Discuss the problem of infinite increasing coin list in anonymous E-cash systems, which reduce the efficiency of whole system greatly. Though some methods are suggested, no one can solve the problem with high efficien...Discuss the problem of infinite increasing coin list in anonymous E-cash systems, which reduce the efficiency of whole system greatly. Though some methods are suggested, no one can solve the problem with high efficiency and flexibility. Here, we use the technique of adding information in blind signatures to deal with this problem. Through adding timestamp in signatures, we can separate the valid period of all used coins into pieces. Only the coins in the last stage are recorded. So the scale of the coins list is controlled. We also analyze the anonymity of these data, and add some indispensable restrictions to them. These restrictions can ensure that the imported data don’t break the anonymity of the customers. In order to fulfill these qualifications, we lead to the concept of restricted common data (RCD). Furthermore, we propose two schemes to add RCD in the blind signature. The simple one is easy to implement, while the complex one can note the value of the coin. The usage of RCD leads to little additional cost, as well as maintaining the anonymity of customers. This method fits for most kinds of anonymous E-cash systems.展开更多
Big data and associated analytics have the potential to revolutionize healthcare through the tools and techniques they offer to manage and exploit the large volumes of heterogeneous data being collected in the healthc...Big data and associated analytics have the potential to revolutionize healthcare through the tools and techniques they offer to manage and exploit the large volumes of heterogeneous data being collected in the healthcare domain. The strict security and privacy constraints on this data, however, pose a major obstacle to the successful use of these tools and techniques. The paper first describes the security challenges associated with big data analytics in healthcare research from a unique perspective based on the big data analytics pipeline. The paper then examines the use of data safe havens as an approach to addressing the security challenges and argues for the approach by providing a detailed introduction to the security mechanisms implemented in a novel data safe haven. The CIMVHR Data Safe Haven (CDSH) was developed to support research into the health and well-being of Canadian military, Veterans, and their families. The CDSH is shown to overcome the security challenges presented in the different stages of the big data analytics pipeline.展开更多
文摘Discuss the problem of infinite increasing coin list in anonymous E-cash systems, which reduce the efficiency of whole system greatly. Though some methods are suggested, no one can solve the problem with high efficiency and flexibility. Here, we use the technique of adding information in blind signatures to deal with this problem. Through adding timestamp in signatures, we can separate the valid period of all used coins into pieces. Only the coins in the last stage are recorded. So the scale of the coins list is controlled. We also analyze the anonymity of these data, and add some indispensable restrictions to them. These restrictions can ensure that the imported data don’t break the anonymity of the customers. In order to fulfill these qualifications, we lead to the concept of restricted common data (RCD). Furthermore, we propose two schemes to add RCD in the blind signature. The simple one is easy to implement, while the complex one can note the value of the coin. The usage of RCD leads to little additional cost, as well as maintaining the anonymity of customers. This method fits for most kinds of anonymous E-cash systems.
文摘Big data and associated analytics have the potential to revolutionize healthcare through the tools and techniques they offer to manage and exploit the large volumes of heterogeneous data being collected in the healthcare domain. The strict security and privacy constraints on this data, however, pose a major obstacle to the successful use of these tools and techniques. The paper first describes the security challenges associated with big data analytics in healthcare research from a unique perspective based on the big data analytics pipeline. The paper then examines the use of data safe havens as an approach to addressing the security challenges and argues for the approach by providing a detailed introduction to the security mechanisms implemented in a novel data safe haven. The CIMVHR Data Safe Haven (CDSH) was developed to support research into the health and well-being of Canadian military, Veterans, and their families. The CDSH is shown to overcome the security challenges presented in the different stages of the big data analytics pipeline.
