Adversarial machine learning attacks against intrusion detection systems: A survey on strategies and defense
Concerns about cybersecurity and attack methods have risen in the information age. Many
techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs) …
techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs) …
How to certify machine learning based safety-critical systems? A systematic literature review
Abstract Context Machine Learning (ML) has been at the heart of many innovations over the
past years. However, including it in so-called “safety-critical” systems such as automotive or …
past years. However, including it in so-called “safety-critical” systems such as automotive or …
Challenges of machine learning applied to safety-critical cyber-physical systems
A Pereira, C Thomas - Machine Learning and Knowledge Extraction, 2020 - mdpi.com
Machine Learning (ML) is increasingly applied for the control of safety-critical Cyber-
Physical Systems (CPS) in application areas that cannot easily be mastered with traditional …
Physical Systems (CPS) in application areas that cannot easily be mastered with traditional …
Real-time out-of-distribution detection in learning-enabled cyber-physical systems
Cyber-physical systems (CPS) greatly benefit by using machine learning components that
can handle the uncertainty and variability of the real-world. Typical components such as …
can handle the uncertainty and variability of the real-world. Typical components such as …
Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey
Machine learning has become widely adopted as a strategy for dealing with a variety of
cybersecurity issues, ranging from insider threat detection to intrusion and malware …
cybersecurity issues, ranging from insider threat detection to intrusion and malware …
Analysis of machine learning systems for cyber physical systems
A Rachmawati - International Transactions on Education …, 2022 - journal.pandawan.id
This study summarizes major literature reviews on machine learning systems for network
analysis and intrusion detection. Furthermore, it provides a brief lesson description of each …
analysis and intrusion detection. Furthermore, it provides a brief lesson description of each …
Uncertainty-aware prediction validator in deep learning models for cyber-physical system data
The use of Deep learning in Cyber-Physical Systems (CPSs) is gaining popularity due to its
ability to bring intelligence to CPS behaviors. However, both CPSs and deep learning have …
ability to bring intelligence to CPS behaviors. However, both CPSs and deep learning have …
Multilayered review of safety approaches for machine learning-based systems in the days of AI
The unprecedented advancement of artificial intelligence (AI) in recent years has altered our
perspectives on software engineering and systems engineering as a whole. Nowadays …
perspectives on software engineering and systems engineering as a whole. Nowadays …
Prid: Model inversion privacy attacks in hyperdimensional learning systems
Hyperdimensional Computing (HDC) is introduced as a promising solution for robust and
efficient learning on embedded devices with limited resources. Since HDC often runs in a …
efficient learning on embedded devices with limited resources. Since HDC often runs in a …
Statistical verification of cyber-physical systems using surrogate models and conformal inference
Uncertainty in safety-critical cyber-physical systems can be modeled using a finite number of
parameters or input signals. Given a system specification in Signal Temporal Logic (STL) …
parameters or input signals. Given a system specification in Signal Temporal Logic (STL) …