Towards learning and verifying invariants of cyber-physical systems by code mutation
Cyber-physical systems (CPS), which integrate algorithmic control with physical processes, often consist of physically distributed components communicating over a network. A malfunctioning or compromised component in such a CPS can lead to costly consequences, especially in the context of public inf...
Saved in:
Main Authors: | CHEN, Yuqi, POSKITT, Christopher M., SUN, Jun |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2016
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/4938 https://ink.library.smu.edu.sg/context/sis_research/article/5941/viewcontent/towards_learning.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Learning from mutants: Using code mutation to learn and monitor invariants of a cyber-physical system
by: CHEN, Yuqi, et al.
Published: (2018) -
Towards learning and verifying invariants of cyber-physical systems by code mutation
by: CHEN, Yuqi, et al.
Published: (2016) -
Learning fault models of cyber physical systems
by: KHOO, Teck Ping, et al.
Published: (2020) -
Learning from mutants: Using code mutation to learn and monitor invariants of a cyber-physical system
by: CHENG, Yuqi, et al.
Published: (2018) -
Anomaly detection for a water treatment system using unsupervised machine learning
by: INOUE, Jun, et al.
Published: (2017)