNs outlining the algorithms used in damage detection and localization, outlining network design challenges, and future research directions. Solutions to network design problems such as scalability, time synchronization, sensor placement, and data processing are compared and discussed. This survey also provides an overview of testbeds and real-world deployments of WSNs for SH.

Structural Health Monitoring Using Wireless Sensor Networks: A Comprehensive Survey

Dataset of Methods for Lowering the Power Consumption of OS-Based Adaptive Deep Brain Stimulation Controllers

Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. Moreover, the specific constraints of WSN make the problem even more critical. However, effective solutions have not been implemented yet. Among the specific attacks derived from new cognitive features, the one most studied is the Primary User Emulation (PUE) attack. This paper discusses a new approach, based on anomaly behavior detection and collaboration, to detect the PUE attack in CWSN scenarios. A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. The algorithm has been tested using a cognitive simulator that brings important results in this area. For example, the result shows that the number of collaborative nodes is the most important parameter in order to improve the PUE attack detection rates. If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives.

https://journals.sagepub.com/doi/pdf/10.1155/2013/815959

PUE Attack Detection in CWSN Using Collaboration and Learning Behavior

The identification of a new generation of adaptive strategies for deep brain stimulation (DBS) will require the development of mixed hardware-software systems for testing and implementing such controllers clinically. Towards this aim, introducing an operating system (OS) that provides high-level features (multitasking, hardware abstraction, and dynamic operation) as the core element of adaptive deep brain stimulation (aDBS) controllers could expand the capabilities and development speed of new control strategies. However, such software frameworks also introduce substantial power consumption overhead that could render this solution unfeasible for implantable devices. To address this, in this work four techniques to reduce this overhead are proposed and evaluated: a tick-less idle operation mode, reduced and dynamic sampling, buffered read mode, and duty cycling. A dual threshold adaptive deep brain stimulation algorithm for suppressing pathological oscillatory neural activity was implemented along with the proposed energy saving techniques on an energy-efficient OS, YetiOS, running on a STM32L476RE microcontroller. The system was then tested using an emulation environment coupled to a mean field model of the parkinsonian basal ganglia to simulate local field potential (LFPs) which acted as a biomarker for the controller. The OS-based controller alone introduced a power consumption overhead of 10.03 mW for a sampling rate of 1 kHz. This was reduced to 12 μW by applying the proposed tick-less idle mode, dynamic sampling, buffered read and duty cycling techniques. The OS-based controller using the proposed methods can facilitate rapid and flexible testing and implementation of new control methods. Furthermore, the approach has the potential to become a central element in future implantable devices to enable energy-efficient implementation of a wide range of control algorithms across different neurological conditions and hardware platforms.

Methods for Lowering the Power Consumption of OS-Based Adaptive Deep Brain Stimulation Controllers.

The loss of efficiency and dependability in wireless communications, caused by the increasing spectrum scarcity problem, is particularly critical for battery-powered devices such as sensor nodes. Cognitive Wireless Sensor Networks (CWSNs) arise in order to mitigate this situation by adding cognitive radio capabilities to them. However, the closed architecture and limited resources of traditional nodes represent a major constraint to perform certain required cognitive tasks. On the other hand, Software-Defined Radios (SDRs), which have the flexibility and performance needed to overcome the aforementioned limitations, currently have a power consumption too high for these networks. In this work, we propose a hybrid methodology of operation that consists of exploiting SDR technology only for those actions that strictly require its high flexibility, using traditional fixed hardware transceivers, which demand less node’s resources, for the remaining tasks. Then, we present the architecture and the main electronic components of a platform able to operate according to this methodology. This solution constitutes a significant reduction in power consumption compared with existing low-power SDRs, while maintaining the functionality needed for research in CWSNs.

A Hybrid Approach to Enhance Cognitive Wireless Sensor Networks with Energy-Efficient Software-Defined Radio Capabilities

User interaction with the intelligent environment should not require the user to adapt to special conventions or rules. It should be the environment who should adapt to the natural way of users interaction, but the tight resource constraints of the embedded sensors do not allow complex video processing algorithms to be executed in real time.

In this paper we present a low-cost approach to camera-based gesture recognition for intelligent environments, minimizing the required communication between sensors and servers, and performing most of the image processing in low-cost battery-powered microcontrollers.

Alvaro Araujo

Papers

Dataset of Methods for Lowering the Power Consumption of OS-Based Adaptive Deep Brain Stimulation Controllers

PUE Attack Detection in CWSN Using Collaboration and Learning Behavior

Methods for Lowering the Power Consumption of OS-Based Adaptive Deep Brain Stimulation Controllers.

A Hybrid Approach to Enhance Cognitive Wireless Sensor Networks with Energy-Efficient Software-Defined Radio Capabilities

Low-Cost Gesture-Based Interaction for Intelligent Environments