无线多跳网络的可信数据传输机制

为无线多跳网络设计了一种可信数据传输方案,通过编码、复制和多路径分发等多种手段的结合,实现了数据机密性和传输鲁棒性的增强.针对数据机密性,设计了基于异或计算的编码方式,将解析数据片段的难度提高到等同于攻占所有的数据分发路径;针对传输的鲁棒性,基于多路径设计了备份与校验相结合的容错模型和数据分发算法,实现了容忍多路径失效.主要算法具备较好的适应性和可扩充性,同时在数据冗余度、路径利用率和快速数据恢复能力等各方面取得了较好的平衡.     

基于多路径路由的移动自组网可靠数据传输

在移动自组网络中，由于攻击或者链路失效使网络产生的拓扑变化往往会导致数据传输的中断，而信道共享和多跳特性也使得机密性难以得到保证。针对Ad hoc网络端对端的可靠数据传输，提出了基于多路径路由的多路数据传输模式，重点研究了数据分割和在多路径上的数据分布问题。通过并行传输、适度数据冗余和校验计算相结合，以及容错的数据分布，增强了数据传输的鲁棒性和机密性。     

无线环境下基于多流优先级的并行多路传输

在无线异构网络环境下提出一种基于多流优先级的并行多路传输方案。该方案基于并行多路传输协议CMT-SCTP,并利用了SCTP的多流特性和部分可靠特性。针对数据的重要性和时间敏感度,设计优先级数据调度算法;同时提出基于路径质量的数据分发机制,进一步保证数据的有效传输。在NS-2中的仿真结果表明,该方案能够有效提高数据传输的吞吐量,减少时延,保证较好的数据传输性能。     

基于智能卡的分布式数据传输安全模型

针对分布式环境下的数据分发和管理问题,以智能卡与口令作为身份认证与密钥交换的基础,设计一个分布式数据传输安全模型。对该模型从敌手攻击角度和模型自身满足安全性角度进行安全性分析,结果表明,该模型不仅可以保证数据的完整性、不可否认性以及达成双方认证,还可以在最大程度上实现机密性信息在分布式环境下的安全传输过程。     

车载自组织网络中一种连通度感知的可靠数据分发机制

车载自组织网络可以通过多跳无线广播实现远距离的数据传输,但网络拓扑的快速变化和无线通信质量的不稳定会导致数据传输性能的不稳定.为了应对这些挑战,文中提出了一种适用于城市场景的可靠的、连通度感知的数据分发机制.该机制利用实时收集的交通流量数据,建立路口车辆排队长度变化的马尔可夫模型,并基于此模型估算路段间无线网络连通度的实时变化,以便数据沿最小延迟路径进行转发.该机制还考虑到城市环境对无线信号的干扰,用覆盖消除规则改进了贪心广播算法,通过多候选转发策略增强了路段间数据传输的可靠性.模拟实验结果表明,与基于传染病的数据分发协议、基于静态节点的自适应数据分发协议相比,文中提出的机制能实现高可靠、低延迟的数据分发.     

无线传感器网络中的分频数据分发协议

从数据源到数据接收者的数据分发是无线传感器网络的重要功能．本文提出了分频数据分发协议，该协议通过多棵分发树对数据接收者进行数据分发，从而最大限度地重用数据传输路径．实验表明，在数据接收者较多的情况下，分频数据分发协议比现有最好的数据分发协议SEAD的加权路径长度要短15％左右，从而有效节省了分发数据的能量消耗，延长了系统生命期．     

基于树结构的分布式数据流水分发方法

针对网络带宽给数据分发带来的限制以及传统数据分发方法的不足,本文提出了一种基于树结构的分布式数据流水分发方法。该方法利用接收端的转发能力,采用流水式传输方式进行数据传输,以提高数据分发的整体效率。算法分析和实验数据表明,本文的方法是有效的。     

无线传感器网络的数据分发技术

无线传感器网络通常由能量有限的大量传感器节点组成,数据分发是无线传感器网络的一个基本功能.设计能量有效的数据分发方案可以优化数据传输路径,减少能量消耗和网络拥塞,有效延长网络寿命.文章在简要介绍数据分发分类的基础上,重点分析了目前主要的数据分发方案,并进行了比较.     

