Voice Over Internet Protocol: Vulnerabilities and Assessments

Khan, Hafiz Muhammad Ashja; Inayat, Usman; Zia, Muhammad Fahad; Ali, Fahad; Jabeen, T. Nusrat; Ali, Syed Moshin

doi:10.1109/icic53490.2021.9692955

Cited by 7 publications

(3 citation statements)

References 26 publications

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“…It requires only a minimal amount of communication mechanism to be carried out. It is commonly believed that UDP is an unstable transport protocol; however, it makes use of IP services, which provide a best effort delivery method [1]. In UDP, the receiver is not required to produce an acknowledgement of the packet that it has received, and the sender is not required to wait for any acknowledgement of the packet that it has delivered.…”

Section: User Datagram Protocol (Udp)mentioning

confidence: 99%

“…VoIP benefits service providers by opening up a new, lucrative revenue stream for them. VoIP offers consumers a glimpse into the future of communication by enabling low-cost, faster, more reliable, and secure connections for conversations across long distances or on tiny networks like local area networks or wide area networks [1]. In order to determine the effectiveness of packet switching communication network services, Quality of Service (QoS) criteria are deemed insufficient [2].…”

Section: Introductionmentioning

confidence: 99%

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QUALITY OF EXPERIENCE FOR VOICE OVER INTERNET PROTOCOL (VoIP)

Ali Jaish,

Al-Shammari

2023

ejuow

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Today, the service of Voice over Internet Protocol or (VoIP) is one of the most used service around the globe in many fields, especially with video conferencing applications. Different applications and also many communications companies around the world use the VoIP service. Communication stakeholders aim to keep old customers happy and attract new customers. There was a need for some kind of service quality measures. Metrics are used to quantify the quality of transmission link are known Quality of Service (QoS). Whereas, user satisfaction level is identified by using Quality of Experience (QoE). This paper conducted a simulation model for VoIP service over heterogeneous, using OPNET modeler. This work aims to compare the user satisfaction level of the VoIP service by using different coding schemes in the application level of the User Equipment (UE). The measured QoS parameters over the heterogeneous transmission link were IP packet delay, IP Packet jitter, IP packet loss, MAC layer delay, PHY layer throughput in the network. Additionally, in this simulation model the use of E-Model to assess QoE level using Mean Opinion Score (MOS) metric in predicting the VoIP call quality. The results using the vocoder G.729A during the (30) sec of the voice call simulation time were as follows: Delay 0.57 mSec, Throughput of 290 Kbits/sec, Jitter of 0.02 uSec, MOS value of 3.76. The results using the vocoder G.711 during the same aforementioned time were as follows: Delay 0.25 mSec, Throughput of 70 Kbits/sec, Jitter of 0 Sec), MOS value of 3.08.

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Section: User Datagram Protocol (Udp)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

QUALITY OF EXPERIENCE FOR VOICE OVER INTERNET PROTOCOL (VoIP)

Ali Jaish,

Al-Shammari

2023

ejuow

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“…Everything is connected to the Internet, such as smart sensors, fitness mobile applications, thermostats, PV systems, air conditioners, and cooking appliances [10,11]. This rapid development in IoT technology is making it harder to secure and protect IoT data from attackers, hackers, unauthorized users, and malicious traffic [12][13][14]. Therefore, multiple defense mechanisms and strategies are being developed and implemented in IoT systems and frameworks to protect information.…”

Section: Iot Security and Datasetsmentioning

confidence: 99%

Learning-Based Methods for Cyber Attacks Detection in IoT Systems: A Survey on Methods, Analysis, and Future Prospects

et al. 2022

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Internet of Things (IoT) is a developing technology that provides the simplicity and benefits of exchanging data with other devices using the cloud or wireless networks. However, the changes and developments in the IoT environment are making IoT systems susceptible to cyber attacks which could possibly lead to malicious intrusions. The impacts of these intrusions could lead to physical and economical damages. This article primarily focuses on the IoT system/framework, the IoT, learning-based methods, and the difficulties faced by the IoT devices or systems after the occurrence of an attack. Learning-based methods are reviewed using different types of cyber attacks, such as denial-of-service (DoS), distributed denial-of-service (DDoS), probing, user-to-root (U2R), remote-to-local (R2L), botnet attack, spoofing, and man-in-the-middle (MITM) attacks. For learning-based methods, both machine and deep learning methods are presented and analyzed in relation to the detection of cyber attacks in IoT systems. A comprehensive list of publications to date in the literature is integrated to present a complete picture of various developments in this area. Finally, future research directions are also provided in the paper.

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Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks

Liyakat

2023

Lecture Notes in Networks and Systems

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Voice Over Internet Protocol: Vulnerabilities and Assessments

Cited by 7 publications

References 26 publications

QUALITY OF EXPERIENCE FOR VOICE OVER INTERNET PROTOCOL (VoIP)

QUALITY OF EXPERIENCE FOR VOICE OVER INTERNET PROTOCOL (VoIP)

Learning-Based Methods for Cyber Attacks Detection in IoT Systems: A Survey on Methods, Analysis, and Future Prospects

Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks

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