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WLAN Integrated with GPRS Network Securely
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In this paper a WLAN network that accesses the Internet through a GPRS network was implemented and tested. The proposed network is managed by the Linux based server. Because of the limited facilities of GPRS such as dynamic IP addressing besides to its limited bandwidth a number of techniques are implemented to overcome these limitations.

      Dynamic Host Configuration Protocol (DHCP) server was added to provide a single central control for all TCP/IP resources. Squid Proxy  was added to provide caching of the redundant accessed Web content to reduce the Internet bandwidth usage and speeding up the client’s download time. Network Address Translation (NAT) service was configured to share one IP address among several different systems. In order to accomplish a secure channel to exchange data between two network devices, the Secure Shell (SSH) protocol was added.

The first test shows that the data transfer rate at different time intervals of the day found to be an average of 10.95 Kbps for uploading and 13.7 Kbps for downloading and the second test shows that the network performance improved when squid proxy cache was used. The data rate found to be 143.3 Kbps average for uploading rate and 376.6 Kbps average for downloading rate.

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Publication Date
Tue Jun 30 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
Real-time Malware Prevention Using Gradient Boosted Decision Trees on the EMBER 2024 Dataset: A Static Analysis Approach for Windows PE Binaries
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The present paper describes a static model of malware detection and employs a tri-class prevention policy that operates on the EMBER 2024 Win64 partition. A LightGBM classifier trained on 1,040,000 samples and 804 static PE features achieves AUC-ROC = 0.9979, precision = 98.7%, recall = 97.4%, and F1 = 0.9805 on the temporally-split 240,000-sample test set. An innovative Tri-class Threshold Scheme (BLOCK/SUSPICIOUS/ALLOW) obtained by constrained F2-score optimisation on a separate validation set obtains 97.9% malware detection with 98.1% benign pass rate. Efficient model scoring is verified by mean per-sample model inference latency of 2.30 ms (P99: 2.70 ms) measured on pre-extracted EMBER features, future work is characterized by a complet

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