Wireless Sensor Networks (WSNs) consist of sensor nodes deployed in a manner to collect information about surrounding environment. Their distributed nature, multihop data forwarding, and open wireless medium are the factors that make WSNs highly vulnerable to security attacks at various levels. Intrusion Detection Systems (IDSs) can play an important role in detecting and preventing security attacks. This paper presents current Intrusion Detection Systems and some open research problems related to WSN security.
The important function of a sensor network is to collect and forward data to destination. It is very important to know about the location of collected data. This kind of information can be obtained using localization technique in wireless sensor networks (WSNs). Localization is a way to determine the location of sensor nodes. Localization of sensor nodes is an interesting research area, and many works have been done so far. It is highly desirable to design low-cost, scalable, and efficient localization mechanisms for WSNs. In this paper, we discuss sensor node architecture and its applications, different localization techniques, and few possible future research directions.
Most sensor networks are deployed at hostile environments to sense and gather specific information. As sensor nodes have battery constraints, therefore, the research community is trying to propose energyefficient solutions for wireless sensor networks (WSNs) to prolong the lifetime of the network. In this paper, we propose an energy-efficient multi-level and distance-aware clustering (EEMDC) mechanism for WSNs. In this mechanism, the area of the network is divided into three logical layers, which depends upon the hop-count-based distance from the base station. The simulation outcomes show that EEMDC is more energy efficient than other existing conventional approaches. Figure 15. Number of nodes alive over simulation time (seconds).
Multi-hop wireless mesh networks (WMNs) are increasingly growing interest as a promising technology for high-speed network access. WMNs are integrated with other networks such as Internet, sensor networks, and cellular networks through gateways. Therefore gateways in WMNs are prone to various security threads and can be easily exploited by the attacker from any part of the Internet to launch a distributed flooding attack to compromise computer systems, affect the network performance, and destruct the services. Many approaches have been proposed by researchers in this regard but still more efforts are needed in terms of accuracy and efficiency. In this research paper, we will propose an artificial neural network-based technique for detection of distributed flooding attacks to things such as sensors or actuators in WMNs called the distributed flood attack detector. In our simulation, sample dataset used to train and test the artificial neural network is generated using NS-2 network simulator. Simulation results and real system implementation proved that the distributed flood attack detector can be used in a real network environment to detect the intermediate and severe distributed flood attacks with low-false positive and false-negative rates.
Increasing use of wireless networks has empowered the facility of ubiquitous health monitoring especially in advanced countries. Various small devices are attached to human body forming personalized wireless body area network (WBAN). These small devices interact with each other using different radios and antennas schemes proposed by many researchers around the globe. However, most of these schemes are facing problem of inefficiency due to fading and shadowing effects. We propose a novel multi-radio multichannel framework for efficient communication among devices in WBAN. The focus of this research is to ensure energy efficient and reliable communication in WBAN.
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