Cryptanalysis of the RNTS system

Internet of Things is a paradigm that enables communication between different devices connected to a local network or to Internet. Identification and communication between sensors used in Internet of Things and devices like smart-phones or tablets are established using radio frequency identification technology. However, this technology still has several security and privacy issues because of its severe computational constraints. In 2011, Jeong and Anh proposed the combined use of an authentication radio frequency identification protocol together with a ticket issuing system for bank services (in J. Supercomput. 55:307, 2011). In this paper we show that their message generation is weak, because it abuses the XOR operation and the use of a counter, which leaks too much secret protocol information. Our analysis shows important security faults that ruin most of the security properties claimed in the original paper. More precisely, information privacy (via a disclosure and leakage attack) and location privacy (traceability attack) are both compromised. Moreover, an attacker can disrupt the proper working of the system by exploiting the fact that message integrity is not properly checked.     

高效的离线电子现金方案

电子现金本质上是一串容易被复制的比特序列,如何在保护合法用户匿名性的前提下有效地防止其被重复花费是电子现金研究的关键。提出了一种新的基于RSA盲签名的离线电子现金方案,采用双密钥对称加密,将用户账号信息嵌入其中,从而保证合法花费一次用户的匿名性,也能够以极大的概率找出重复使用同一笔电子现金的用户。对分割选择（cutandchoose）机制进行了改进,降低了计算复杂度。最后,对方案的公平性和安全性进行了分析。     

Effect of trust on customer acceptance of Internet banking

Two beliefs, ease of use and usefulness, have been considered to be fundamental in determining the acceptance of various IS in the past decades. These beliefs may not, however, fully explain the users’ behavior in an emerging environment such as Internet banking. In this study, we introduce trust as another belief that has an impact on the acceptance of Internet banking. We collected 845 cases on the Web to survey users’ behavior towards Internet banks. The results of statistical analyses using structural equation modeling indicate that trust has a significant impact on the acceptance of Internet banking.     

面向用户隐私保护的高效基因比对方案

针对当前的基因序列比对协议普遍要求一个可信赖的第三方,可能因此造成大范围的隐私数据泄漏的问题,提出了一种基于线性扫描的基因比对方案。首先对两方的基因序列进行基于混淆电路（GC）的编码,然后线性扫描整个基因组数据库并用混淆电路实现客户的基因序列与库中所有基因序列的比对。上述方案可以在保护双方用户隐私的前提下,实现基因比对。不过该方案需要扫描整个基因组数据库,时间复杂度为O（n）,在基因组数据库较大时效率较低。为了提高基因比对的效率,进一步提出了基于不经意随机存取（ORAM）的基因比对方案,先将基因数据存储在ORAM上,然后只需把目标路径上的数据项取出并用混淆电路进行基因比对。该方案的比对次数和数据库的大小呈亚线性关系,时间复杂度为O（log n）。实验结果表明,基于ORAM的基因比对方案在实现隐私保护的同时,把比对次数由O（n）减小到了O（log n）,明显降低了比对操作的时间复杂度,可以用来进行疾病诊断,尤其适用于基因组数据库较大的场景。     

基于CIF的银行分析型CRM系统的研究与设计

分析型客户关系管理系统（ACRM）的决策支持能力是CRM实施成功的关键。首先讨论了当前银行分析型客户关系管理数据仓库系统存在的问题,然后介绍了企业信息工厂（CIF）理论的原理、主要部件和对CRM的决策支持能力,提出了一种改进的三层ACRM体系结构模型,并从体系结构和决策支持能力两个方面探讨了基于CIF的银行分析型CRM数据仓库系统的设计与实施,最后讨论了其应用。     

一种高效隐私的区块链认知物联网框架

针对动态物联网隐私安全问题及低效推荐系统问题,提出一种高效隐私的区块链认知物联网框架。该框架分为区块链物联网管理层、认知过程层和需求层三层,区块链物联网管理层为认知层提供所需信息,然后对系统的可管理元素进行安全隐私的操作;在认知层中,认知引擎观察有关系统的信息,然后执行适当的算法来管理系统;在需求层中,通过认知规范语言（cognitive specification language,CSL）来描述网络的目标和行为。所提区块链物联网框架的认知推荐系统从过去发生的经验中学习,改进关于物联网推荐的决策,与其他物联网框架比较,所提框架和推荐系统具有隐私安全和高性能的推荐能力。     

A blackboard system for the off-line programming of Robots

This paper describes the use of the blackboard architecture for the off-line programming of an IMB 7565 Robot. A blackboard system was implemented in PROLOG and it has been applied successfully for the automatic generation of a control code for the robot to perform the task of block assembly in an environment with an obstacle. The opportunistic type of problem-solving offered by the blackboard architecture has succeeded in obtaining a solution. The user-interface to the system is represented as a knowledge source in the blackboard system, which allows the user to modify the goal specifications during the operation of the blackboard system.     

The effect of Internet general privacy concern on customer behavior

Privacy and its related variables are important determinants of customer behavior in the electronic market. This paper aims to examine the concern for customer privacy on the Internet, mainly with regard to disclosing personal information online. Furthermore, by establishing an experimental situation, we will analyze how this behavior is influenced by familiarity with the website sponsor, the level of control over the information the customer has and the sensitivity of the information requested.The results indicate that all the above-mentioned variables (except familiarity) have a significant impact on consumer online behavior.     

