DCIDS—Distributed Container IDS
نویسندگان
چکیده
Intrusion Detection Systems (IDS) still prevail as an important line of defense in modern computing environments. Cloud environment characteristics such resource sharing, extensive connectivity, and agility deploying new applications pose security risks that are increasingly exploited. New technologies like container platforms require IDS to evolve effectively detect intrusive activities these environments, advancements this regard necessary. In context, work proposes a framework for implementing focused on using machine learning techniques anomaly detection system calls. We contribute with the ability build dataset calls share it community; generation alerts open-source support SOC through analysis calls; possibility different algorithms approaches anomalies (such frequency, sequence, arguments among other type data) aiming greater efficiency; integrate tools, improving collaborative security. A five-layer architecture was built free tools tested corporate emulated GNS3 software version 2.2.29. experiment conducted public call dataset, possible validate operation integration layers, achieving results superior originated dataset.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2023
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app13169301