Muhammad R. Ahmed

Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network

Underwater wireless sensor network (UWSN) technology has introduced a new flux to a whole gamut of application domains such as scientific exploration, commercial exploitation, underwater disaster prevention, etc. Such diversity of UWSN has gained prominence to the researchers quite fast and has marked this field of research as one of the emerging ones. With extensive researches conducted in this field, several design challenges have been experienced and explored by the network designers. Large propagation delay, low bandwidth, frequent loss of connectivity, variability of sound speed, limitation on source of energy, etc. are the key challenges, which are identified as necessary issues for establishing efficient and reliable UWSN. To address these issues, several MAC and routing protocols for UWSN have been proposed by the researchers during the last decade. In this review, the core design aspects for an ideal UWSN are identified which are energy-efficiency and reliability. These design aspects are evaluated in terms of energy consumption and communication efficiency - in order to provide an insight to the network designers on ideal design metrics. It is found that the protocols are highly selective, and the fitness of any protocol depends solely on the application and design requirements, which is addressed by this review. This paper also provides a comprehensive overview through comparison and simulation to analyze and summarize the MAC and routing protocols under concern.

Timing control for protecting from internal attacks in wireless sensor networks

Wireless sensor networks (WSNs) are widely used due to they are easy and rapid deployed, low cost, low power, self-organized, cooperatively collect the environmental information and realize the integration of the physical world and communication network. It is the fact that due to open nature of the wireless medium an adversary can easily eavesdrop and replay or inject fabricated messages. Different cryptographic methods can be used to defend against some of such attacks. However, node compromise is another major problem of WSN security as it allows an adversary to enter inside the security perimeter of the network, which raised a serious challenge for WSNs. This paper is focusing on investigating internal attacks of wireless sensor networks, by which we show our novel method will work well for the security under some fixed parameters designed by the network designer, we also have reasonable model for predicting the highest signal noise ratio (S/N). “Timing control” method is to be used for protecting internal attacks in SWNs. Therefore we may allow a sinker to be open only around a particular time period to receive the signals from the sources while the other time slots are in “sleeping state” to ignore any signals, including the internal attacking signal. In particularly, we found the highest S/N timing can be controlled by the sending rating for a fixed network. We can easily manipulate the sending rate to control the time when the highest S/N is occurring to protect from “internal attacks.” The simulation results have been shown and they underpinned our novel algorithm.

Wireless sensor network internal attacker identification with multiple evidence by dempster-shafer theory

Wireless sensor Network (WSN) is known to be vulnerable to variety of attacks due to the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or insider attacker has gained prominence and poses the most challenging attacks to WSN. Many works has been done to secure WSN from internal attacker but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure WSN need to find the internal attacker. Normally, internal attacker node behavioral pattern is different from the other neighbor good nodes in the system, but neighbor node can be attacked as well. In this paper, we use Dempster-Shafer theory (DST) of combined multiple evidence to identify the malicious or internal attacker in WSN. This theory reflects with the uncertain event or uncertainty as well as uncertainty of the observation. Moreover, it gives a numerical procedure for fusing together multiple pieces of evidence from unreliable neighbor with higher degree of conflict reliability.

A Novel Trust and Reputation Model Based WSN Technology to Secure Border Surveillance

Border surveillance systems have recently came into attention to address the concerns about national security. Conventional border surveillance or petrol systems consist of check points and border troops. The existing system for surveillance suffers from intensive human involvement. The recent technology is expensive as it requires using high-tech devices e.g. Unmanned aerial vehicles, unattended ground sensors, and surveillance towers equipped with Radar and camera sensors. These techniques suffer with problems such as high false alarm rate and for communication line of sight is necessary. In such surveillance system wireless sensor network is cost effective and efficient for event detection in the large area with multi hope communications. Using Wireless Sensor Network (WSN) the task of object tracking or event detection has been investigated but not much attention was given to secure the border. In this paper the security analysis of the border and a trust and reputation based WSN is presented secure border surveillance with some simulation results.

Outage capacity analysis of cluster-based forwarding scheme for Body Area Network using nano-electromagnetic communication

The emergence of nano-electromagnetic communication becomes appealing for potential applications in nano-scale Body Area Network. In this work a new energy aware communication model for nano-electromagnetic communication in Terahertz Band is developed based on clustering scheme for the performance improvement of BAN. The proposed conceptual network model is used to determine channel capacity. A closed-form expression for outage probability is also derived. The approach is extended to determine outage capacity for maintaining a constant rate with a specified outage probability. Simulation shows that in term of capacity, proposed scheme outperforms the random forwarding scheme.

