Performance Analysis of IDS Snort and IDS Suricata with Many-Core Processor in Virtual Machines Against Dos/DDoS Attacks

Fadhilah, Dede; Marzuki, Marza Ihsan

doi:10.1109/bcwsp50066.2020.9249449

Cited by 12 publications

(2 citation statements)

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“…Snort is a de‐facto industry standard traditional network‐based IDS solution for detecting malicious activity. Snort monitors the network and detects the threats based on the concept of ‘Signatures’ 49,50 . These signatures are a set of rules of the network packet that signals ongoing threats.…”

Section: Experiments and Resultsmentioning

confidence: 99%

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P‐DNN: Parallel DNN based IDS framework for the detection of IoT vulnerabilities

Sharmila¹,

Nagapadma²

2023

Security and Privacy

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SummaryThe rapid growth of the Internet of Things (IoT) in our daily life has recently received attention from hackers in releasing novel attacks. This is because the existing traditional Intrusion Detection System (IDS) uses an alert‐based approach that cannot detect new emerging attacks, making it unfeasible for devices with limited resources. The study presents the deployment of a Parallel Deep Neural Network (P‐DNN) IDS framework to improve the detection rate and resource constraint issues. To validate the framework for detecting the latest IoT vulnerabilities, we generated a proprietary dataset created under the IoT environment. The experimental results reveal that the P‐DNN IDS framework proposed in this study outperformed the K‐nearest Neighbour (KNN), Support Vector Machine (SVM), and Naive Bayes algorithms with respect to performance metrics. In addition, a comparative analysis of the P‐DNN framework with Snort and Suricata IDS results demonstrates a significant reduction in CPU consumption, memory utilization, and processing time. The results of this investigation indicate that the deployment of the P‐DNN framework has the capability to detect vulnerabilities in resource‐constraint IoT environments effectively.

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Section: Experiments and Resultsmentioning

confidence: 99%

“…Snort monitors the network and detects the threats based on the concept of 'Signatures'. 49,50 These signatures are a set of rules of the network packet that signals ongoing threats. However, signatures cannot detect emerging threats or small variations in attack patterns.…”

Section: Performance Evaluationmentioning

confidence: 99%