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SafeSec

SafeSec

Michael Felderer (ORCID: 0000-0003-3818-4442)
  • Grant DOI 10.55776/I4701
  • Funding program Principal Investigator Projects International
  • Status ended
  • Start January 1, 2021
  • End June 30, 2024
  • Funding amount € 242,014
  • E-mail

DACH: Österreich - Deutschland - Schweiz

Disciplines

Computer Sciences (100%)

Keywords

    Safety Engineering, Self-Adaptive Systems, Security Engineering, Model-Based Software Engineering, Empirical Software Engineering

Abstract Final report

Modern cyber-physical systems, such as connected cars, connected factories in the 4.0 age industry or quadrocopter swarms are typically safety-critical systems that may harm their environment. They increasingly make decisions autonomously and, thus, adapt their behavior to changes in the system itself and the environment by performing self-adaptation. Due to the connectedness of these systems, security has become the key influence factor for their safety with the possibility of severe consequences for the health or even the life of affected people. Therefore, the integration of security aspects into modern safety analysis is a must in order to be able to employ the appropriate techniques to ensure that hazards are eliminated, reduced, or controlled. However, suitable approaches for integrated safety and security modeling and analysis are still rare. The project SafeSec: Integrated Safety and Security Model Generation and Analysis of Self- Adaptive Systems will overcome this issue and provides for the first time a combined safety and security engineering approach for self-adaptive systems. For that purpose, SafeSec develops a novel hazard analysis approach that integrates system and fault models with attack models. To enable this novel hazard analysis approach attacks to self-adaptive systems are systematically analyzed and a suitable attack modeling language is developed. Modeling security attacks is essential for the provided new hazard analysis approach, but requires specific knowledge and is time consuming. Therefore, SafeSec additionally contributes a novel approach to mine attack models based on the available system and fault models, system structure as well as additional empirical data sources like vulnerability databases or forums. The evaluation of SafeSec is based on a quadrocopter lab case as well as industrial aerospace and plant control systems.

Modern cyber-physical systems, such as connected cars, connected factories in the 4.0 age industry or quadrocopter swarms are typically safety-critical systems that may harm their environment. They increasingly make decisions autonomously and, thus, adapt their behavior to changes in the system itself and the environment by performing self-adaptation. Due to the connectedness of these systems, security has become the key influence factor for their safety with the possibility of severe consequences for the health or even the life of affected people. Therefore, the integration of security aspects into modern safety analysis is a must in order to be able to employ the appropriate techniques to ensure that hazards are eliminated, reduced, or controlled. However, suitable approaches for integrated safety and security modeling and analysis are still rare. The project "SafeSec: Integrated Safety and Security Model Generation and Analysis of Self-Adaptive Systems" will overcome this issue and provides for the first time a combined safety and security engineering approach for self-adaptive systems. For that purpose, SafeSec develops a novel hazard analysis approach that integrates system and fault models with attack models. To enable this novel hazard analysis approach attacks to self-adaptive systems are systematically analyzed and a suitable attack modeling language is developed. Modeling security attacks is essential for the provided new hazard analysis approach, but requires specific knowledge and is time consuming. Therefore, SafeSec additionally contributes a novel approach to mine attack models based on the available system and fault models, system structure as well as additional empirical data sources like vulnerability databases or forums. The evaluation of SafeSec is based on a quadrocopter lab case.

Research institution(s)
  • Universität Innsbruck - 100%
International project participants
  • Matthias Tichy, Universität Ulm - Germany

