---------- The 5th International Workshop on Reliability and Security Data Analysis -----------
------------------------------------------ RSDA 2020 ------------------------------------------


co-located with The 31st Annual IEEE International
Symposium on Software Reliability Engineering (ISSRE 2020)
Virtual conference (initially planned to be held in Coimbra, Portugal)
12-15 Oct 2020


The workshop follows its past successful editions held at both ISSRE and DSN (RSDA 2019, RSDA 2016, RSDA 2014, RSDA 2013).
RSDA 2020 aims to concentrate ideas and contributions from academic and industrial organizations addressing reliability
and security of computer systems through data analysis.

The 5th RSDA Edition is co-located with the prestigious 31st Annual IEEE International Symposium on
Software Reliability Engineering (ISSRE 2020),
which will be a full virtual conference due to the worldwide situation
regarding COVID-19.

*** RSDA 2020 will be virtual!!! ***

ISSRE 2020, such as its workshops, will be a full virtual
conference. Authors of accepted workshop papers are expected to give
a remote talk, with no in-person attendance.

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 2020 will be included in the ISSRE Supplemental Proceedings as well as in the
ISSRE-W volume on IEEE Xplore.

Website: http://www.dessert.unina.it/RSDA2020/

Contact: Raffaele Della Corte - raffaele.dellacorte@critiware.com


Workshop Co-chairs

Raffaele Della Corte, Critiware, ITA
Christopher Gutierrez, Intel Labs, USA
Jin Hong, University of Western Australia, AUS
Marta Catillo, Università degli Studi del Sannio, ITA


SCOPE OF RSDA

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.


RSDA ADDRESSES, BUT IT IS NOT LIMITED TO, THE FOLLOWING RESEARCH ISSUES/TOPICS:

- Event logs and security-related data collection, processing and management;
- Monitoring and analysis of resource utilization metrics;
- Dependability and security monitoring, measurement and modeling;
- Anomaly detection;
- Analysis of attacks, defenses, and countermeasures;
- Adversarial machine learning:
- 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;
- Defect analysis and Software Reliability Growth Models (SRGM);
- Dependability and security forensics;
- Generation of synthetic data sets for benchmarking dependability/security techniques;
- Dependability and security analysis of large datasets and production systems;
- Machine Learning for security.


RELEVANT APPLICATION AREAS INCLUDE, BUT ARE NOT LIMITED TO:

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


Paper submission and other information: please refer to http://www.dessert.unina.it/RSDA2020/