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Informer: irregular traffic detection for containerized microservices RPC in the real world

Published: 07 November 2019 Publication History

Abstract

Containerized microservices have been widely deployed in industry. Meanwhile, security issues also arise. Many security enhancement mechanisms for containerized microservices require predefined rules and policies. However, it is challenging when it comes to thousands of microservices and a massive amount of real-time unstructured data. Hence, automatic policy generation becomes indispensable. In this paper, we focus on the automatic solution for the security problem: irregular traffic detection for RPCs.
We propose Informer, which is a two-phase machine learning framework to track the traffic of each RPC and report anomalous points automatically. Firstly, we identify RPC chain patterns by density-based clustering techniques and build a graph for each critical pattern. Next, we solve the irregular RPC traffic detection problem as a prediction problem for time-series of attributed graphs by leveraging spatial-temporal graph convolution networks. Since the framework builds multiple models and makes individual predictions for each RPC chain pattern, it can be efficiently updated upon legitimate changes in any of the graphs.
In evaluations, we applied Informer to a dataset containing more than 7 billion lines of raw RPC logs sampled from an large Kubernetes system for two weeks. We provide two case studies of detected real-world threats. As a result, our framework found fine-grained RPC chain patterns and accurately captured the anomalies in a dynamic and complicated microservice production scenario, which demonstrates the effectiveness of Informer.

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Published In

cover image ACM Conferences
SEC '19: Proceedings of the 4th ACM/IEEE Symposium on Edge Computing
November 2019
455 pages
ISBN:9781450367332
DOI:10.1145/3318216
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • IEEE-CS\DATC: IEEE Computer Society

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 November 2019

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Author Tags

  1. GCN
  2. RPC
  3. anomaly detection
  4. containers
  5. microservices

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  • Research-article

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SEC '19
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SEC '19: The Fourth ACM/IEEE Symposium on Edge Computing
November 7 - 9, 2019
Virginia, Arlington

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SEC '19 Paper Acceptance Rate 20 of 59 submissions, 34%;
Overall Acceptance Rate 40 of 100 submissions, 40%

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  • (2023)Log2Policy: An Approach to Generate Fine-Grained Access Control Rules for Microservices from ScratchProceedings of the 39th Annual Computer Security Applications Conference10.1145/3627106.3627137(229-240)Online publication date: 4-Dec-2023
  • (2023)SoKComputers and Security10.1016/j.cose.2023.103119127:COnline publication date: 1-Apr-2023
  • (2021)Securing microservices and microservice architecturesComputer Science Review10.1016/j.cosrev.2021.10041541:COnline publication date: 1-Aug-2021
  • (2021)ThunQ: A Distributed and Deep Authorization Middleware for Early and Lazy Policy Enforcement in Microservice ApplicationsService-Oriented Computing10.1007/978-3-030-91431-8_13(204-220)Online publication date: 18-Nov-2021

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