Research Output

  • 181 Citations
  • 27 Publications
  • 3 Datasets & models
  • 1 Software
Publications
  • 2023
    Title Guiding the retraining of convolutional neural networks against adversarial inputs
    DOI 10.60692/yg71h-w8v08
    Type Other
    Author Francisco Durán
    Link Publication
  • 2023
    Title Guiding the retraining of convolutional neural networks against adversarial inputs
    DOI 10.60692/djr3y-nd073
    Type Other
    Author Francisco Durán
    Link Publication
  • 2022
    Title Guiding the retraining of convolutional neural networks against adversarial inputs
    DOI 10.48550/arxiv.2207.03689
    Type Preprint
    Author López F
  • 2022
    Title Metamorphic Testing in Autonomous System Simulations
    DOI 10.48550/arxiv.2209.11031
    Type Preprint
    Author Adigun J
  • 2023
    Title A systematic review on security and safety of self-adaptive systems
    DOI 10.1016/j.jss.2023.111716
    Type Journal Article
    Author Pekaric I
    Journal Journal of Systems and Software
    Pages 111716
    Link Publication
  • 2023
    Title Model-Based Generation of Attack-Fault Trees
    DOI 10.48550/arxiv.2309.09941
    Type Preprint
    Author Groner R
  • 2023
    Title Towards Model Co-evolution Across Self-Adaptation Steps for Combined Safety and Security Analysis
    DOI 10.48550/arxiv.2309.09653
    Type Preprint
    Author Witte T
  • 2023
    Title VULNERLIZER: Cross-analysis Between Vulnerabilities and Software Libraries
    DOI 10.48550/arxiv.2309.09649
    Type Preprint
    Author Pekaric I
  • 2023
    Title Simulation of Sensor Spoofing Attacks on Unmanned Aerial Vehicles Using the Gazebo Simulator
    DOI 10.48550/arxiv.2309.09648
    Type Preprint
    Author Pekaric I
  • 2023
    Title Model-Based Generation of Attack-Fault Trees
    DOI 10.1007/978-3-031-40923-3_9
    Type Book Chapter
    Author Groner R
    Publisher Springer Nature
    Pages 107-120
  • 2023
    Title Risk-driven Online Testing and Test Case Diversity Analysis for ML-enabled Critical Systems
    DOI 10.1109/issre59848.2023.00017
    Type Conference Proceeding Abstract
    Author Adigun J
    Pages 344-354
    Link Publication
  • 2023
    Title Streamlining Attack Tree Generation: A Fragment-Based Approach
    DOI 10.48550/arxiv.2310.00654
    Type Preprint
    Author Pekaric I
  • 2023
    Title Guiding the retraining of convolutional neural networks against adversarial inputs
    DOI 10.7717/peerj-cs.1454
    Type Journal Article
    Author Durán F
    Journal PeerJ Computer Science
    Link Publication
  • 2024
    Title Towards Real-time Object Detection for Safety Analysis in an ML-Enabled System Simulation
    Type Journal Article
    Author Adigun J G
    Journal WiPiEC Journal-Works in Progress in Embedded Computing Journal
    Link Publication
  • 2024
    Title Streamlining Attack Tree Generation: A Fragment-Based Approach
    Type Conference Proceeding Abstract
    Author Frick M.
    Conference Hawaii International Conference on System Sciences (HICSS 2024)
    Pages 7447-7456
    Link Publication
  • 2022
    Title What is software quality for AI engineers?
    DOI 10.1145/3522664.3528599
    Type Conference Proceeding Abstract
    Author Golendukhina V
    Pages 1-9
    Link Publication
  • 2022
    Title Towards model co-evolution across self-adaptation steps for combined safety and security analysis
    DOI 10.1145/3524844.3528062
    Type Conference Proceeding Abstract
    Author Witte T
    Pages 106-112
    Link Publication
  • 2022
    Title Collaborative Artificial Intelligence Needs Stronger Assurances Driven by Risks
    DOI 10.1109/mc.2021.3131990
    Type Journal Article
    Author Adigun J
    Journal Computer
    Pages 52-63
    Link Publication
  • 2022
    Title What is Software Quality for AI Engineers? Towards a Thinning of the Fog
    DOI 10.48550/arxiv.2203.12697
    Type Preprint
    Author Golendukhina V
  • 2022
    Title Attack Model Mining for Security Assurance of Self-Adaptive Systems
    Type PhD Thesis
    Author Irdin Pekaric
  • 2022
    Title Metamorphic Testing in Autonomous System Simulations
    DOI 10.1109/seaa56994.2022.00059
    Type Conference Proceeding Abstract
    Author Adigun J
    Pages 330-337
    Link Publication
  • 2022
    Title Simulation of Sensor Spoofing Attacks on Unmanned Aerial Vehicles using the Gazebo Simulator
    DOI 10.1109/qrs-c57518.2022.00016
    Type Conference Proceeding Abstract
    Author Pekaric I
    Pages 44-53
    Link Publication
  • 2021
    Title Collaborative Artificial Intelligence Needs Stronger Assurances Driven by Risks
    DOI 10.48550/arxiv.2112.00740
    Type Preprint
    Author Adigun J
  • 2021
    Title Controlled Experimentation in Continuous Experimentation: Knowledge and Challenges
    DOI 10.48550/arxiv.2102.05310
    Type Preprint
    Author Auer F
  • 2021
    Title Controlled experimentation in continuous experimentation: Knowledge and challenges
    DOI 10.1016/j.infsof.2021.106551
    Type Journal Article
    Author Auer F
    Journal Information and Software Technology
    Pages 106551
    Link Publication
  • 2021
    Title VULNERLIZER: Cross-analysis Between Vulnerabilities and Software Libraries
    DOI 10.24251/hicss.2021.843
    Type Conference Proceeding Abstract
    Author Pekaric I
    Link Publication
  • 2021
    Title From monolithic systems to Microservices: An assessment framework
    DOI 10.1016/j.infsof.2021.106600
    Type Journal Article
    Author Auer F
    Journal Information and Software Technology
    Pages 106600
    Link Publication
Datasets & models
  • 2023 Link
    Title Risk-driven Online Testing and Test Case Diversity Analysis for ML-enabled Critical Systems (Replication Package)
    DOI 10.5281/zenodo.8152294
    Type Database/Collection of data
    Public Access
    Link Link
  • 2023 Link
    Title cais_rtod
    Type Computer model/algorithm
    Public Access
    Link Link
  • 2021 Link
    Title A Systematic Review on Security and Safety of Self-adaptive Systems (Supplementary Materials)
    DOI 10.5281/zenodo.5799781
    Type Database/Collection of data
    Public Access
    Link Link
Software
  • 2022 Link
    Title SafeSec Attack-Fault Tree Generation Toolchain
    Link Link

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