TY - GEN
T1 - Towards secure edge-assisted image sharing for timely disaster situation awareness
AU - Yao, Jing
AU - Zheng, Yifeng
AU - Wang, Cong
AU - Nepal, Surya
N1 - Publisher Copyright:
Copyright © 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved
PY - 2020/7
Y1 - 2020/7
N2 - To save human lives and reduce injury and property loss in disasters, it is important to collect real-time situation awareness information such as the surroundings, road conditions, resource information, and more. Among others, images carry rich information and can easily provide a comprehensive view of the disaster situations. This is nowadays greatly facilitated with the prevalence of camera-embedded smartphones. However, high redundancy typically exists among the images gathered from different users during disasters. Given that bandwidth is dearer in disaster situations, it would be valuable to detect the image redundancy during transmission so that bandwidth allocation can be prioritized for unique images, enabling the timely delivery of useful information. In light of the above, in this position paper, we propose the design of an image sharing system architecture for timely disaster situation awareness. Our system architecture takes advantage of the emerging edge computing paradigm to perform image redundancy detection and prioritize the transmission of unique images, optimizing the amount of useful information delivered within a certain period of time. Meanwhile, to prevent images from being exposed to the intermediate edge infrastructure, our protocol is devised in a manner that the edge infrastructure can perform image redundancy detection without seeing the images in the clear.
AB - To save human lives and reduce injury and property loss in disasters, it is important to collect real-time situation awareness information such as the surroundings, road conditions, resource information, and more. Among others, images carry rich information and can easily provide a comprehensive view of the disaster situations. This is nowadays greatly facilitated with the prevalence of camera-embedded smartphones. However, high redundancy typically exists among the images gathered from different users during disasters. Given that bandwidth is dearer in disaster situations, it would be valuable to detect the image redundancy during transmission so that bandwidth allocation can be prioritized for unique images, enabling the timely delivery of useful information. In light of the above, in this position paper, we propose the design of an image sharing system architecture for timely disaster situation awareness. Our system architecture takes advantage of the emerging edge computing paradigm to perform image redundancy detection and prioritize the transmission of unique images, optimizing the amount of useful information delivered within a certain period of time. Meanwhile, to prevent images from being exposed to the intermediate edge infrastructure, our protocol is devised in a manner that the edge infrastructure can perform image redundancy detection without seeing the images in the clear.
KW - Data security
KW - Edge computing
KW - Image sharing
UR - https://www.scopus.com/pages/publications/85110912145
U2 - 10.5220/0009801602950301
DO - 10.5220/0009801602950301
M3 - Conference article published in proceeding or book
AN - SCOPUS:85110912145
T3 - ICETE 2020 - Proceedings of the 17th International Joint Conference on e-Business and Telecommunications
SP - 295
EP - 301
BT - ICETE 2020 - Proceedings of the 17th International Joint Conference on e-Business and Telecommunications
A2 - Callegari, Christian
A2 - Ng, Soon Xin
A2 - Sarigiannidis, Panagiotis
A2 - Battiato, Sebastiano
A2 - de Leon, Angel Serrano Sanchez
A2 - Ksentini, Adlen
A2 - Lorenz, Pascal
A2 - Obaidat, Mohammad
A2 - Obaidat, Mohammad
A2 - Obaidat, Mohammad
PB - SciTePress
T2 - 17th International Conference on Security and Cryptography, SECRYPT 2020 - Part of the 17th International Joint Conference on e-Business and Telecommunications, ICETE 2020
Y2 - 8 July 2020 through 10 July 2020
ER -