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Found 6 papers, 0 papers with code
Communication Traffic Characteristics Reveal an IoT Devices Identity
In this paper, a supervised machine learning-based device fingerprinting (DFP) model has been proposed for identifying network-connected IoT devices using only communication traffic characteristics (or implicit identifiers).
A Hypergraph-Based Approach to Recommend Online Resources in a Library
This research analyzes a digital library's usage data to recommend items to its users, and it uses different clustering algorithms to design the recommender system.
Internet of Things: Digital Footprints Carry A Device Identity
In this paper, a device fingerprinting (DFP) model, which is able to distinguish between Internet of Things (IoT) and non-IoT devices, as well as uniquely identify individual devices, has been proposed.
Device identification using optimized digital footprints
In this paper, a device fingerprinting (DFP) method has been proposed for device identification, based on digital footprints, which devices use for communication over a network.
Item Recommendation Using User Feedback Data and Item Profile
Here, we have used the user's feedback data and content data to solve the content recommendation problem.
Network Traffic Analysis based IoT Device Identification
DFP identifies a device by using implicit identifiers, such as network traffic (or packets), radio signal, which a device used for its communication over the network.
