The Experts below are selected from a list of 45588 Experts worldwide ranked by ideXlab platform

Yanjiang Yang - One of the best experts on this subject based on the ideXlab platform.

  • Towards Lightweight Anonymous Entity Authentication for IoT Applications
    Information Security and Privacy, 2016
    Co-Authors: Yanjiang Yang, Haibin Cai, Haibing Lu, Zhuo Wei, Kim-kwang Raymond Choo
    Abstract:

    Preservation of Individual Privacy is an important issue in future IoT applications, which calls for lightweight anonymous entity authentication solutions that can be executed efficiently upon a wide range of resource-constrained IoT devices and gadgets. Existing anonymous credential techniques are not well fitted to the setting of IoT, and it is especially so when credential revocation support is considered. In this paper, leveraging on dynamic accumulator we propose a lightweight anonymous entity authentication scheme with outsource-able witness update, solving the main bottleneck of anonymous credentials. We further improve the performance of the scheme with the idea of self-blinding, in such a way that the computation by the prover works entirely in the compact bilinear group of bilinear map. Our performance evaluation shows that the proposed schemes are good for resource-constrained devices.

  • self blindable credential towards anonymous entity authentication upon resource constrained devices
    International Conference on Information Security, 2013
    Co-Authors: Yanjiang Yang, Haibing Lu, Xuhua Ding, Jian Weng, Jianying Zhou
    Abstract:

    We are witnessing the rapid expansion of smart devices in our daily life. The need for Individual Privacy protection calls for anonymous entity authentication techniques with affordable efficiency upon the resource-constrained smart devices. Towards this objective, in this paper we propose self-blindable credential, a lightweight anonymous entity authentication primitive. We provide a formulation of the primitive and present two concrete instantiations.

  • self blindable credential towards lightweight anonymous entity authentication
    IACR Cryptology ePrint Archive, 2013
    Co-Authors: Yanjiang Yang, Haibing Lu, Xuhua Ding, Jian Weng
    Abstract:

    We are witnessing the rapid expansion of smart devices in our daily life. The need for Individual Privacy protection calls for anonymous entity authentication techniques with affordable efficiency upon the resource-constrained smart devices. Towards this objective, in this paper we propose self-blindable credential, a lightweight anonymous entity authentication primitive. We provide a formulation of the primitive and present two concrete instantiations. The first scheme implements verifier-local revocation and the second scheme enhances the former with forward security. Our analytical performance results show that our schemes outperform relevant existing schemes.

  • a new approach for anonymous password authentication
    Annual Computer Security Applications Conference, 2009
    Co-Authors: Yanjiang Yang, Jian Weng, Jianying Zhou, Feng Bao
    Abstract:

    Anonymous password authentication reinforces password authentication with the protection of user Privacy. Considering the increasing concern of Individual Privacy nowadays, anonymous password authentication represents a promising Privacy-preserving authentication primitive. However, anonymous password authentication in the standard setting has several inherent weaknesses, making its practicality questionable. In this paper, we propose a new and efficient approach for anonymous password authentication. Our approach assumes a different setting where users do not register their passwords to the server; rather, they use passwords to protect their authentication credentials. We present a concrete scheme, and get over a number of challenges in securing password-protected credentials against off-line guessing attacks. Our experimental results confirm that conventional anonymous password authentication does not scale well, while our new scheme demonstrates very good performance.

Jian Weng - One of the best experts on this subject based on the ideXlab platform.

  • self blindable credential towards anonymous entity authentication upon resource constrained devices
    International Conference on Information Security, 2013
    Co-Authors: Yanjiang Yang, Haibing Lu, Xuhua Ding, Jian Weng, Jianying Zhou
    Abstract:

    We are witnessing the rapid expansion of smart devices in our daily life. The need for Individual Privacy protection calls for anonymous entity authentication techniques with affordable efficiency upon the resource-constrained smart devices. Towards this objective, in this paper we propose self-blindable credential, a lightweight anonymous entity authentication primitive. We provide a formulation of the primitive and present two concrete instantiations.

