A Distributed Approach to Security in Sensornets

Abstract — Secure communication is an important aspect of any network and it has largely remained unexplored in wireless sensor networks (WSN). Security becomes a major challenge because of ad-hoc and resource constrained nature of sensor networks. In this paper we present a scalable and distributed security protocol, DSPS, for WSN that fits in between the network and the transport layers. DSPS satisfies the essential requirements of secure communication such as Data Confidentiality, Data Authentication, Data Integrity and Data Freshness. Basic building blocks of our security protocol are Key Generation-Distribution and Signatures. The key is a 56-bit random number generated initially by a key server, which is then securely distributed to all the nodes in the cluster. This key is used for encryption. DSPS also supports security critical transactions by dynamically generating a key, which can be shared between two nodes. The simplicity of DSPS allows compatibility with most of the routing protocols. Keywords-component; wireless sensor networks (WSN); security protocols; I

An Empirical Study to Investigate the Effect of Air Density Changes on the DSRC Performance

The primary role of Intelligent Transportation Systems (ITS) system is to implement Advanced Driver Assistance Services (ADAS) such as pedestrian detection, fog detection and collisions avoidance. These services rely on detecting and communicating the environment conditions such as heavy rain or snow with nearby vehicles to improve the driver\u27s visibility. ITS systems rely on DSRC to communicate this information via a Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) communications architectures. DSCR performance may be susceptible to environmental changes such as air density, gravitation (gravitational acceleration), air temperature, atmospheric pressure, humidity, and precipitation. The goal of this research is to investigate whether the DSRC performance persist with respect to air density changes in a foggy environment. Simulation experiments are setup using PreScan to study the influence of changing the air density on the DSRC performance in a foggy environment using V2V communications. The PreScan simulation experiments are carried out over a wide range of air density levels that start from an extremely low value of (0.05 kg/m3), a normal air density level of 1.28 kg/m3 to a high altitude with air density level of (50 kg/m3). The study uses this wide range of air density levels to allow us to determine the influence of the air density on the DSRC performance and explore any performance inconsistency if there is any. The research findings proved that the DSRC performance can persist through air density changes, which helps to make up for lost human visibility on roads during foggy times. This finding aims to promote safe highway operations in foggy conditions

DSCR Based Sensor-Pooling Protocol for Connected Vehicles in Future Smart Cities

Smart cities are racing to create a more connected Intelligent Transportation Systems (ITS) that rely on collecting data from every possible sensor such as a smart utility meter or a smart parking meter. The use of more sensors resulted in generating a lot of information that maps the smart city environment conditions to more real time data points that needed to be shared and analyzed among smart city nodes. One possibility, to carry and share the collected data, is in autonomous vehicles systems, which use the Dedicated Short Range Communications (DSRC) technology. For example, in a Car-to-Parking-Meter or a Vehicle-to-Vehicle (V2V) communications, short-range embedded sensors such as Bluetooth, Cameras, Lidar send the collected data to the vehicle’s Electronic Control Unit (ECU) or to a road side gateway for making collaborative decisions and react to the environment’s surrounding conditions. The goal of this research is to develop and test a DSRC based sensor-pooling protocol for vehicles to cooperatively communicate inclement weather or environment conditions. Five simulation experiments are setup using PreScan and Simulink to validate and study the scalability of the proposed solution. PreScan is an automotive simulation platform that is used for developing and testing Advanced Driver Assistance System (ADAS). The research findings proved that the DSRC can be used to effectively stream the short range sensors’ collected data over a long distance communications link

The Minimum Scheduling Time for Convergecast in Wireless Sensor Networks

We study the scheduling problem for data collection from sensor nodes to the sink node in wireless sensor networks, also referred to as the convergecast problem. The convergecast problem in general network topology has been proven to be NP-hard. In this paper, we propose our heuristic algorithm (finding the minimum scheduling time for convergecast (FMSTC)) for general network topology and evaluate the performance by simulation. The results of the simulation showed that the number of time slots to reach the sink node decreased with an increase in the power. We compared the performance of the proposed algorithm to the optimal time slots in a linear network topology. The proposed algorithm for convergecast in a general network topology has 2.27 times more time slots than that of a linear network topology. To the best of our knowledge, the proposed method is the first attempt to apply the optimal algorithm in a linear network topology to a general network topology

Anomaly intrusion detection in Wireless Sensor networks

Abstract: We propose lightweight methods to detect anomaly intrusions in wireless sensor networks (WSNs). The main idea is to reuse the already available system information that is generated at various layers of a network stack. To the best of our knowledge, this is the first such approach for anomaly intrusion detection in WSNs