Crowdsensing Multimedia Data: Security and Privacy Issues

2017 ◽  
Vol 24 (4) ◽  
pp. 58-66 ◽  
Author(s):  
Yan Li ◽  
Young-Sik Jeong ◽  
Byeong-Seok Shin ◽  
Jong Hyuk Park
Author(s):  
Amavey Tamunobarafiri ◽  
Shaun Aghili ◽  
Sergey Butakov

Cloud computing has been massively adopted in healthcare, where it attracts economic, operational, and functional advantages beneficial to insurance providers. However, according to Identity Theft Resource Centre, over twenty-five percent of data breaches in the US targeted healthcare. The HIPAA Journal reported an increase in healthcare data breaches in the US in 2016, exposing over 16 million health records. The growing incidents of cyberattacks in healthcare are compelling insurance providers to implement mitigating controls. Addressing data security and privacy issues before cloud adoption protects from monetary and reputation losses. This article provides an assessment tool for health insurance providers when adopting cloud vendor solutions. The final deliverable is a proposed framework derived from prominent cloud computing and governance sources, such as the Cloud Security Alliance, Cloud Control Matrix (CSA, CCM) v 3.0.1 and COBIT 5 Cloud Assurance.


2021 ◽  
Vol 1 (1) ◽  
pp. 47-58
Author(s):  
S. Benzegane ◽  
S. Sadoudi ◽  
M. Djeddou

In this paper, we present a software development of multimedia streaming encryption using Hyperchaos-based Random Number Generator (HRNG) implemented in C#. The software implements and uses the proposed HRNG to generate keystream for encrypting and decrypting real-time multimedia data. The used HRNG consists of Hyperchaos Lorenz system which produces four signal outputs taken as encryption keys. The generated keys are characterized by high quality randomness which is confirmed by passing standard NIST statistical tests. Security analysis of the proposed encryption scheme through image and audio security analysis confirms its robustness against different kind of attacks.


2020 ◽  
Vol 2020 ◽  
pp. 1-24
Author(s):  
Xiabing Zhou ◽  
Bin Li ◽  
Yanrong Qi ◽  
Wanying Dong

With the rapid development of the Internet, the security of network multimedia data has attracted increasingly more attention. The moving target defense (MTD) and cyber mimic defense (CMD) approaches provide a new way to solve this problem. To enhance the security of network multimedia data, this paper proposes a mimic encryption box for network multimedia data security. The mimic encryption box can directly access the network where the multimedia device is located, automatically complete the negotiation, provide safe and convenient encryption services, and effectively prevent network attacks. According to the principles of dynamization, diversification, and randomization, the mimic encryption box uses a reconfigurable encryption algorithm to encrypt network data and uses IP address hopping, port number hopping, protocol camouflage, and network channel change to increase the attack threshold. Second, the mimic encryption box has a built-in pseudorandom number generator and key management system, which can generate an initial random key and update the key with the hash value of the data packet to achieve “one packet, one key.” Finally, through the cooperation of the ARM and the FPGA, an access control list can be used to filter illegal data and monitor the working status of the system in real time. If an abnormality is found, the feedback reconstruction mechanism is used to “clean” the FPGA to make it work normally again. The experimental results and analysis show that the mimic encryption box designed in this paper has high network encryption performance and can effectively prevent data leakage. At the same time, it provides a mimic security defense mechanism at multiple levels, which can effectively resist a variety of network attacks and has high security.


2019 ◽  
Vol 2019 ◽  
pp. 1-2 ◽  
Author(s):  
Zhaoqing Pan ◽  
Ching-Nung Yang ◽  
Victor S. Sheng ◽  
Naixue Xiong ◽  
Weizhi Meng

Author(s):  
M. Govindarajan

Security and privacy issues are magnified by the volume, variety, and velocity of big data, such as large-scale cloud infrastructures, diversity of data sources and formats, the streaming nature of data acquisition and high volume inter-cloud migration. In the past, big data was limited to very large organizations such as governments and large enterprises that could afford to create and own the infrastructure necessary for hosting and mining large amounts of data. These infrastructures were typically proprietary and were isolated from general networks. Today, big data is cheaply and easily accessible to organizations large and small through public cloud infrastructure. The purpose of this chapter is to highlight the big data security and privacy challenges and also presents some solutions for these challenges, but it does not provide a definitive solution for the problem. It rather points to some directions and technologies that might contribute to solve some of the most relevant and challenging big data security and privacy issues.


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