Secure VOIP LTE network for secure transmission using PLRT (Packet Level Restraining Technique) under DDOS Attack

Shoket, Humma; Aulakh, Jagdeep Singh

doi:10.1109/spin.2018.8474211

Cited by 4 publications

(1 citation statement)

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“…The trust-based model is united with CUSUM, Tanimoto Distance, and Hellinger Distance to assess the expected rate of falsepositive and accuracy by applying it on mixed attack traffic [38]. Authors in [39] implemented VoIP Defender to track SIP traffic to prevent DDoS attacks. The architecture in question consists of a variety of assimilated techniques of detection and some techniques of attack reduction and prevention.…”

Section: Literature Reviewmentioning

confidence: 99%

Intrusion Detection and Prevention System for Secure Multimedia sharing in Future Internet

ASHRAF,

ULLAH,

TAHIRA

et al. 2024

Preprint

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IP Multimedia Subsystem (IMS) supports high-speed transmission of multi-media like data, audio, and video between mobiles and other wireless devices. IMS is the most suitable for multimedia communication across multiple networks using the Internet of Things (IoT) and cloud computing. IoT-IMS can efficiently manage the huge amount of data generated by smart devices for audio-video during live streaming applications. During these services, the main problem is that an intruder can launch a Session Initialization Protocol (SIP) messages flooding attack on IMS that does not have the functionality to prevent itself from these types of attacks. In this paper, an intrusion detecting and preventing system (IDPS) is proposed that eﬀectively detects the register flooding and spoofing attacks using SIP messages. We proposed a watermark embedding algorithm on the user side and an extraction algorithm on receiving side. A test-bed is set up for IMS where we have considered four different scenarios to evaluate the IDPS approach as compared to counterparts. Results illustrate the dominance of our scheme in terms of response time, register flooding attack detection ratios, CPU load utilization, fault detection ratio, and memory utilization. The fault detection ratio averagely 98.18

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Section: Literature Reviewmentioning

confidence: 99%