An Energy Conserving Routing Scheme for Wireless Body Sensor Nanonetwork Communication

Current developments in nanotechnology make electromagnetic communication possible at the nanoscale for applications involving body sensor networks (BSNs). This specialized branch of wireless sensor networks, drawing attention from diverse fields, such as engineering, medicine, biology, physics, and computer science, has emerged as an important research area contributing to medical treatment, social welfare, and sports. The concept is based on the interaction of integrated nanoscale machines by means of wireless communications. One key hurdle for advancing nanocommunications is the lack of an apposite networking protocol to address the upcoming needs of the nanonetworks. Recently, some key challenges have been identified, such as nanonodes with extreme energy constraints, limited computational capabilities, terahertz frequency bands with limited transmission range, and so on, in designing protocols for wireless nanosensor networks. This work proposes an improved performance scheme of nanocommunication over terahertz bands for wireless BSNs making it suitable for smart e-health applications. The scheme contains – a new energy-efficient forwarding routine for electromagnetic communication in wireless nanonetworks consisting of hybrid clusters with centralized scheduling; a model designed for channel behavior taking into account the aggregated impact of molecular absorption, spreading loss, and shadowing; and an energy model for energy harvesting and consumption. The outage probability is derived for both single and multilinks and extended to determine the outage capacity. The outage probability for a multilink is derived using a cooperative fusion technique at a predefined fusion node. Simulated using a nano-sim simulator, performance of the proposed model has been evaluated for energy efficiency, outage capacity, and outage probability. The results demonstrate the efficiency of the proposed scheme through maximized energy utilization in both single and multihop communications; multisensor fusion at the fusion node enhances the link quality of the transmission.

Design of a tri-band implantable antenna for wireless telemetry applications

In this paper, a miniaturized Egret-Beak shaped patch tri-band implantable antenna for Medical Implant Communication Services (MICS) (402-405 MHz), Wireless Medical Telemetry Service (WMTS) (1430MHz) and Industrial Scientific and Medical (ISM) (2.4-2.48GHz) band is proposed. The antenna is composed of an Egret-Beak shaped radiation patch and a ground plane. A shorting pin is directly connects from the radiating patch to the ground plane to reduce the size of the antenna. The antenna occupies a small size of 10×12mm2. The antenna is optimized to achieve the triple band designed antenna. The results indicates that the antenna can achieve 260MHz (74%) band for MICS, 150MHz (11%) band for WMTS and 680MHz (27%) band for ISM band. The proposed antenna (implanting in the arm) with significant impedance bandwidth and its compactness shows that the antenna is suitable for wireless telemetry applications.

Dempster-Shafer Theory to Identify Insider Attacker in Wireless Sensor Network

Due to the construction and network infrastructure of wireless sensor network (WSN) are known to be vulnerable to variety of attacks. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Several works have been done to secure WSN, but identification of insider attacker has not been given much attention. In the WSN system the malicious node behavior is different from the neighbor nodes. Instead of relying the untrustworthy neighbor node we use Dempster-Shafer theory (DST) of combined evidence to identify the insider attacker in WSN. This theory reflects with the uncertain event or uncertainty as well as uncertainty of the observation. The mathematical calculation shows the DST capability of identifying the insider attacker.

A novel misbehavior evaluation with dempster-shafer theory in wireless sensor networks

Misbehavior evaluation in Wireless Sensor Network (WSN) has attracted significant attention to provide the complete security in the network. Many schemes have been proposed to identify misbehaving nodes in WSN. Most of these mechanisms relay on either predefined threshold or a set a training dataset. But it is not realistic to set a threshold or collecting training dataset of an attack ahead of time. In this paper, we have proposed a misbehaviour evaluation technique based on the dempster-shafer theory by combining the observation result by multiple neighbor nodes.

Malicious attack detection in underwater wireless sensor network

Under-water wireless sensor network (UWSN) in one of the auspicious technology for marine observation. The applications of underwater sensing has several domain that range from oil industry to aquaculture. Some of the UWSN applications includes device checking, underwater ecosystems monitoring, forecasting of natural disasters and disturbances, exploration and survey missions, as well as study of oceanic life. With the characteristics and applications platform of UWSN, security of UWSN is a critical issue and had drawn significant attention to the researchers. In order to have a functional UWSN to extract the authentic data safeguarding and protection mechanisms are crucial. Malicious node attacks has accomplished eminence and constitute the utmost challenging attacks to UWSN. Several research has been conducted to protect UWSN from malicious attacks but majority of the works depend on a defined threshold prior to the deployment or a training data set. It is a complication and challenge for UWSN that with no established security groundwork a UWSN required to detect the malicious attacks. In this paper, we support vector machine to identify the malicious attacks in a UWSN. SVM delivers good result and its training time is much smaller comparing with neural networks.