具有隐私保护的边缘计算高效数据卸载方法

针对用户终端数据卸载过程中难以同时实现高隐私安全和低时间消耗的目标,提出了一种具有隐私保护的边缘计算高效数据卸载方法.首先,利用时间计算模型和隐私熵值分别将用户终端时间消耗和数据隐私安全程度进行量化,并建立一个多目标优化问题模型;其次,利用改进强度帕累托进化算法对时间消耗和隐私熵值进行联合优化;最后,利用基于熵权法的多属性决策方法选取最优的时间消耗和隐私熵组合策略.在多终端用户多计算任务的边缘计算下展开实验研究和对比分析,结果表明,该方法在降低传输时间的基础上还增强了数据卸载传输的安全性.     

Efficient protocols for heavy hitter identification with local differential privacy

Local differential privacy (LDP), which is a technique that employs unbiased statistical estimations instead of real data, is usually adopted in data collection, as it can protect every user’s privacy and prevent the leakage of sensitive information. The segment pairs method (SPM), multiple-channel method (MCM) and prefix extending method (PEM) are three known LDP protocols for heavy hitter identification as well as the frequency oracle (FO) problem with large domains. However, the low scalability of these three LDP algorithms often limits their application. Specifically, communication and computation strongly affect their efficiency. Moreover, excessive grouping or sharing of privacy budgets makes the results inaccurate. To address the above-mentioned problems, this study proposes independent channel (IC) and mixed independent channel (MIC), which are efficient LDP protocols for FO with a large domains. We design a flexible method for splitting a large domain to reduce the number of sub-domains. Further, we employ the false positive rate with interaction to obtain an accurate estimation. Numerical experiments demonstrate that IC outperforms all the existing solutions under the same privacy guarantee while MIC performs well under a small privacy budget with the lowest communication cost.     

具有完全保密性的高效可净化数字签名方案*

现有的基于变色龙散列函数的方案均未达到完全保密性,而基于群签名的可净化数字签名方案满足完全保密性,但因效率较低而不够实用。为此,提出一个新的可净化数字签名方案,它基于传统数字签名方案、BLS签名方案和公钥加密方案构造,且满足可净化数字签名的所有基本安全性需求,即不可伪造性、不可变性、透明性、完全保密性及可审计性,同时具有比基于群签名方案更高的运算效率,继而具有更高的实用性。     

Protecting business intelligence and customer privacy while outsourcing data mining tasks

Nowadays data mining plays an important role in decision making. Since many organizations do not possess the in-house expertise of data mining, it is beneficial to outsource data mining tasks to external service providers. However, most organizations hesitate to do so due to the concern of loss of business intelligence and customer privacy. In this paper, we present a Bloom filter based solution to enable organizations to outsource their tasks of mining association rules, at the same time, protect their business intelligence and customer privacy. Our approach can achieve high precision in data mining by trading-off the storage requirement. This research was supported by the USA National Science Foundation Grants CCR-0310974 and IIS-0546027.

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Efficient biometric palm-print matching on smart-cards for high security and privacy

Multimedia Tools and Applications - Smart control access to any service is at the very basis of any smart city project. Biometrics have been used as a solution for system access control, for many...     

An off-line cursive handwriting recognition system

Describes a complete system for the recognition of off-line handwriting. Preprocessing techniques are described, including segmentation and normalization of word images to give invariance to scale, slant, slope and stroke thickness. Representation of the image is discussed and the skeleton and stroke features used are described. A recurrent neural network is used to estimate probabilities for the characters represented in the skeleton. The operation of the hidden Markov model that calculates the best word in the lexicon is also described. Issues of vocabulary choice, rejection, and out-of-vocabulary word recognition are discussed     

互联网金融业务用户隐私数据安全保障理论与实践

互联网金融业务利用数字化技术,覆盖了传统金融难以覆盖的场景和人群,实现了普惠金融,在为用户带来高效、便捷服务的同时,数字化技术也带来了系统的复杂性风险和技术风险。用户的身份标识、业务属性、行为数据属于高度隐私数据,在采集、存储、分析、应用和交换的生命周期中,任何环节的疏漏均会带来隐私泄漏的安全风险。为此,建立全生命周期的数据安全保障体系,规避相关风险,是对互联网金融业务信息安全的基本要求。     

An expert system for experimental design in off-line quality control

Abstract: Robust design is an efficient method for designing high quality products at low cost. The method examines the effect of a large number of design factors on the variability of a product's response due to various sources of disturbance. This effect can be observed efficiently by studying a large number of variables simultaneously through balanced, orthogonal array experiments, and by analyzing the resulting data using variance decomposition methods. In this paper we describe an expert system prototype for designing efficient experiments. Given the information on various parameters and their levels, the system designs an experiment using orthogonal arrays. This expert system is implemented in Prolog, which is a logic programming language for artificial intelligence research and expert systems development. The system was implemented under the P-Shell knowledge programming environment on UNIX.     

A privacy preserving authorisation system for the cloud

In this paper we describe a policy based authorisation infrastructure that a cloud provider can run as an infrastructure service for its users. It will protect the privacy of users? data by allowing the users to set their own privacy policies, and then enforcing them so that no unauthorised access is allowed to their data. The infrastructure ensures that the users? privacy policies are stuck to their data, so that access will always be controlled by the policies even if the data is transferred between cloud providers or services. This infrastructure also ensures the enforcement of privacy policies which may be written in different policy languages by multiple authorities such as: legal, data subject, data issuer and data controller. A conflict resolution strategy is presented which resolves conflicts among the decisions returned by the different policy decision points (PDPs). The performance figures are presented which show that the system performs well and that each additional PDP only imposes a small overhead.