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RSDA 2019 : The 4th International Workshop on Reliability and Security Data Analysis


When Oct 28, 2019 - Oct 31, 2019
Where Berlin, GERMANY
Submission Deadline Jul 28, 2019
Notification Due Aug 25, 2019
Final Version Due Sep 8, 2019
Categories    machine learning   cybersecurity   relaibility   data engineering

Call For Papers

---------- The 4th International Workshop on Reliability and Security Data Analysis -----------
-------------------------------- RSDA 2019 ----------------------------------------

co-located with The 30th Annual IEEE International
Symposium on Software Reliability Engineering (ISSRE 2019)
BERLIN, GERMANY 28-31 Oct 2019

The workshop follows its past successful editions held at both ISSRE and DSN (RSDA 2016, RSDA 2014, RSDA 2013).
RSDA 2019 aims to concentrate ideas and contributions from academic and industrial organizations addressing reliability
and security of computer systems through data analysis.

RSDA aims to gather high-quality papers on data-driven methodologies, measurements from production systems,
and analysis of large datasets.

The papers accepted at RSDA 2019 will be included in the ISSRE Supplemental Proceedings as well as in the
ISSRE-W volume on IEEE Xplore.


Contact: Antonio Pecchia -

Workshop Co-chairs

Marcello Cinque, Università degli Studi di Napoli Federico II, ITALY
Almerindo Graziano, Silensec, UK
Dongseong Kim, The University of Queensland, AUS
Antonio Pecchia, Università degli Studi di Napoli Federico II, ITALY

Web Chair
Raffaele Della Corte, Università degli Studi di Napoli Federico II, ITALY


Computer systems are the basis for daily human activities and, more importantly, they play a key role in a variety of critical domains. Assessing dependability properties of computer systems is today an important concern for engineers and practitioners.

The analysis of textual/numeric data and log files produced under real workload conditions by applications, systems, and networks, intrusion detection systems, monitors and issue-trackers plays a key role for dependability assessment. Data analysis is crucial in a variety of engineering tasks, such as measuring availability and reliability of a system, characterizing failures, gaining insights into the progression of security attacks, designing mitigation means and countermeasures.

Academia and industry widely recognize the inherent potential of reliability and security data analysis for assessing dependability of computer systems and operational networks, and improving the engineering process. Data analysis in these specific areas poses many challenging research questions due to the heterogeneity, volume and velocity of the collected data, the lack of systematic end-to-end analysis procedures, the increasing diversity of analysis objectives and emerging application domains in critical areas.


Dependability and security measurement and modeling;
Dependability and security monitoring and control;
Analysis of attacks, defenses, and countermeasures;
Adversarial machine learining:
Security Information and Event Management (SIEM);
Data visualization;
Intrusion detection and prevention;
Denial-of-Service and botnet analysis, detection, and mitigation;
Application security status monitoring;
Behavior-based fraud and threat detection;
Insider threat and functional misuse detection;
Error/Failure detection and characterization;
Failure prediction and recovery techniques;
Failure data analysis and field studies;
Fault and intrusion tolerance;
Dependability and security forensics;
Generation of synthetic data sets for benchmarking dependability/security techniques;
Dependability and security analysis techniques for large datasets;
Dependability and security analysis of production systems.


Application dependability and security;
Distributed, parallel, clustered and grid systems;
Critical infrastructures protection;
Mobile systems and services;
Database and transactional systems;
Operating systems;
Web-based information systems.

Paper submission and other information: please refer to

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