A Scheme for Generating a Dataset for Anomalous Activity Detection in IoT Networks

By I. Ullah, Qusay H. Mahmoud. Canadian Conference on AI, 2020

317 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/25cd96cc105927efa772f690426e955f080f72ff

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Rongxing Lu
2. Ali Akbar Ghorbani

In Computer Networks and Communications

1. Rongxing Lu
2. Ali Akbar Ghorbani
3. Nour Moustafa
4. Ansam Khraisat

In Signal Processing

1. Rongxing Lu
2. Ali Akbar Ghorbani

Citations in the corpus

• CICIoT2023: A Real-Time Dataset and Benchmark for Large-Scale Attacks in IoT Environment (2023, methodology): “IoTIDs (2020) [42] is proposed as a dataset composed of IoT-related flow-based features, selected and ranked by the correlation coefficients technique and the Shapiro–Wilk algorithm, respectively.”