Circuit simulators have the capability to create virtual environment to test circuit design. Simulators save time and hardware cost. However, when components in circuit design increase, most simulators take longer time to test large circuit design, in many cases days or even weeks. Therefore, to handle large dataset and accurate performance, simulators need to be improved. In this paper, we propose machine learning-based parallel implementations of circuit analyser on graphics card with Compute Unified Device Architecture (CUDA). After parsing netlist file, the first approach is to analyse compute intensive mathematical functions and then convert it into parallel executable version. Further, we propose a Design-Level Parallelism with hybrid parallel implementation of components and processing methods. Dynamic decision-making is required to select functions and parameters to map on Graphics Processing Unit (GPU). To reduce load overhead, machine learning clustering approach has been adopted. Combination of procedure clustering and mapping takes few cycles but overall performance enhances efficiency as compared to serial processing.

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One of the most challenging network security concerns for network administrators is the presence of rogue access points. Rogue access points, if undetected, can be an open door to sensitive information on the network. Many data raiders have taken advantage of the undetected rogue access points to view confidential information. In this paper, we present a rogue access point detection approach. In this approach we are extending the functionality of basic analyzer. It will deeply analyse different properties of WLAN. If required it will calculate statistics and store it in databse. We can use this result to compare next data. Besides analyzing wireless data, some filters are implemented that can be used to identify rogue APs in WLAN. Actually people thinks that analyzer is just common approach but we can use this tool in WLAN in very efficient way ie to reduce time and cost. This topic comes under wireless security