An Enhanced WLAN Security System With FPGA Implementation for Multimedia Applications

Maintaining a high level of data security with a low impact on system performance is more challenging in wireless multimedia applications. Protocols that are used for wireless local area network (WLAN) security are known to significantly degrade performance. In this paper, we propose an enhanced security system for a WLAN. Our new design aims to decrease the processing delay and increase both the speed and throughput of the system, thereby making it more efficient for multimedia applications. Our design is based on the idea of offloading computationally intensive encryption and authentication services to the end systems’ CPUs. The security operations are performed by the hosts’ central processor (which is usually a powerful processor) before delivering the data to a wireless card (which usually has a low-performance processor). By adopting this design, we show that both the delay and the jitter are significantly reduced. At the access point, we improve the performance of network processing hardware for real-time cryptographic processing by using a specialized processor implemented with field-programmable gate array technology. Furthermore, we use enhanced techniques to implement the Counter (CTR) Mode with Cipher Block Chaining Message Authentication Code Protocol (CCMP) and the CTR protocol. Our experiments show that it requires timing in the range of 20–40 μs to perform data encryption and authentication on different end-host CPUs (e.g., Intel Core i5, i7, and AMD 6-Core) as compared with 10–50 ms when performed using the wireless card. Furthermore, when compared with the standard WiFi protected access II (WPA2), results show that our proposed security system improved the speed to up to 3.7 times.

A lightweight indoor localization model based on motley-keenan and COST

This paper presents a novel approach to WLAN propagation models for use in indoor localization. The major goal of this work is to eliminate the need for in situ data collection to generate the Fingerprinting map, instead, it is generated by using analytical propagation models such as: COST Multi-Wall, COST 231 average wall and Motley- Keenan. As Location Estimation Algorithms kNN (K-Nearest Neighbour) and WkNN (Weighted K-Nearest Neighbour) were used to determine the accuracy of the proposed technique. This work is based on analytical and measurement tools to determine which path loss propagation models are better for location estimation applications, based on Receive Signal Strength Indicator (RSSI).This study presents different proposals for choosing the most appropriate values for the models parameters, like obstacles attenuation and coefficients. Some adjustments to these models, particularly to Motley-Keenan, considering the thickness of walls, are proposed. The best found solution is based on the adjusted Motley-Keenan and COST models that allows to obtain the propagation loss estimation for several environments.Results obtained from two testing scenarios showed the reliability of the adjustments, providing smaller errors in the measured values values in comparison with the predicted values.