Privacy-preserving distributed data fusion is a pretreatment process in data mining involving security models. In this paper, we present a method of implementing multiparty data fusion, wherein redundant attributes of a same set of individuals are stored by multiple parties. In particular, the merged data does not suffer from background attacks or ...
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Wireless sensor networks (WSN) are integral part of Industrial Internet of Things (IIOT), the said networks comprise of elements possessing low power processors. WSNs are used for gathering data in the monitoring region, using which vital information about the sensor and the monitoring region can be attained (placement of the sensor node is critica...
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In today’s world, most of the people utilize Online Social Networks (OSN) to mingle with people of their interest. Various new and innovative photo sharing features attract many users and kindle them to post several photos. The user has the privilege of posting any photo on his/her profile and share it with a range of people. Unfortunately, it may ...
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Privacy-preserving distributed data fusion is a pretreatment process in data mining involving security models. In this paper, we present a method of implementing multiparty data fusion, wherein redundant attributes of a same set of individuals are stored by multiple parties. In particular, the merged data does not suffer from background attacks...
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Wireless sensor networks (WSN) allow to exchange information and to take immediate and remote actions in natural, industrial, military or domestic environment systems. These networks are vulnerable to cyber-attacks, hence, they are vulnerable to being intercepted, interrupted or modified. However, for the last twenty years, the amount of informatio...
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With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of urbanization. IoT networks allow distributed smart devices to collect and process data within smart city infrastructure using an open channel, the Internet. Thus, challenges such as centralization, security, privacy (e.g., performing data poisoning and in...
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The Internet of things (IoT) has certainly become one of the hottest technology frameworks of the year. It is deep in many industries, affecting people's lives in all directions. The rapid development of the IoT technology accelerates the process of the era of ``Internet of everything'' but also changes the role of terminal equipment at the edge of...
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Edge computing, as a new computing paradigm that extends cloud computing, allows a service vendor to deploy its services on distributed edge servers to serve its service users in close geographic proximity to those edge servers. Caching edge data on edge servers can minimize service users data retrieval latency. However, such edge data are subject ...
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Attribute-based authentication is considered a cornerstone component to achieve scalable fine-grained access control in the fast growing market of cloud-based services. Unfortunately, it also poses a privacy concern. Users attributes should not be linked to the users identity and spread across different organizations. To tackle this issue, several ...
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In the edge computing environment, app vendors can cache their data on a large number of geographically distributed edge servers to serve their users. However, those cached data are particularly vulnerable to both intentional and accidental corruption, which makes data security a major concern in the EC environment. Given limited computing resource...
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Searchable encryption (SE) is a powerful technology that enables keyword-based search over encrypted data becomes possible. However, most SE schemes focus on exact keyword search which can not tolerate misspellings and typos. Existing fuzzy keyword search schemes only support fuzzy search within a limited similarity threshold d, the storage cost wi...
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The population of cloud computing greatly facilitates the sharing of explosively generated image today. While benefiting from the convenient of cloud, the privacy protection mechanism that commonly applied in cloud service makes the spreading of illegal and harmful data very hard to be detected or controlled. Such a realistic threat should be serio...
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Federated learning (FL) is a machine-learning setting, where multiple clients collaboratively train a model under the coordination of a central server. The clients' raw data are locally stored, and each client only uploads the trained weight to the server, which can mitigate the privacy risks from the centralized machine learning. However, most of ...
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In medical field, previous patients' cases are extremely private as well as intensely valuable to current disease diagnosis. Therefore, how to make full use of precious cases while not leaking out patients' privacy is a leading and promising work especially in future privacy-preserving intelligent medical period. In this paper, we investigate how t...
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Driving behaviors are highly relevant to automotive statuses and on-board safety, which offer compelling shreds of evidence for mobility as a service (MaaS) providers to develop personalized rental prices and insurance products. However, the direct dissemination of driving behaviors may lead to violations of identity and location privacy. In this p...
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As 5G and mobile computing are growing rapidly, deep learning services in the Social Computing and Social Internet of Things (IoT) have enriched our lives over the past few years. Mobile devices and IoT devices with computing capabilities can join social computing anytime and anywhere. Federated learning allows for the full use of decentralized tra...
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With the booming of smart grid, The ubiquitously deployed smart meters constitutes an energy internet of things. This paper develops a novel blockchain-based transactive energy management system for IoT-aided smart homes. We consider a holistic set of options for smart homes to participate in transactive energy. Smart homes can interact with the gr...
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With the rapid development of bioinformatics and the availability of genetic sequencing technologies, genomic data has been used to facilitate personalized medicine. Cloud computing, features as low cost, rich storage and rapid processing can precisely respond to the challenges brought by the emergence of massive genomic data. Considering the secur...
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With the development of cloud computing, the great amount of storage data requires safe and efficient data sharing. In multiparty storage data sharing, first, the confidentiality of shared data is ensured to achieve data privacy preservation. Second, the security of stored data is ensured. That is, when stored shared data are subject to frequent ac...
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With the wide deployment of public clouds, owners of big graphs want to use the cloud to handle the scalability issues. However, the privacy and ownership of the graphs in the cloud has become a major concern. In this paper, we study privacy-preserving algorithms for graph spectral analysis of outsourced encrypted graph in the cloud. We consider a ...
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In this era of rapid growth of vehicles, the ratio of road accident increases day by day. Nowadays, Traffic incidents are persistent problems in both developed and developing countries which result in huge loss of life and property. No one in this world is ready to gaze what’s happening around them. Nobody cares even when an accident occurs. This ...
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With the rapid advances of wireless technologies and popularization of smart mobile devices, edge-enabled mobile social networks (MSNs) have emerged as a promising network paradigm for mobile users to deliver, share, and exchange contents with each other. By leveraging edge caching technology, various content services can be provided to mobile user...
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In this digital world, transferring sensitive data electronically has become inevitable. The objective of this work is to hide and retrieve confidential information in image mosaics. The photo mosaic approach has been used for the creation of the mosaic and the least significant bit (LSB) technique has been adopted for the embedding of the hidden i...
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