Context-adaptive blocking for protecting personal information exposed to social multimedia content

Author(s):  
Byeongtae Ahn ◽  
Seok-Woo Jang
2014 ◽  
Vol 19 (5) ◽  
pp. 694-715 ◽  
Author(s):  
George Panteras ◽  
Sarah Wise ◽  
Xu Lu ◽  
Arie Croitoru ◽  
Andrew Crooks ◽  
...  

Author(s):  
Patrick C. Shih ◽  
Kyungsik Han ◽  
John M. Carroll

AbstractSocial media has been widely adopted for assisting the efforts in emergency response and recovery, but it has been underutilized for emergency planning purposes. Emergency planning in a local community context must leverage accessible and free resources such as social media, because it is largely a volunteer enterprise. We describe our fieldwork with local annual festival emergency planning teams that led to the design of the Community Incident Report (CIR). CIR is a novel emergency planning system that externalizes community knowledge on persisting issues and common mitigation strategies by integrating police reports, local crisis information, and social multimedia content to foster citizens’ awareness of local emergency information and to assist emergency planners in planning for recurring and cyclical events. We provide a use case analysis of CIR and its evaluation with 20 local residents, and discuss how it could be extended to inform emergency planning for other community events and local municipalities that share similar characteristics.


2012 ◽  
Vol 9 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Won-Ik Park ◽  
Sanggil Kang ◽  
Young-Kuk Kim

With the development and diffusion of compact and portable mobile devices, users can use multimedia content such as music and movie on personal mobile devices, anytime and anywhere. However, even with the rapid development of mobile device technology, it is still not easy to search multimedia content or manage large volume of content in a mobile device with limited resources. To resolve these problems, an approach for recommending content on the server-side is one of the popular solutions. However, the recommendation in a server also leads to some problems like the scalability for a lot of users and the management of personal information. Therefore, this paper defines a personal content manager which acts between content providers (server) and mobile devices and proposes a method for recommending multimedia content in the personal content manager. For the recommendation based on user's personal characteristic and preference, this paper adopts and applies the DISC model which is verified in psychology field for classifying user's behavior pattern. The proposed recommendation method also includes an algorithm for reflecting dynamic environmental context. Through the implements and evaluation of a prototype system, this paper shows that the proposed method has acceptable performance for multimedia content recommendation.


2017 ◽  
Vol 44 (3) ◽  
pp. 298-313 ◽  
Author(s):  
Hyun-Ki Hong ◽  
Gun-Woo Kim ◽  
Dong-Ho Lee

The volumes of multimedia content and users have increased on social multimedia sites due to the prevalence of smart mobile devices and digital cameras. It is common for users to take pictures and upload them to image-sharing websites using their smartphones. However, the tag characteristics deteriorate the quality of tag-based image retrieval and decrease the reliability of social multimedia sites. In this article, we propose a semantic tag recommendation technique exploiting associated words that are semantically similar or related to each other using the interwiki links of Wikipedia. First, we generate a word relationship graph after extracting meaningful words from each article in Wikipedia. The candidate words are then rearranged according to importance by applying a link-based ranking algorithm and then the top-k words are defined as the associated words for the article. When a user uploads an image, we collect visually similar images from a social image database. After propagating the proper tags from the collected images, we recommend associated words related to the candidate tags. Our experimental results show that the proposed method can improve the accuracy by up to 14% compared with other works and that exploiting associated words makes it possible to perform semantic tag recommendation.


The mind setup of persons has been changed in today’s environment due to the easily available of internet and smart phone on very low-price cost. Smart phone and internet are two main resources which are being used by persons most of the time in his/her daily routine specially in lockdown due to COVID-19. In this lockdown, persons are doing some creative activity, making fun, etc and recording all his/her this personal information in the form of multimedia contents like text, images, audio and video. This created multimedia content is shared by persons frequently on globe through internet in the daily routine life and some other persons are watching this daily routine activity and making huge business with these data by sometimes with original content or sometimes with modified content without concerns/information/permission of the originator. In this process if everything is going in right way then no issues but if something going wrong then require legal issues and for this, we need to protect our data legally through some methodology. So this paper proposed secure watermarking technique for protecting multimedia content like images using Aadhar number and Discrete Cosine Transform (DCT) technique. In this proposed methodology individual can share the information’s with watermarked information which is hidden in shared images and on demand at the time of legal issue originator will show the actuality and its ownership. This paper explained details concepts of the embedding and reverse of embedding ( i.e. extracting) process for authentication of the images and its protection from the misuse or fraud. The experimental result of the proposed methodology is shown on different family photos shared on globe and found robust results.


Author(s):  
Georgios Lappas

In recent years there is a vast and rapidly growing amount of multimedia content available online. Web 2.0 and online social networks have dramatically influenced the growing amount of multimedia content due to the fact that users become more active producers and distributors of such multimedia context. This work conceptualizes and introduces the concept of social multimedia mining as a new emerging research area that combines web mining research, multimedia research and social media research. New challenges in multimedia research, social network analysis research as well as trends and opportunities in research areas of social and communication studies and more specific in politics, public relations, public administration, marketing and advertising are discussed in this chapter.


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