Docker container security via heuristics-based multilateral security-conceptual and pragmatic study

Manu, A R; Patel, Jitendra Kumar; Akhtar, Shakil; Agrawal, Vinod Kumar; Murthy, K. N. Balasubramanya

doi:10.1109/iccpct.2016.7530217

Cited by 28 publications

(8 citation statements)

References 15 publications

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“…Manu et al, have provided unified security and privacy multilateral security architecture for cloud services stack, using key latest technology via LxC in general and Docker containers in specific to help assess the security design and architecture quality using multilateral security framework for Docker container. [9]. They have made a deep dive of the PAAS security and also try to analyze, compare and contrast the PAAS Docker container security, with other container technologies, and also with Virtual machine security with and without Hypervisor, and current security level of Dockers container [10].…”

Section: Security Problems In the Docker Literaturementioning

confidence: 99%

Securing Vulnerabilities in Docker Images

Efe¹,

Aslan²,

Kara³

2020

International Journal of Innovative Engineering Applications

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Review PaperDocker is an alternative application development and publishing infrastructure tool to various virtualization environments such as Virtual box and the like. The most popular containerization platform is Docker which is the area where Docker images are run. Container is a lightweight contrasting option to full machine virtualization that includes exemplifying an application in a container with its own working condition. These two concepts, virtualization and containerization are competing in the cloud-based environments. When virtualization became the mainstream, VM security concerns was common. IT Security experts are discussing the potential weaknesses of a virtualized environment for a long time. In this paper, focusing on Docker container, its vulnerabilities and possible measurements against security concerns, we have provided information about assessment of risks and vulnerabilities of containerization and the main differences between these two concepts via vulnerability analysis.

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Section: Security Problems In the Docker Literaturementioning

confidence: 99%

Securing Vulnerabilities in Docker Images

Efe¹,

Aslan²,

Kara³

2020

International Journal of Innovative Engineering Applications

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“…For network security, to enhance the container security provides the access control in terms of the communication level. Manu et al [25] design the balanced multilateral security prototype. The proposed architecture applied OSI/TCP/IP model to the cloud service structure.…”

Section: B Dockermentioning

confidence: 99%

“…There are some techniques that we can use to increase the container security, e.g. isolation or communication control [22], [24], [25]. In this paper, we focus on providing the scalable log data saving service for semiconductor testing.…”

Section: The Proposed Solution -Scalable Semiconductor Data Loggermentioning

confidence: 99%

An Implementation of Scalable High Throughput Data Platform for Logging Semiconductor Testing Results

2019

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Unlike graded data of common semiconductor test results storing in relational databases, log data in the standard test data format (STDF) contain millions of test data entries. In a semiconductor packaging and testing factory, a semiconductor wafer or integrated circuit tests generate thousands of STDF files each day; therefore, how to store these massive databases is a crucial topic. Different products correspond to different test items and STDF content; if a relational database is used to store all forms of data, the practical operation becomes challenging. This paper used a NoSQL document-oriented database collocated with a Docker container to build a system, named the scalable STDF data (SSD) framework, for storing semiconductor test data. According to semiconductor test operations, the SSD framework first converts STDF files into an open standard format for data transmission and subsequently transfers them to the database. The use of NoSQL databases allows for flexibility of specifications of STDF content, and a Docker container exhibits features such as rapid deployment and high scalability. The SSD framework meets the requirements of semiconductor testing for throughput, latency, and parallel experimental projects; possesses excellent execution efficiency; and provides flexible data storage services in a semiconductor testing environment where processing a large quantity of data is required. From our simulation results, the major performance of the proposed system depends on the hardware properties. The higher hardware distribution degree provides better performance. Docker container provides more connections and the scalability of storage, but higher software distribution contributes limited performance enhancement. INDEX TERMS Flexible data storage, scalable STDF data, semiconductor testing, standard test data format.

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“…a Docker container [9]). Through encapsulation, we achieve a high level of security [3,8]: 3D Apps cannot access the memory space and data of other apps. User isolation guarantees that a separate instance of the application will process each user's data, and after processing, will return the result and be destroyed.…”

Section: Hardware 3dprinterosmentioning

confidence: 99%

A Digital Ecosystem for Personal Manufacturing

Vedeshin

Dogru

Liiv

et al. 2019

Proceedings of the 11th International Conference on Management of Digital EcoSystems

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Recently, we have witnessed the advent of personal manufacturing, where home users, small, medium, and Fortune 500 enterprises use devices such as 3D printers, CNC mills, and robotics to manufacture products locally. We have been developing a digital ecosystem of personal manufacturing for the last seven years. This ecosystem is currently used or being tried by 111 Fortune 2000 enterprises. In this paper, we focus on the creation of the cloud-based manufacturing operating system, 3DPrinterOS, to address an evolving critical problem of personal manufacturing. We introduce a novel software ecosystem architecture to sustain a massive communication load of command, control, and telemetry data to and from millions of manufacturing machines and users. Our solution allows users to create and deploy their own applications into 3DPrinterOS cloud operating system. Our long term experiments show that over the last five years, 95, 000 users have generated over three million CAD designs and machine codes, and produced more than 1, 030, 000 physical parts on 32, 000 manufacturing machines in 100 countries. Short term experiments showed that, on average, it is five times faster to perform a 3D print using 3DPrinterOS. CCS CONCEPTS • Applied computing → Enterprise computing infrastructures; • Computer systems organization → Cloud computing; • General and reference → Experimentation; • Information systems → Enterprise applications.

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Docker container security via heuristics-based multilateral security-conceptual and pragmatic study

Cited by 28 publications

References 15 publications

Securing Vulnerabilities in Docker Images

Securing Vulnerabilities in Docker Images

An Implementation of Scalable High Throughput Data Platform for Logging Semiconductor Testing Results

A Digital Ecosystem for Personal Manufacturing

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