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Title |
Privacy Inferences and Performance Analysis of Open Source IPS/IDS to Secure IoT-Based WBAN |
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Author |
Amjad Ali, Dr. Maruf Pasha, Rabbiah Zaheer, Faiz Jillani,1 Urooj Pasha |
| Citation |
Vol. 22 No. 12 pp. 1-12 |
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Abstract |
Besides the unexpected growth perceived by IoT network, the variety and volume of security threads for such systems have increased, highlighting the importance of efficient intrusion prevention and detection system. But intrusion prevention and detection system inside the IoT network presents another challenge primarily due to their unique characteristics of such systems, such as Privacy inference, Performance, and detection rate and their frequency in the dynamic nature of networks. Our research focused on the privacy inferences of existing intrusion prevention and detection system approaches. We also tackle the problem of providing a solution to implement the open-source IDPS into the IoT architecture to check the performance of current IDS regarding their usage consumption and detection rate. The proposed scheme is considered to help implement the human health monitoring system in IoT networks |
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Keywords |
Privacy Inferences, IDS, IDS tools, WBAN, IoT Security, Performance assessment |
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