Retrieving, analyzing, and processing large data can be challenging. An effective and
efficient mechanism for overcoming these challenges is to cluster the data into a compact …

Machine Learning's widespread application owes to its ability to develop accurate and
scalable models. In cyber-security, where labeled data is scarce, Semi-Supervised Learning …

Log files give insight into the state of a computer system and enable the detection of
anomalous events relevant to cyber security. However, automatically analyzing log data is …

Artificial Intelligence for IT operations (AIOps) aims to combine the power of AI with the big
data generated by IT Operations processes, particularly in cloud infrastructures, to provide …

Technological advances and increased interconnectivity have led to a higher risk of
previously unknown threats. Cyber Security therefore employs Intrusion Detection Systems …

Log lines consist of static parts that characterize their structure and enable assignment of
event types, and event parameters, ie, variable parts that provide specific information on …

Evaluations of intrusion detection systems (IDS) require log datasets collected in realistic
system environments. Existing testbeds therefore offer user simulations and attack scenarios …

Event logs are one of the most important sources of digital evidence for forensic
investigation because they record essential activities on the system. In this paper, we …

With the rapid development of the Industrial Internet of Things, log-based anomaly detection
has become vital for smart industrial construction that has prompted many researchers to …

The fog computing provides a platform for various time critical real-time applications. It
reduces the communication latency by placing computational resources to near to IoT …