Data collected used for end-point security is expected to grow exponentially in the next decade thanks to evolution of Internet of Things (IoT) and the increasing migration to cloud computing platforms. Not only the volume of data is increasing, the data sources and data features are also becoming more diverse. To properly manage the volume and diversity of data, different but coherent strategies are needed to indicators of compromise in real-time that enable information security (InfoSec) professionals and system administrators to detect intrusion attempts or other malicious activities. Novel technologies integrating fast search engines, systems for data analysis, and security information and event management SIEM systems are enabling new capacities for producing meaningful intelligence with data captured in real-time. This promising approach also addresses the complex integrations between multiple services to provide an end-to-end implementation of pipelines required to collect and structure data from multiple distributed environments.
The RTCAC 2025 workshop focuses on exploring tools available in cloud-based data analytics systems and implementing techniques to address the collection, management, and analysis of data from distributed environments for cyber security event detection and threat forensics. Topics that may apply data driven systems for automating the detection of cyber security events include, but not limited to:
Data driven intelligence supported approaches and technologies
Data driven intelligence supported applications and systems
Quality of Service (QoS) and Quality of Experience (QoE) support
Data centers and cloud systems
Behavioral analysis of distributed systems
Network fault detection
Intrusion detection, intrusion prevention, and self-protection
Machine learning relevant topics
Cyber security relevant topics
Relevant analysis and modelling
Relevant surveys