Leveraging Blockchain for Device Registration and Authentication in tSIP-Based Phone-of-Things (PoT) Systems

Khalil, Haytham; Elgazzar, Khalid

doi:10.1109/iwcmc58020.2023.10183200

Cited by 2 publications

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

SIP-DDoS: SIP Framework for DDoS Intrusion Detection Based on Recurrent Neural Networks

Sbai,

Allaert,

Sondi

et al. 2024

Machine Learning for Networking

View full text Add to dashboard Cite

The rapid evolution of beyond fifth-generation (B5G) and sixth-generation (6G) networks has significantly driven the growth of Internet of Things (IoT) applications. These applications are characterised by: a massive connectivity, high security level, trust, wireless coverage, also ultra-low latency, high throughput, and ultra-reliability, especially for real-time oriented sessions or sensor like cameras. While traditional protocols like MQTT and CoAP are inadequate for such types of applications, under certain conditions, the 3GPP standard Session Initiation Protocol (SIP) emerges as a promising solution. However, SIP faces various Distributed Denial of Service (DDoS) threats, as INVITE flooding attacks presenting a significant challenge. This work presents a GRUbased Intrusion Detection System (IDS) to detect SIP-INVITE flooding attacks. Leveraging recurrent neural networks, the IDS efficiently process sequential SIP traffic data in real time, identifying attack patterns effectively. The GRU's ability to capture temporal dependencies enhances accuracy in classifying and detecting attack behaviors. The results demonstrate that the framework can effectively detect and mitigate INVITE flooding attacks of different intensities, under practical settings. The performance results show that the proposed framework is robust and can be practically deployed, e.g., inference time less than 800 µs and a marginal rate for the misclassified traffic.

show abstract

SIP-DDoS: SIP Framework for DDoS Intrusion Detection Based on Recurrent Neural Networks

Sbai,

Allaert,

Sondi

et al. 2024

Machine Learning for Networking

View full text Add to dashboard Cite

show abstract

The Resource Constrained IOT Systems of Blockchain in Optimal Deployment Mechanism

Taneja

2023

2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON)

View full text Add to dashboard Cite

Leveraging Blockchain for Device Registration and Authentication in tSIP-Based Phone-of-Things (PoT) Systems

Cited by 2 publications

References 12 publications

SIP-DDoS: SIP Framework for DDoS Intrusion Detection Based on Recurrent Neural Networks

SIP-DDoS: SIP Framework for DDoS Intrusion Detection Based on Recurrent Neural Networks

The Resource Constrained IOT Systems of Blockchain in Optimal Deployment Mechanism

Contact Info

Product

Resources

About