Intrusion detection system thesis pdf

In 2015, Viegas and his colleagues [37] proposed an anomaly-based intrusion detection engine, aiming System-on-Chip (SoC) for applications in Internet of Things (IoT), for instance. The proposal applies machine learning for anomaly detection, providing energy-efficiency to a Decision Tree, Naive-Bayes, and k-Nearest Neighbors classifiers implementation in an Atom CPU and its hardware-friendly implementation in a FPGA. [38] [39] In the literature, this was the first work that implement each classifier equivalently in software and hardware and measures its energy consumption on both. Additionally, it was the first time that was measured the energy consumption for extracting each features used to make the network packet classification, implemented in software and hardware. [40]

Intrusion detection system thesis pdf

intrusion detection system thesis pdf

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intrusion detection system thesis pdfintrusion detection system thesis pdfintrusion detection system thesis pdfintrusion detection system thesis pdf