activity
20172019
most citedEvaluation of Machine Learning-based Anomaly Detection Algorithms on an Industrial Modbus/TCP Data Set

90 citations · 343 across the 25 of their papers we have counts for

collaborators

27 papers

cs.CR20191 cited

Anomaly-based Intrusion Detection in Industrial Data with SVM and Random Forests

Simon D. Duque Anton, Sapna Sinha, Hans Dieter Schotten

Attacks on industrial enterprises are increasing in number as well as in effect. Since the introduction of industrial control systems in the 1970's, industrial networks have been t…

eess.SP20194 cited

Methodologies of Link-Level Simulator and System-Level Simulator for C-V2X Communication

Wang Donglin, Raja R. Sattiraju, Qiu Anjie +2

At the time of the development, standardization, and further improvement are vital to the modern cellular systems such as the next generation wireless communication (5G). Simulatio…

cs.CR20196 cited

Using Temporal and Topological Features for Intrusion Detection in Operational Networks

Simon D. Duque Anton, Daniel Fraunholz, Hans Dieter Schotten

Until two decades ago, industrial networks were deemed secure due to physical separation from public networks. An abundance of successful attacks proved that assumption wrong. Intr…

cs.CR20192 cited

Putting Things in Context: Securing Industrial Authentication with Context Information

Simon Duque Anton, Daniel Fraunholz, Christoph Lipps +2

The development in the area of wireless communication, mobile and embedded computing leads to significant changes in the application of devices. Over the last years, embedded devic…

cs.CY20198 cited

Highly Scalable and Flexible Model for Effective Aggregation of Context-based Data in Generic IIoT Scenarios

Simon Duque Anton, Daniel Fraunholz, Janis Zemitis +2

Interconnectivity of production machines is a key feature of the Industrial Internet of Things (IIoT). This feature allows for many advantages in producing. Configuration and maint…

cs.CR201914 cited

Implementing SCADA Scenarios and Introducing Attacks to Obtain Training Data for Intrusion Detection Methods

Simon Duque Antón, Michael Gundall, Daniel Fraunholz +1

There are hardly any data sets publicly available that can be used to evaluate intrusion detection algorithms. The biggest threat for industrial applications arises from state-spon…