基于多径路由的安全消息传输协议MODSMT的设计

移动自组网中现有的基于多径路由的安全消息传输协议在机密性和可用性方面不能同时得到保证。提出一种安全增强的数据传输协议MODSMT(Modified Secure Message Transmission)。MODSMT协议关注的是数据的可用性和机密性,它在SMT协议基础上进行安全优化,每条路径上的加密密钥是通过采用秘密值关联的单向函数动态地计算而得出,编码片段加密后分开传输加密数据和对应密钥参数,并通过多径传输到目的节点。仿真表明,MODSMT协议对数据的可用性和机密性能够同时兼顾。     

无线传感器网络中数据分发方案的研究

无线传感器网络是由大量具有感知、计算和通信能力的能量有限的微型传感器节点组成。为了建立有效的数据传输路径,节约能耗和带宽,延长网络生存期,设计能量有效的数据分发方案是至关重要的。针对无线传感器网络中节点是否可移动的三种情况,分析了目前提出的主要数据分发方案。     

面向雾计算的压缩感知图像秘密传输和篡改恢复方案

在雾计算三层数据传输框架下,用户的图像数据隐私泄露依然是最严重的问题之一,特别是大多数加密方法都不适用于物理终端资源受限的情况。因此,针对这类场景,需要设计合适的数据隐私保护方法。压缩感知具有轻量级和保密性,可以解决该问题。文章提出一种基于压缩感知的图像数据三层传输方案,不仅可以实现数据的安全传输,还可以结合里德-所罗门码(RS)应对篡改攻击,实现篡改定位和恢复。保密性方面,终端利用块压缩感知实现轻量级加密。由于测量值可能泄露明文能量,在雾服务器上将测量值进行局部归一化,对产生的能量值进行高强度加密,使传输过程达到完美保密。完整性方面,利用压缩感知的鲁棒性和ELS编码的冗余性实现数据的篡改定位和双重篡改恢复。仿真结果和分析验证了该方案的性能。     

基于区块链和属性基加密的个人隐私数据保护方案

针对用户使用第三方应用提供的服务时所带来的隐私泄露问题,提出一种基于属性基加密和区块链的个人隐私数据保护方案.方案利用区块链来保存个人隐私数据的哈希值和第三方应用的属性集,而真正的隐私信息利用属性基算法加密后保存在分布式哈希表中.本方案实现了个人数据的一对多的安全传输和数据的细粒度访问控制;针对用户在不同时期的需求动态变化的特点,提出了一种新的属性基加密方案,用户可以随时撤销第三方应用的访问权限,并且不需要可信第三方.对整个方案进行了仿真实验,验证了方案的可行性和实用性.     

Channel equalization for synchronization of chaotic maps

Many communication systems applying synchronism of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, due to the lack of robustness of chaos synchronization, even minor channel imperfections are enough to hinder communication. In this paper, we propose an adaptive equalization scheme based on a modified normalized least-mean-squares (NLMS) algorithm, which enables chaotic synchronization when the communication channel is not ideal. As an example of application, this scheme is used to recover a binary sequence modulated by a chaotic signal generated by the Hénon map. Simulation results show that the modified NLMS can successfully equalize the channel in different scenarios.     

A fine-grained privacy protection data aggregation scheme for outsourcing smart grid

Compared with the traditional power grid, smart grid involves many advanced technologies and applications. However, due to the rapid development of various network technologies, smart grid is facing the challenges of balancing privacy, security, efficiency, and functionality. In the proposed scheme, we design a privacy protection scheme for outsourcing smart grid aided by fog computing, which supports fine-grained privacy-protected data aggregation based on user characteristics. The fog server matches the encrypted characteristics in the received message with the encrypted aggregation rules issued by the service provider. Therefore, the service provider can get more fine-grained analysis data based on user characteristics. Different from the existing outsourcing smart grid schemes, the proposed scheme can achieve real-time pricing on the premise of protecting user privacy and achieving system fault tolerance. Finally, experiment analyses demonstrate that the proposed scheme has less computation overhead and lower transmission delay than existing schemes.     

