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Table 8 Performance evaluation of autoenocder, QAE-f16 and QAE-u8 models on Raspberry Pi IoT device

From: Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset

Methods

Memory size (bytes)

Average memory utilization (MiB)

Peak memory utilization(MiB)

Average CPU utilization

Peak CPU utilization

Time consumption (s)

Autoencoder

79,432

154.23

219.19

115.87

184

34

QAE-f16

8368

51.64

63.84

107.31

201

24

QAE-u8

6168

46.24

57.06

111.51

147

15