Vian Adnan Ferman

Al-Nahrain University · Electronic Computer Center

The proliferation of Internet of Things (IoT) markets in the last decade introduces new challenges for network traffic analysis, and processing packet flows to identify IoT devices. This type of device suffers from scarcity, making them vulnerable to spoofing operations. In such circumstances, the device can be recognized by identifying its fingerp...

The proliferation and diversity of Internet of things (IoT) devices increase IoT system risks. This open many challenging area for research like identifying authorized and unauthorized IoT devices, classifying events of devices, detecting network traffic anomalies generated by such devices, etc. To do so, machine and deep learning algorithms should...

The pervasive availability of the Internet of Things (IoT) markets lures targets for cyber-attacks since most manufactured IoT devices are usually resource-constrained devices. The first powerful line of IoT network protection from these vulnerabilities is detecting IoT devices especially the unauthorized ones by utilizing machine learning (ML) alg...

The dramatic growth of Internet of Things (IoT) devices in recent years increases the IoT networks’ vulnerabilities and introduces new challenges among machine learning (ML) algorithms to detect the networked devices. The creation of a Device Fingerprint (DFP) may depend on extracting the network traffic features related to the device except for t...

The dramatic growth of Internet of Things (IoT) devices in recent years increases the IoT networks’ vulnerabilities and introduces new challenges among machine learning (ML) algorithms to detect the networked devices. The creation of a Device Fingerprint (DFP) may depend on extracting the network traffic features related to the device except for th...