Web1 jan. 2024 · Device fingerprinting is a problem of identifying a network device using network traffic data to secure against cyber-attacks. Automated device classification from a large set of network... Web19 apr. 2024 · In this paper, we propose Device Authentication Code (DAC), a novel method for authenticating IoT devices with wireless interface by exploiting their radio frequency (RF) signatures. The proposed DAC is based on RF fingerprinting, information theoretic method, feature learning, and discriminatory power of deep learning.

Analysis of IoT Device Network Traffic: Thinking Toward Machine Learning

Web7 jul. 2024 · The experimental results confirmed that the proposed framework based on deep learning algorithms for an intrusion detection system can effectively detect real-world attacks and is capable of enhancing the security of the IoT environment. 1. Introduction Web1 okt. 2024 · Radio Frequency (RF) fingerprinting as a physical layer authentication method could be used to distinguish legitimate wireless devices from adversarial ones. In this paper, we present a wireless device identification platform to improve Internet of things (IoT) security using deep learning techniques. sahale snacks nutrition facts

Automated IoT Device Fingerprinting Through Encrypted Stream ...

WebThis study applied deep learning on network traffic to automatically identify connected IoT devices that are not on the white-list (unknown devices) and trained multiclass classifiers to detect unauthorized IoT devices connected to the network. The growing use of IoT devices in organizations has increased the number of attack vectors available to attackers due to … Web13 dec. 2024 · Leveraging these features, we have developed a deep learning based classification model for IoT device fingerprinting. Using a real-world IoT dataset, our evaluation results demonstrate that the proposed method can achieve \({\sim }99\%\) accuracy in IoT device-type identification based on single network flow classification. Web3 nov. 2024 · Data-based RF fingerprint identification uses deep learning algorithms, which can automatically train the raw data of the signal to identify mobile devices. Before 2024, the research of radio frequency fingerprint identification mainly focused on the use of machine learning algorithms, e.g., the support vector machines (SVM) algorithms are … thickened edge