Detecting bad information in mobile wireless networks based on the wireless application protocol

Zhang, Weizhe; You, Zai-Jin; Kim, Tai-hoon

doi:10.1007/s00607-013-0325-1

Cited by 10 publications

(5 citation statements)

References 11 publications

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“…Smartphones are now commonly used to record video with HD quality and have Internet access for sharing on the social clouds such as Facebook, Twitter, Tumblr, and Google Plus [1]. Users upload and share HD videos on social clouds but social clouds compress video files for fast loading of the web page, save storage because of a large amount of video data, and provide QoS delivery of video streaming over low-bandwidth networks [2][3][4]. The purpose of video compression is efficiently reducing visual data by avoiding the loss of visual quality due to compression [5].…”

Section: Introductionmentioning

confidence: 99%

Quality of Experience Assessment of Video Quality in Social Clouds

Laghari

Karim

et al. 2017

Wireless Communications and Mobile Computing

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Video sharing on social clouds is popular among the users around the world. High-Definition (HD) videos have big file size so the storing in cloud storage and streaming of videos with high quality from cloud to the client are a big problem for service providers. Social clouds compress the videos to save storage and stream over slow networks to provide quality of service (QoS). Compression of video decreases the quality compared to original video and parameters are changed during the online play as well as after download. Degradation of video quality due to compression decreases the quality of experience (QoE) level of end users. To assess the QoE of video compression, we conducted subjective (QoE) experiments by uploading, sharing, and playing videos from social clouds. Three popular social clouds, Facebook, Tumblr, and Twitter, were selected to upload and play videos online for users. The QoE was recorded by using questionnaire given to users to provide their experience about the video quality they perceive. Results show that Facebook and Twitter compressed HD videos more as compared to other clouds. However, Facebook gives a better quality of compressed videos compared to Twitter. Therefore, users assigned low ratings for Twitter for online video quality compared to Tumblr that provided high-quality online play of videos with less compression.

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Section: Introductionmentioning

confidence: 99%

Quality of Experience Assessment of Video Quality in Social Clouds

Laghari

Karim

et al. 2017

Wireless Communications and Mobile Computing

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“…In the future work, we plan to add the fuzzy sets during the test generation process, which can better simulate the actions of intruder of a network system. Some real network protocols, such as RADIUS and the protocol used in [ 26 ], are going to be considered. And the more complex experiments [ 27 ] are going to be defined.…”

Section: Discussionmentioning

confidence: 99%

A Model Based Security Testing Method for Protocol Implementation

Fu¹,

Xin

2014

The Scientific World Journal

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The security of protocol implementation is important and hard to be verified. Since the penetration testing is usually based on the experience of the security tester and the specific protocol specifications, a formal and automatic verification method is always required. In this paper, we propose an extended model of IOLTS to describe the legal roles and intruders of security protocol implementations, and then combine them together to generate the suitable test cases to verify the security of protocol implementation.

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“…However, because of broadcast nature of wireless communication, dynamic topology, mobility, signal channel instability, and so forth [1], they are also vulnerable to various security threats and attacks such as DoS (Denial of Service), counterfeiting, tampering, leakage, interference, network flooding, eavesdropping, and traffic analysis [2]. Particularly, with the popularity of intelligent terminals, some bad information, such as obscenity information, viruses, and Trojans, becomes more and more widespread [3]. This bad information not only occupies lots of user's traffic, but also endangers the privacy of users.…”

Section: Introductionmentioning

confidence: 99%

Information Security of PHY Layer in Wireless Networks

Fang

Sun

et al. 2016

Journal of Sensors

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Since the characteristics of wireless channel are open and broadcasting, wireless networks are very vulnerable to be attacked via eavesdropping, jamming, and interference. As traditional secure technologies are not suitable for PHY layer of wireless networks, physical-layer security issues become a focus of attention. In this paper, we firstly identify and summarize the threats and vulnerabilities in PHY layer of wireless networks. Then, we give a holistic overview of PHY layer secure schemes, which are divided into three categories: spatial domain-based, time domain-based, and frequency domain-based. Along the way, we analyze the pros and cons of current secure technologies in each category. In addition, we also conclude the techniques and methods used in these categories and point out the open research issues and directions in this area.

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Detecting bad information in mobile wireless networks based on the wireless application protocol

Cited by 10 publications

References 11 publications

Quality of Experience Assessment of Video Quality in Social Clouds

Quality of Experience Assessment of Video Quality in Social Clouds

A Model Based Security Testing Method for Protocol Implementation

Information Security of PHY Layer in Wireless Networks

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