MoniLog: An Automated Log-Based Anomaly Detection System for Cloud Computing Infrastructures

Vervaet, Arthur

doi:10.1109/icde51399.2021.00317

Cited by 13 publications

(2 citation statements)

References 40 publications

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“…Vervaet et al [27] conducted a study on anomaly detection within the framework of cloud containers. This approach demonstrates the capability of detecting anomalies within a cloud container by employing network traffic analysis and accessing the kernel at a low level.…”

Section: Related Workmentioning

confidence: 99%

Toward a Conflict Resolution Protocol for Cloud Forensics Investigation

Alashjaee

2024

IEEE Access

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In cloud forensics, both the provider and consumer can independently collect evidence from cloud resources. Any inconsistencies between the forensic data supplied by the provider and that supplied by the client could lead to contentious situations requiring resolution between the involved parties. This work argues that by implementing appropriate mechanisms, it can adjudicate a significant proportion of these disputes electronically. In light of ongoing research into the design of such mechanisms, we propose a protocol that addresses the resolution of online disputes involving forensic evidence. To reconcile the two outputs, whenever possible, the peer-to-peer protocol considers the potential causes of the discrepancy between forensic data from the provider and the consumer. Consequently, disputes pertaining to cloud forensics often give rise to confrontations between the involved parties and have the potential to influence a court's decision. This raises a thought-provoking question regarding the indispensability of a mediation process. This work simulates disputes between providers and consumers by substituting an AI-powered conflict resolution system for a human arbitrator in the role of a mediator. This methodology is implemented in a case study. The participants in the case study demonstrated the efficacy of this protocol.

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Section: Related Workmentioning

confidence: 99%

Toward a Conflict Resolution Protocol for Cloud Forensics Investigation

Alashjaee

2024

IEEE Access

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“…Historic logs allow for investigation process of prior occurrences and provide system administrators with a way to track out the source of issues [3]. Furthermore, logs may aid in the recovery of a non-faulty state, the resetting of wrong transactions, the restoration of data, and the replication of circumstances that result in inaccurate conditions.…”

Section: Introductionmentioning

confidence: 99%

Investigating optimal features in log files for anomaly detection using optimization approach

Ranga,

Mohankumar

2024

IJ-AI

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<p><span lang="EN-US">Logs have been frequently utilised in different software system administration activities. The number of logs has risen dramatically due to the vast scope and complexity of current software systems. A lot of research has been done on log-based anomaly identification using machine learning approach. In this paper, we proposed an optimization approach to select the optimal features from the logs. This will provide the higher classification accuracy on reduced log files. In order to predict the anomalies three phases are used: i) log representation ii) feature selection and iii) Performance evaluation. The efficacy of the proposed model is evaluated using benchmark datasets such as BlueGene/L (BGL), Thunderbird, spirit and hadoop distributed file system (HDFS) in terms of accuracy, converging ability, train and test accuracy, receiver operating characteristic (ROC) measures, precision, recall and F1-score. The results shows that the feature selection on log files outperforms in terms all the evaluation measures.</span></p>

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TWLog: Task Workflow-Based Log Anomaly Detection

Zhang,

Fan,

et al. 2024

Lecture Notes in Computer Science

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MoniLog: An Automated Log-Based Anomaly Detection System for Cloud Computing Infrastructures

Cited by 13 publications

References 40 publications

Toward a Conflict Resolution Protocol for Cloud Forensics Investigation

Toward a Conflict Resolution Protocol for Cloud Forensics Investigation

Investigating optimal features in log files for anomaly detection using optimization approach

TWLog: Task Workflow-Based Log Anomaly Detection

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