Abstract-Entities (e.g., users, services) have to authenticate themselves to service providers (SPs) in order to use their services. An entity provides personally identifiable information (PII) that uniquely identifies it to an SP.In the traditional application-centric Identity Management (IDM) model, each application keeps trace of identities of the entities that use it. In cloud computing, entities may have multiple accounts associated with different SPs, or one SP. Sharing PIIs of the same entity across services along with associated attributes can lead to mapping of PIIs to the entity.We propose an entity-centric approach for IDM in the cloud. The approach is based on: (1) active bundles-each including a payload of PII, privacy policies and a virtual machine that enforces the policies and uses a set of protection mechanisms to protect themselves; (2) anonymous identification to mediate interactions between the entity and cloud services using entity's privacy policies.The main characteristics of the approach are: it is independent of third party, gives minimum information to the SP and provides ability to use identity data on untrusted hosts.
Abstract-Cloud computing allows the use of Internet-based services to support business processes and rental of IT-services on a utility-like basis. It offers a concentration of resources but also poses risks for data privacy. A single breach can cause significant loss. The heterogeneity of "users" represents a danger of multiple, collaborative threats.In cloud computing, entities may have multiple accounts associated with a single or multiple service providers (SPs). Sharing sensitive identity information (that is, Personally Identifiable information or PII) along with associated attributes of the same entity across services can lead to mapping of the identities to the entity, tantamount to privacy loss.Identity management (IDM) is one of the core components in cloud privacy and security and can help alleviate some of the problems associated with cloud computing. Available solutions use trusted third party (TTP) in identifying entities to SPs. The solution providers do not recommend the usage of their solutions on untrusted hosts.We propose an approach for IDM, which is independent of TTP and has the ability to use identity data on untrusted hosts. The approach is based on the use of predicates over encrypted data and multi-party computing for negotiating a use of a cloud service. It uses active bundle-which is a middleware agent that includes PII data, privacy policies, a virtual machine that enforces the policies, and has a set of protection mechanisms to protect itself. An active bundle interacts on behalf of a user to authenticate to cloud services using user's privacy policies.
Speech recognition (SR) technologies were evaluated in different classroom environments to assist students to automatically convert oral lectures into text. Two distinct methods of SR-mediated lecture acquisition (SR-mLA), real-time captioning (RTC) and postlecture transcription (PLT), were evaluated in situ life and social sciences lecture courses employing typical classroom equipment. Both methods were compared according to technical feasibility and reliability of classroom implementation, instructors' experiences, word recognition accuracy, and student class performance. RTC provided near-instantaneous display of the instructor's speech for students during class. PLT employed a user-independent SR algorithm to optimally generate multimedia class notes with synchronized lecture transcripts, instructor audio, and class PowerPoint slides for students to access online after class. PLT resulted in greater word recognition accuracy than RTC. During a science course, students were more likely to take optional online quizzes and received higher quiz scores with PLT than when multimedia class notes were unavailable. Overall class grades were also higher when multimedia class notes were available. The potential benefits of SR-mLA for students who have difficulty taking notes accurately and independently were discussed, particularly for nonnative English speakers and students with disabilities. Field-tested best practices for optimizing SR accuracy for both SR-mLA methods were outlined.
Abstract-Modern organizations interact with their partners through digital supply chain business processes for producing and delivering products and services to consumers. A partner in this supply chain can be a sub-contractor to whom work is outsourced. Each partner in a supply chain uses data, generates data and shares data with other partners, and all this collaboration contributes to producing and delivering the product(s) or service(s). The main security challenge in supply chains is the unauthorized disclosure and data leakage of information shared among the partners. Current approaches for protecting data in supply chain rely on the use of standards, service level agreements, and legal contracts. We propose an auditing based approach for protecting shared data in digital supply chains.
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