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Network Intrusion Detection Systems (NIDSs) play a crucial role in detecting malicious activities within the networks. Basically, an NIDS monitors network flows and compares it with the pre-defined suspicious patterns. To be effective, different intrusion detection algorithms and packet capturing methods have been implemented. With rapidly increasing network speeds, NIDSs face a challenging problem of monitoring large and diverse traffic volumes; in particular, the high packet drop rate has a significant impact on detection accuracy. In this work, we investigate three popular open-source NIDSs: Snort, Suricata, and Bro along with their comparative performance benchmarks. We investigate key factors (including system resource usage, packet processing speed and packet drop rate) that limit applicability of NIDSs to large-scale networks. Moreover, we also analyse and compare the performance of NIDSs when configurations and traffic volumes are changed.
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Hu et al. (2017) studied this question.
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