On construction of a network log management system using ELK Stack with Ceph

Yang, Chao-Tung; Kristiani, Endah; Wang, Yuan-Ting; Min, Geyong; Lai, Ching-Han; Jiang, Wei-Je

doi:10.1007/s11227-019-02853-2

Cited by 12 publications

(8 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, in [23], Wang K et al proposed a payload-based intrusion detection method. On the contrary, Rafał Kozik et al used the flexibility of cloud-based architecture, as well as the latest advances in the field of large-scale machine learning, for shifting computationally more expensive and demanding operations [5], [24]. Going to the cloud to conduct traffic classification effectively using edge computing capacities, based on complex ELMs (extreme learning machine models) pre-built on the cloud, can decrease the overhead efficiency on edge devices.…”

Section: B Related Workmentioning

confidence: 99%

See 1 more Smart Citation

NetFlow Monitoring and Cyberattack Detection Using Deep Learning With Ceph

et al. 2020

Self Cite

View full text Add to dashboard Cite

Figuring the network's hidden abnormal behavior can reduce network vulnerability. This paper presents a detailed architecture in which the collected log data of the network can be processed and analyzed. We process and integrate on-campus network information from every router and store the integrated NetFlow log data. Ceph is used as an open-source distributed storage platform that offers high efficiency, high reliability, scalability, and preliminary preprocessing of raw data with Python, removing redundant areas and unification. In the subanalysis, we discover the anomaly event and absolute flow by three times of standard deviation rule. Keras has been used to classify in-time data collected via a cyberattack and to construct an automatic identifier template through the Recurring Neural Network (RNN) test. The identification accuracy of the optimization model is around 98% in attack detection. Finally, in the MySQL server, the results of the real-time evaluation can be obtained, and the results of the assessment can be displayed via ECharts.

show abstract

Section: B Related Workmentioning

confidence: 99%

“…The benefit of NetFlow is the lightweight and fastness of the entire data packet. Such features could be ideal for extraordinary detection in a crowded network environment [5].…”

Section: Introductionmentioning

confidence: 99%

NetFlow Monitoring and Cyberattack Detection Using Deep Learning With Ceph

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…During the past few years, some research has already been carried out on Ceph. Nonetheless, the existing research focuses attention on the application of Ceph [7] or the performance analysis of Ceph [8]. To the best of our knowledge, there was only some research concerned formal verification of Ceph.…”

Section: Introductionmentioning

confidence: 99%

Formalization and Analysis of Ceph Using Process Algebra

Zhu

Yin

2021

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

“…The logs can be stored in cloud systems for convenient management. With the management tools, it is allowed to collect, store, analyze, archive, and dispose of the log information [ 10 ]. Specific uses of the logs include device monitoring [ 11 ], user behavior analysis [ 12 ], or digital forensics [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

An Autonomous Log Storage Management Protocol with Blockchain Mechanism and Access Control for the Internet of Things

Hsu

Wei-xin

2020

Sensors

View full text Add to dashboard Cite

As the Internet of Things (IoT) has become prevalent, a massive number of logs produced by IoT devices are transmitted and processed every day. The logs should contain important contents and private information. Moreover, these logs may be used as evidences for forensic investigations when cyber security incidents occur. However, evidence legality and internal security issues in existing works were not properly addressed. This paper proposes an autonomous log storage management protocol with blockchain mechanism and access control for the IoT. Autonomous model allows sensors to encrypt their logs before sending it to gateway and server, so that the logs are not revealed to the public during communication process. Along with blockchain, we introduce the concept “signature chain”. The integration of blockchain and signature chain provides efficient management functions with valuable security properties for the logs, including robust identity verification, data integrity, non-repudiation, data tamper resistance, and the legality. Our work also employs attribute-based encryption to achieve fine-grained access control and data confidentiality. The results of security analysis using AVSIPA toolset, GNY logic and semantic proof indicate that the proposed protocol meets various security requirements. Providing good performance with elliptic curve small key size, short BLS signature, efficient signcryption method, and single sign-on solution, our work is suitable for the IoT.

show abstract

On construction of a network log management system using ELK Stack with Ceph

Cited by 12 publications

References 9 publications

NetFlow Monitoring and Cyberattack Detection Using Deep Learning With Ceph

NetFlow Monitoring and Cyberattack Detection Using Deep Learning With Ceph

Formalization and Analysis of Ceph Using Process Algebra

An Autonomous Log Storage Management Protocol with Blockchain Mechanism and Access Control for the Internet of Things

Contact Info

Product

Resources

About