Mobile sensor networks (MSNs) have become a research hotspot recently and lead to a wide demand for wireless communication-based applications such as Internet of Things (IoTs), vehicular networks and mobile social networks, etc However, due to the power limitation of battery and the requirement of real time performance, it is critical to design an effective and efficient neighbor discovery protocol with minimal energy consumption and discovery latency Prior discovery protocols are essentially static, in which the passive discovery can be achieved when a pair of neighboring nodes are active at the same time according to their predefined schedules In this paper, we design a new neighbor discovery model, in which the beacons are separated from the active slots and the broadcast of beacons can be dynamically adjusted to accelerate the discovery Based on the model, we propose a proactive wakeup based energy-efficient neighbor discovery protocol called PWEND The PWEND is applicable to both the slot-aligned and slot-unaligned scenarios, and the worst-case discovery latency is obtained Furthermore, we extend the PWEND to make it applicable to the asymmetric scenario, where different nodes are with different duty cycles We implement and evaluate the PWEND protocol by state-based simulations and the simulation results show that PWEND protocol outperforms other existing ones

PWEND: Proactive wakeup based energy-efficient neighbor discovery for mobile sensor networks

The DDoS attack is a serious threat to the Internet of Things (IoT). As a new class of DDoS attacks, Link-flooding attack (LFA) disrupts connectivity between legitimate IoT devices and target servers by flooding only a small number of links. Several mechanisms have been proposed to mitigate the sophisticated attack. However, they can only reactively mitigate LFA after target links have been flooded by the adversaries. In this paper, we propose an active LFA mitigation mechanism, called Linkbait, that is a proactive and preventive defense to throttle LFA for IoT. The fact behind Linkbait is that adversaries rely on the set of key links impacting the network connectivity (i.e.,linkmap) to identify target links. Linkbait mitigates the attacks by interfering with linkmap discovery and providing a fake linkmap to adversaries. Inspired by moving target defense (MTD), we propose a link obfuscation algorithm in Linkbait that selectively reroutes probing flows to hide target links from adversaries and mislead them to identify bait links as target links. By providing the faked linkmap to adversaries, Linkbait can actively mitigate LFA for IoT even without identifying compromised IoT devices while not affecting flows from legitimate IoT devices. To block attack traffic and further reduce the impact in IoT, we propose a compromised IoT devices detection algorithm that extracts unique traffic patterns of LFA for IoT and leverages support vector machine (SVM) to identify attack traffic. We evaluate the performance of Linkbait by using both real-world experiments and large-scale simulations. The experimental results demonstrate the effectiveness of Linkbait.

Active Link Obfuscation to Thwart Link-flooding Attacks for Internet of Things.

The DDoS attack is a serious threat to Internet of Things (IoT). As a new class of DDoS attack, Link-flooding attack (LFA) disrupts connectivity between legitimate IoT devices and target servers by flooding only a small number of links. In this paper, we propose an active LFA mitigation mechanism, called Linkbait, that is a proactive and preventive defense to throttle LFA for IoT. We propose a link obfuscation algorithm in Linkbait that selectively reroutes probing flows to hide target links from adversaries and mislead them to identify bait links as target links. To block attack traffic and further reduce the impact in IoT, we propose a compromised IoT devices detection algorithm that extracts unique traffic patterns of LFA for IoT and leverages support vector machine (SVM) to identify attack traffic. We evaluate the performance of Linkbait by using both real-world experiments and large-scale simulations. The experimental results demonstrate the effectiveness of Linkbait.

Active Link Obfuscation to Thwart Link-flooding Attacks for Internet of Things

The traditional mouse has been used as a main tool for human-computer interaction for more than 50 years. However, it has become unable to cater to people’s need for mobile officing and all-weather use due to its reliance on the support of a two-dimensional plane, poor portability, wearisomeness, and other problems. In this paper, we propose a portable ring-type wireless mouse scheme based on IMU sensors and a multi-level decision algorithm. The user only needs to operate in the air with a smart ring worn on the middle finger of their right hand to realize the interactive function of a mouse. The smart ring first captures changes in the finger’s attitude angle to reflect how the cursor position changes. And, it captures the rapid rotation of the user’s palm to the left and right to achieve mouse clicking. In addition, a multi-level decision algorithm is developed to improve the response speed and recognition accuracy of the virtual mouse. The experimental results show that the virtual mouse has a target selection accuracy of over 96%, which proves its practicability in real-world applications. This virtual mouse is expected to be used as a portable and reliable tool for multi-scenario human-computer interaction applications in the future.

Mouse on a Ring: A Mouse Action Scheme Based on IMU and Multi-Level Decision Algorithm

This paper introduces a novel hand-free human–computer interaction system called AirMouse, which turns a common pair of glasses into a mouse to enable the interaction between computers and humans, especially for disabled people. The basic idea is to simulate mouse operations with head activities without using hands. To this end, an embedded device is attached to a pair of glasses, which leverages the gyroscope to accurately detect head activities and map them to corresponding mouse operations on devices (e.g., computers and smart TVs). In particular, AirMouse uses activities to simulate mouse operations instead of tracking the gaze or the head movements in the real-time manner. This provides flexibility to users allowing them to control devices even far away or not at front of the devices. We implement a prototype of AirMouse with the personalized pretraining module and the motion detection module, which is featured with low-cost, accurate, easy-to-use and real-time interaction, and evaluate AirMouse with 20 volunteers. The experimental results show that AirMouse achieves accurate, reliable, and real-time activity recognition and interaction. Specially, the technique of AirMouse can be integrated into wearable devices (e.g., smart glasses) to enrich their interaction functionalities.

Huejie Shao

Papers

AirMouse: Turning a Pair of Glasses Into a Mouse in the Air