  • self blindable credential towards lightweight anonymous entity authentication
    IACR Cryptology ePrint Archive, 2013
    Co-Authors: Yanjiang Yang, Haibing Lu, Xuhua Ding, Jian Weng
    Abstract:

    We are witnessing the rapid expansion of smart devices in our daily life. The need for Individual Privacy protection calls for anonymous entity authentication techniques with affordable efficiency upon the resource-constrained smart devices. Towards this objective, in this paper we propose self-blindable credential, a lightweight anonymous entity authentication primitive. We provide a formulation of the primitive and present two concrete instantiations. The first scheme implements verifier-local revocation and the second scheme enhances the former with forward security. Our analytical performance results show that our schemes outperform relevant existing schemes.

  • a new approach for anonymous password authentication
    Annual Computer Security Applications Conference, 2009
    Co-Authors: Yanjiang Yang, Jian Weng, Jianying Zhou, Feng Bao
    Abstract:

    Anonymous password authentication reinforces password authentication with the protection of user Privacy. Considering the increasing concern of Individual Privacy nowadays, anonymous password authentication represents a promising Privacy-preserving authentication primitive. However, anonymous password authentication in the standard setting has several inherent weaknesses, making its practicality questionable. In this paper, we propose a new and efficient approach for anonymous password authentication. Our approach assumes a different setting where users do not register their passwords to the server; rather, they use passwords to protect their authentication credentials. We present a concrete scheme, and get over a number of challenges in securing password-protected credentials against off-line guessing attacks. Our experimental results confirm that conventional anonymous password authentication does not scale well, while our new scheme demonstrates very good performance.

Donna F Stroup - One of the best experts on this subject based on the ideXlab platform.

  • future directions for comprehensive public health surveillance and health information systems in the united states
    American Journal of Epidemiology, 1994
    Co-Authors: Stephen B Thacker, Donna F Stroup
    Abstract:

    The authors describe a comprehensive system for public health surveillance for the United States based on a network of data systems ranging from population surveys and physician-based records to electronically linked laboratory and administrative data. They also discuss traditional uses of surveillance data, legal and ethical issues associated with using data from any surveillance system (particularly the tension between Individual Privacy and the public right to a healthful environment), and factors impeding the development of a comprehensive system. Just as provisional data on notifiable diseases are critical in protecting communities from disease, data from other information systems should be applied to prevention practice with the same urgency. The major barriers to a successful comprehensive, nationwide, integrated public health surveillance and information system are a lack of appreciation for the value of high-quality provisional surveillance data and a weak societal commitment to public health.

Laura E Hunt - One of the best experts on this subject based on the ideXlab platform.

Jian Pei - One of the best experts on this subject based on the ideXlab platform.

  • minimality attack in Privacy preserving data publishing
    Very Large Data Bases, 2007
    Co-Authors: Raymond Chiwing Wong, Ke Wang, Jian Pei
    Abstract:

    Data publishing generates much concern over the protection of Individual Privacy. Recent studies consider cases where the adversary may possess different kinds of knowledge about the data. In this paper, we show that knowledge of the mechanism or algorithm of anonymization for data publication can also lead to extra information that assists the adversary and jeopardizes Individual Privacy. In particular, all known mechanisms try to minimize information loss and such an attempt provides a loophole for attacks. We call such an attack a minimality attack. In this paper, we introduce a model called m-confidentiality which deals with minimality attacks, and propose a feasible solution. Our experiments show that minimality attacks are practical concerns on real datasets and that our algorithm can prevent such attacks with very little overhead and information loss.

  • achieving k anonymity by clustering in attribute hierarchical structures
    Data Warehousing and Knowledge Discovery, 2006
    Co-Authors: Raymond Chiwing Wong, Jian Pei
    Abstract:

    Individual Privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view of k-anonymity is clustering with a constraint of the minimum number of objects in every cluster. Most existing approaches to achieving k-anonymity by clustering are for numerical (or ordinal) attributes. In this paper, we study achieving k-anonymity by clustering in attribute hierarchical structures. We define generalisation distances between tuples to characterise distortions by generalisations and discuss the properties of the distances. We conclude that the generalisation distance is a metric distance. We propose an efficient clustering-based algorithm for k-anonymisation. We experimentally show that the proposed method is more scalable and causes significantly less distortions than an optimal global recoding k-anonymity method.