Neuro-Symbolic Empowered Denoising Diffusion Probabilistic Models for Real-Time Anomaly Detection in Industry 4.0: Wild-and-Crazy-Idea Paper.
Luigi CapogrossoAlessio MascoliniFederico GirellaGeri SkenderiSebastiano GaiardelliNicola Dall'OraFrancesco PonzioEnrico FraccaroliSanta Di CataldoSara VincoEnrico MaciiFranco FummiMarco CristaniPublished in: FDL (2023)
Keyphrases
- anomaly detection
- denoising
- probabilistic model
- connectionist systems
- intrusion detection
- detecting anomalies
- anomalous behavior
- network traffic
- computer security
- graphical models
- network intrusion detection
- network anomaly detection
- intrusion detection system
- unsupervised anomaly detection
- data assimilation
- image denoising
- behavior analysis
- detect anomalies
- one class support vector machines
- neural network
- negative selection algorithm
- network security
- unsupervised learning
- detecting anomalous
- expectation maximization
- image processing
- cumulative sum
- data sets
- malware detection
- maximum likelihood
- text mining
- real world