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Attribute based encryption(ABE) is an efficient technique that exploits attributes and access policies to achieve fine-grained access control in cloud computing. Besides, outspread ABE schemes with multiple authorities(multi-authority ABE) are more suitable for practical applications than basic single-authority ABE schemes. Nevertheless, existing multi-authority ABE schemes either can't preserve access...
Location Based Service (LBS) is gaining popularity. As one fundamental LBS service, range search returns all Point of Interests (POIs) within a user-specified range. However, people also leave their location privacy at risks when using range search. How to provide a high-quality range search service while protecting users' location privacy is a challenging problem. Most existing approaches use space-filling...
Recent large-scale deployments of differentially private algorithms employ the local model for privacy (sometimes called PRAM or randomized response), where data are randomized on each individual's device before being sent to a server that computes approximate, aggregate statistics. The server need not be trusted for privacy, leaving data control in users' hands. For an important class of convex optimization...
In cloud infrastructure, garage of files is rapidly gaining popularity throughout the world. If an individual's sensitive information is stored in a remote storage location without encryption, an attacker can access these data without consent of data owner. This study addresses this trouble through offering a secured, effective & faster statistics data search in cloud through RSBS and trapdoors...
Push notification services provide reliable, energy efficient, store-and-forward messaging between servers and clients. This mode of communication is widely used, and sufficiently compelling for mobile devices that push notification services are integrated into operating systems. Unfortunately, push notification services today allow the service provider to practice censorship, surveillance, and location...
Despite many applications, mobile cloud computinginduces privacy concerns. In particular, when mobile device usersoffload the computation of a mobile app to the cloud, they may notwant the cloud service provider (CSP) to know what kind of appthey are using, since that information might be used to infer theirpersonal activities and living habits. One possible way for the CSPto learn the type of an...
This investigation proposes a methodology with a practical approach for privacy vulnerability analysis on Android Applications. The methodology combines the controls of the OWASP Mobile Security Project [1], Open Android Security Assessment Methodology [2], and good practices from the current state of the art. The proposed assessment is composed of the following stages: collection of information,...
Personal information is often gathered and processed in a decentralized fashion. Examples include health records and governmental data bases. To protect the privacy of individuals, no unique user identifier should be used across the different databases. At the same time, the utility of the distributed information needs to be preserved which requires that it be nevertheless possible to link different...
Thanks to their crucial role in different areas such as supply chain and healthcare, Radio Frequency Identification (RFID) technologies have currently attracted a lot of attention. They are mainly used for identifying objects and people based on a combination of tags and readers. Nevertheless, this identification brings out many challenges and concerns including security which still remains an open...
Mobile cloud computing (MCC) is a platform that allows mobile users to offload the computationally rigorous and storage demanding tasks on available cloud resources using wireless access. The major concern with MCC is the privacy of data. Mobile users give confidential information through the network, that if not safeguarded may lead to security issues. Identity Management (IDM) is the management...
With the rapid development of mobile Internet and locating technology, location-based services (LBS) are widely used in mobile social networks, while the user obtained the LBS services, their location information is also provided to the service provider, this information may be obtained by the attacker and the user's other personal privacy may be inferred, threatening to the user's personal information...
A location-based service (LBS) is a software level service that are offered through mobile device based on users' location, that means the user location is known to the service and data provider who may be an external third-party location service (LCS) client. To achieve a good quality of service and good system performance, the system needs to preserve the user's privacy with a quick response and...
This paper presents a strategy for enabling speech recognition to be performed in the cloud whilst preserving the privacy of users. The approach advocates a demarcation of responsibilities between the client and server-side components for performing the speech recognition task. On the client-side resides the acoustic model, which symbolically encodes the audio and encrypts the data before uploading...
When user-generated data such as audio and video signals are used to train machine learning algorithms, users' privacy must be considered before the learned model is released. In this work, we present an open-source library for privacy-preserving machine learning framework on smart devices. The library allows Android and iOS devices to collectively learn a common classifier/regression model from distributed...
Opportunistic Network (OppNet) is an emerging communication paradigm, by which nodes inside forward messages through personal contact opportunities. Recently, numerous studies have focused on predicting nodes meeting to promote routing efficiency and reduce transmission delay. However, individual privacy would likely be revealed to strangers or attackers during the execution of prediction. In this...
Recently perceived vulnerabilities in public key infrastructures (PKI) demand that a semantic or cognitive definition of trust is essential for augmenting the security through trust formulations. In this paper, we examine the meaning of trust in PKIs. Properly categorized trust can help in developing intelligent algorithms that can adapt to the security and privacy requirements of the clients. We...
Location-based services can be seen everywhere today in our smartphones and devices that use GPS, and this service has become invaluable to customers. LBSs, however, do have their flaws. Users are forced to reveal location data if they want to use the service, which can be a risk for their own privacy and security. Therefore, several techniques have been proposed in literature in order to provide...
Mobile crowd-sourcing can become as a strategy to perform time-sensitive urban tasks (such as municipal monitoring and last mile logistics) by effectively coordinating smartphone users. The success of the mobile crowd-sourcing platform depends mainly on its effectiveness in engaging crowd-workers, and recent studies have shown that compared to the pull-based approach, which relies on crowd-workers...
Preserving user privacy is crucial for the wide adoption of crowdsensing and participatory sensing applications that rely on personal devices. Currently, each application comes with its own hardwired and possibly undocumented privacy support (if any), while the horizontal protection mechanisms provided by operating and runtime systems operate at a low level that can significantly harm application...
Vehicular Ad-hoc Networks (VANETs) are formed by a huge number of vehicles which act as the network nodes and communicate with one another. This emerging paradigm has opened up new business opportunities and enables numerous applications ranging from road safety enhancement to mobile entertainment. A fundamental issue that impacts the successful deployment of VANET applications is the security and...
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