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This is the era of smart devices or things which are fueling the growth of Internet of Things (IoT). It is impacting every sphere around us, making our life dependent on this technological feat. It is of high concern that these smart things are being targeted by cyber criminals taking advantage of heterogeneity, minuscule security features and vulnerabilities within these devices. Conventional centralized IT security measures have limitations in terms of scalability and cost. Therefore, these smart devices are required to be monitored closer to their location ideally at the edge of IoT networks. In this paper, we explore how some security features can be implemented at the network edge to secure these smart devices. We explain the importance of Network Function Virtualization (NFV) in order to deploy security functions at the network edge. To achieve this goal, we introduce NETRA-a novel lightweight Docker-based architecture for virtualizing network functions to provide IoT security. Also, we highlight the advantages of the proposed architecture over the standardized NFV architecture in terms of storage, memory usage, latency, throughput, load average, scalability and explain why the standardized architecture is not suitable for IoT. We study the performance of proposed NFVbased edge analysis for IoT security and show that attacks can be detected with more than 95% accuracy in less than a second.

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As the population is increasing worldwide, huge need arises to provide proper health-care services. With the advent of modern technologies the need-gap may be augmented. Sensor is one such technology which can be used to enable Internet of Things based health-care monitoring system. In this paper, implementation of such a system is described. In a real time health monitoring system, there are many sensors connected to a local data processing unit through a shared channel having a fixed bandwidth. These sensors have a wide variety of channel access requirements. The access to the channel should be discrete, so that each and every sensor avails the required bandwidth and delay in the shared channel. In this paper, a scheduling technique is proposed for the IoT based system, which nullify interference among different sensors and consequent distortation of precious health data. Implementation of this technique in our prototype health-care monitoring application is discussed in this paper.

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