Vulnerability Assessment of the Rowhammer Attack Using Machine Learning and the gem5 Simulator - Work in Progress.
Loïc FranceMaria MushtaqFlorent BruguierDavid NovoPascal BenoitPublished in: SAT-CPS@CODASPY (2021)
Keyphrases
- machine learning
- attack graphs
- risk assessment
- attack graph
- data mining
- learning algorithm
- machine learning algorithms
- penetration testing
- active learning
- artificial intelligence
- machine learning methods
- inductive learning
- decision trees
- buffer overflow
- computational intelligence
- explanation based learning
- risk management
- feature selection
- simulation model
- security risks
- learning tasks
- countermeasures
- text classification
- supervised learning
- information extraction
- computer vision
- computer science
- pattern recognition
- knowledge base
- alert correlation
- denial of service
- attack detection
- neural network
- inductive logic programming
- learning problems
- statistical methods
- semi supervised learning
- knowledge acquisition
- natural language processing
- support vector machine
- data analysis