Prediction-based secured handover authentication for mobile cloud computing

Khedr, Walid I.; Hosny, Khalid M.; Khashaba, Marwa M.; Amer, Fathy A.

doi:10.1007/s11276-020-02368-2

Cited by 7 publications

(2 citation statements)

References 43 publications

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“…These algorithms are further extended by the work in [12][13][14], wherein security-based models, fuzzy analytic hierarchy process, and secure handoff for mobile-based cloud deployments is proposed. These models assist in improving security during handoffs, thereby reducing attack probability, and increasing overall QoS of the heterogeneous network.…”

Section: Duementioning

confidence: 99%

NLADSS: Design of Connectivity as a Service (CaaS) Model using Node-Level Augmentation & Dynamic Sleep Scheduling for Heterogeneous Wireless Network Handoffs

2022

IJIES

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Seamless connectivity is need-of-the-hour for high-speed wireless networks. With the advent of 5th Generation (5G) wireless devices, users from different networks require inter-network connectivity with minimum packet drops, and maximum bit-rate. In order to perform this task, high efficiency handover models are proposed, which evaluate various network-level parameters including trust-levels, capacity, Quality of Service (QoS), etc. These algorithms also evaluate various node level metrics which include end-to-end delay, Received Signal Strength Indicator (RSSI), movement patterns, etc. in order to map the nodes to relevant networks. The drawback of proposed approaches is their inability to cater high-speed environments without causing QoS degradation. Moreover, most of these models do not consider node-level augmentations, which restricts their performance when applied to real-world scenarios. In order to remove these drawbacks and make the algorithms perform well with high speed environments without QoS degradation, we propose the design of a novel Connectivity as a Service (CaaS) model that uses Node-Level Augmentation & Dynamic Sleep Scheduling (NLADSS) for high efficiency heterogeneous wireless network handoffs. It was observed that the proposed algorithm is able to achieve a handoff efficiency of 98% for 5G heterogeneous networks, which outperforms most of the recently proposed models. The proposed model also aims at providing immutability, traceability, and high-performance distributed computing, while not compromising on QoS performance of the network.

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Section: Duementioning

confidence: 99%

NLADSS: Design of Connectivity as a Service (CaaS) Model using Node-Level Augmentation & Dynamic Sleep Scheduling for Heterogeneous Wireless Network Handoffs

2022

IJIES

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“…For example, the semantics of audio signal may change fundamentally after a simple rearrangement or removal of a few small segments, which cannot be detected only by human auditory perception. Audio authentication technology is an effective technical means to protect the integrity and authenticity of music, voice, and other audio data [3]. It can ensure that the received audio data in the transmission process, without malicious editing and tampering by a third party, that is, in the sense of human perception system and the original audio, is exactly the same.…”

Section: Introductionmentioning

confidence: 99%

Research on Music Multiterminal Audio Authentication Based on Wireless Network

2021

Wireless Communications and Mobile Computing

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The current music multiterminal audio authentication algorithm does not consider the mutation of music signal, which leads to poor tamper detection ability and long time of audio authentication. By analyzing the characteristics and key technologies of wireless network, a wireless multiterminal audio system is established. The short-term energy calculation method is used to consider the sudden change of music signal. The music signal is divided into note segments, and chroma features of half order notes are extracted. The robust hash value is calculated by nonuniform quantization method. The dynamic time warping algorithm is used to align the notes, and the Hamming distance between the hash values of each two corresponding notes is calculated to obtain the measurement values of error series, statistical characteristics, and time distribution characteristics. According to the measurement value, the fuzzy classification method is applied to calculate the membership degree of the signals belonging to two different types of operation, and the authentication confidence degree is obtained. The tampered area of the music signal that has not passed the authentication is detected, and the music multiterminal audio authentication is realized. Experimental results show that the proposed algorithm has good tamper detection ability and can effectively shorten the audio authentication time.

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Cloud Continuum in Vehicular Networks

2023

Cloud and Edge Networking

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Prediction-based secured handover authentication for mobile cloud computing

Cited by 7 publications

References 43 publications

NLADSS: Design of Connectivity as a Service (CaaS) Model using Node-Level Augmentation & Dynamic Sleep Scheduling for Heterogeneous Wireless Network Handoffs

NLADSS: Design of Connectivity as a Service (CaaS) Model using Node-Level Augmentation & Dynamic Sleep Scheduling for Heterogeneous Wireless Network Handoffs

Research on Music Multiterminal Audio Authentication Based on Wireless Network

Cloud Continuum in Vehicular Networks

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