102 citations · 216 across the 20 of their papers we have counts for
4 papers · 1 filter
DeepAlign: Alignment-based Process Anomaly Correction using Recurrent Neural Networks
Timo Nolle, Alexander Seeliger, Nils Thoma +1
In this paper, we propose DeepAlign, a novel approach to multi-perspective process anomaly correction, based on recurrent neural networks and bidirectional beam search. At the core…
TRIDEnT: Building Decentralized Incentives for Collaborative Security
Nikolaos Alexopoulos, Emmanouil Vasilomanolakis, Stephane Le Roux +2
Sophisticated mass attacks, especially when exploiting zero-day vulnerabilities, have the potential to cause destructive damage to organizations and critical infrastructure. To tim…
On generating network traffic datasets with synthetic attacks for intrusion detection
Carlos Garcia Cordero, Emmanouil Vasilomanolakis, Aidmar Wainakh +2
Most research in the area of intrusion detection requires datasets to develop, evaluate or compare systems in one way or another. In this field, however, finding suitable datasets…
BINet: Multi-perspective Business Process Anomaly Classification
Timo Nolle, Stefan Luettgen, Alexander Seeliger +1
In this paper, we introduce BINet, a neural network architecture for real-time multi-perspective anomaly detection in business process event logs. BINet is designed to handle both…