A MS-GS VQ codebook design for wireless image communication usinggenetic algorithms

An image compression technique is proposed that attempts to achieve both robustness to transmission bit errors common to wireless image communication, as well as sufficient visual quality of the reconstructed images. Error robustness is achieved by using biorthogonal wavelet subband image coding with multistage gain-shape vector quantization (MS-GS VQ) which uses three stages of signal decomposition in an attempt to reduce the effect of transmission bit errors by distributing image information among many blocks. Good visual quality of the reconstructed images is obtained by applying genetic algorithms (GAs) to codebook generation to produce reconstruction capabilities that are superior to the conventional techniques. The proposed decomposition scheme also supports the use of GAs because decomposition reduces the problem size. Some simulations for evaluating the performance of the proposed coding scheme on both transmission bit errors and distortions of the reconstructed images are performed. Simulation results show that the proposed MS-GS VQ with good codebooks designed by GAs provides not only better robustness to transmission bit errors but also higher peak signal-to-noise ratio even under high bit error rate conditions     

隐私数据验证场景下的隐私保护研究

隐私数据验证场景是信息验证服务下的一类特殊场景,其实用性要求数据在第三方数据库进行存储、发布且有能力处理任意形式声明的验证,其安全性要求数据在存储、更新与证明期间提供有效的隐私保护手段。目前该场景下的隐私保护研究尚且处于空白阶段,因此本文引入可证明数据加密策略的概念,以满足隐私数据验证场景下的实用性与安全性需求。本文主要有三个贡献：（1）对可证明数据加密策略进行讨论并给出形式化定义;（2）基于非交互零知识证明构造出首个可证明数据加密方案,并同时支持高效的数据更新操作;（3）基于承诺方案、非交互零知识证明与全同态加密,提出可证明数据加密策略的两种通用构造框架并给予相关性质证明。     

基于单向函数的无线传感器网络安全数据汇聚方案

为有效减少冗余数据传输,增强安全性,提出了一种基于单向函数的传感器网络安全数据汇聚方案,汇聚节点无须解密数据,利用单向函数完成数据完整性检查、身份认证、数据汇聚等,保证了端到端传输的数据私密性。与相关数据汇聚方案相比,除了具有较小的能耗开销,该方案还在抵抗主动攻击、节点妥协攻击及DoS攻击等恶意行为方面具有较高的安全性。     

一种改进的匿名奖励方案

根据盲签名的电子现金支付方式,提出一种改进的匿名奖励方案。该方案可保证奖励申请者匿名地提交问题解答和获得奖励,能有效地保护奖励申请者的隐私。引入(t, m)秘密共享方案,使奖励提供者通过合作获得问题解答,从而保证方案的公平性。与现有的奖励方案相比,该方案具有数据传输安全性高、密钥长度短、通信成本低等特点,在无线网络中具有一定的实用性。     

Toward inference attacks for k-anonymity

Current research still cannot effectively prevent an inference attacker from inferring privacy information for k-anonymous data sets. To solve the issue, we must first study all kinds of aggressive reasoning behaviors and process for the attacker thoroughly. Our work focuses on describing comprehensively the inference attack and analyzing their privacy disclosures for k-anonymous data sets. In this paper, we build up a privacy inference graph based on attack graph theory, which is an extension of attack graph. The privacy inference graph describes comprehensively the inference attack in k-anonymous databases by considering attacker background knowledge and external factors. In the privacy inference graph, we introduce a concept of valid inference path to analyze the privacy disclosures in face of inference attack. According to both above, we design an algorithm to compute the n-valid inference paths. These paths can deduce some privacy information resulting in privacy disclosure. Moreover, we study the optimal privacy strategies to resist inference attack by key attribute sets and valid inference paths in the attack graph. An approximate algorithm is designed to obtain the approximate optimal privacy strategy set. At last, we prove the correctness in theory and analyze the performance of the approximate algorithm and their time complexity.     

Peer-to-Peer Live Video Distribution under Heterogeneous Bandwidth Constraints

This paper presents a new collaborative peer-to-peer (P2P) streaming framework for heterogeneous bandwidth capacity of clients. The proposed architecture aims for two primary goals: (1) providing higher streaming quality by making best use of the extra available bandwidth that might exist among heterogeneous clients and (2) providing robustness and resilience to high churn rate of peers by introducing redundancy, both in network paths (multisender overlay) and data (multilayered video content). For achieving these goals, we employ a gossip-based data-driven scheme for partnership formation and layered video coding for bandwidth adaptivity. To solve multilayer bitstream allocation problem, we proposed two algorithms, namely optimized transmission policy and graceful degradation scheme algorithms. The proposed system has a complete self-regulation and in a decentralized fashion. Extensive simulations show that the proposed system achieves higher quality of service through peer-assisted streaming and layered video coding. The results also show that the system outperforms some previous schemes in system overhead and reliability for dynamic node behavior.