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1Extended Capabilities for a Privacy-Enhanced Participatory Sensing Infrastructure (PEPSI)
"... Abstract—Participatory sensing is emerging as an innovative com-puting paradigm that targets the ubiquity of always-connected mobile phones and their sensing capabilities. In this context, a multitude of pioneering applications increasingly carry out pervasive collection and dissemination of informa ..."
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to the reports (e.g., location, movements, etc.), a number of privacy concerns need to be taken into account prior to a large-scale deployment of these applications. Motivated by the need for privacy protection in Participatory Sensing, this work presents PEPSI: a Privacy-Enhanced Participatory Sensing
PicFS: The Privacy-enhancing Image-based Collaborative File System
"... Abstract—Cloud computing makes available a vast amount of computation and storage resources in the pay-as-you-go manner. However, the users of cloud storage have to trust the providers to ensure the data privacy and confidentiality. In this paper, we present the Privacy-enhancing Image-based Collabo ..."
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Abstract—Cloud computing makes available a vast amount of computation and storage resources in the pay-as-you-go manner. However, the users of cloud storage have to trust the providers to ensure the data privacy and confidentiality. In this paper, we present the Privacy-enhancing Image
TPIM: Transparent Privacy-Enhanced Identity Management of Web Services
"... Abstract. The growth of web services has been accompanied by sharing more and more users ’ personal information with service providers, which has raised concern about possible malicious or accidental unauthorized abuse of user information. This paper focuses on how we can give the user a deep sense ..."
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of safety, privacy and certainty about service invocations in the diverse and heterogeneous computing environment. We present Transparent privacy-enhanced Identity Management of Web Services (TPIM), a privacy-enhanced personal Identity Management architecture for web services users. TPIM is an extension
FACE RECOGNITION WITH BIOMETRIC ENCRYPTION FOR PRIVACY-ENHANCING SELF-EXCLUSION
"... Face recognition has been employed in various securityrelated applications such as surveillance, mugshot identification, e-passport, and access control. Despite its recent advancements, privacy concern is one of several issues preventing its wider deployment. In this paper, we address the privacy co ..."
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Cited by 2 (0 self)
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concern for a self-exclusion scenario of face recognition, through combining face recognition with a simple biometric encryption scheme called helper data system. The combined system is described in detail with focus on the key binding procedure. Experiments are carried out on the CMU PIE face database
PEPSI (Privacy-Enhanced Permanent Subject Identifier) Embedded in X.509 Certificate
"... bind a public key to a subject. The subject is specified through one or more subject names in the "subject " or "subjectAltName" fields of a certificate. Where the subject is a person, the name that is specified in the subject field of the certificate may reflect the name of the ..."
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) is regarded as a sensitive, private or personal data. Such an identifier cannot simply be included as part of the subject field, since its disclosure may lead to misuse. This paper presents a new method for secure and accurate user authentication through the PEPSI included in the standard certificate
Securing Data Provenance in the Cloud
"... Abstract. Cloud storage offers the flexibility of accessing data from anywhere at any time while providing economical benefits and scalability. However, cloud stores lack the ability to manage data provenance. Data provenance describes how a particular piece of data has been produced. It is vital fo ..."
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for a post-incident inves-tigation, widely used in healthcare, scientific collaboration, forensic analysis and legal proceedings. Data provenance needs to be secured since it may reveal pri-vate information about the sensitive data while the cloud service provider does not guarantee confidentiality
Data Provenance and Security
"... Information is often filtered, sampled, repackaged, condensed, or altered to suit any number of purposes. Over time, the entropy of these processes causes information to lose its essential validity. Far too often, we’re left with data without knowledge. Context is necessary for good decision-making. ..."
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systems. Manifest as annotations, logs, or workflow histories, provenance indicates the data’s origins and pedigree. Data provenance and security are symbiotic. Good security leads to accurate, timely, and detailed age is a pervasive loss of context. Users and organizations receive information
A Privacy-Enhancing Protocol that Provides In-Network Data Aggregation and Verifiable Smart Meter Billing
"... We present an innovative protocol combining in-network data aggregation and smart meter billing for a smart grid scenario. The former enables an energy supplier to allocate and balance resources. The latter provides dynamic pricing schemes according to fine-grained consumption profiles. More-over, ..."
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Cited by 1 (0 self)
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homomorphic commitment scheme with a homomorphic encryption scheme. All data sent from a meter to any other component in the communication network is either a commitment or an encrypted message. To provide security and privacy, we only require software modifications, leaving the hardware of the smart grid
Enhancing source-location privacy in sensor network routing
- In Proceedings of the 25th IEEE International Conference on Distributed Computing Systems (ICDCS
, 2005
"... Abstract — One of the most notable challenges threatening the successful deployment of sensor systems is privacy. Although many privacy-related issues can be addressed by security mechanisms, one sensor network privacy issue that cannot be adequately addressed by network security is source-location ..."
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Cited by 93 (2 self)
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protocols. One of our strategies, a technique we have called phantom routing, has proven flexible and capable of protecting the source’s location, while not incurring a noticeable increase in energy overhead. Further, we examined the effect of source mobility on location privacy. We showed that, even
A Security Model for Provenance
, 2006
"... A Security Model for Provenance Most security models are designed to protect data. Some also deal with traditional metadata. Provenance metadata introduces additional complexity, as does the delicate interactions between provenance metadata and the data it describes. We designed a security model for ..."
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Cited by 14 (3 self)
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A Security Model for Provenance Most security models are designed to protect data. Some also deal with traditional metadata. Provenance metadata introduces additional complexity, as does the delicate interactions between provenance metadata and the data it describes. We designed a security model
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