基于变色龙hash的区块链可扩展存储方案

区块链中的节点以副本形式保存数据,随着时间的推移,区块链中的区块数不断增加,导致节点承受的存储压力随之增大,存储压力成为区块链应用落地的瓶颈之一。为了解决区块链中存储压力问题,提出了基于变色龙hash的区块链可扩展存储方案,该方案利用节点被攻击成功的概率和改进的温度模型,将区块分为高低安全性的冷热区块;基于变色龙hash算法和改进的Merkle tree,对高安全性的冷区块进行部分节点存储。在存储过程中,除高安全性冷区块的区块体信息被重构外,其余数据保持不变。仿真实验表明,在不改变区块链结构和安全性能的情况下,所提出的方案可减少区块链中数据的存储总量,减少存储节点的存储压力;且区块数量越多,其优势越明显。     

Chameleon Hashes Without Key Exposure Based on Factoring

Chameleon hash is the main primitive to construct a chameleon signature scheme which provides nonrepudiation and non-transferability simultaneously. However, the initial chameleon hash schemes suffer from the key exposure problem： non-transferability is based on an unsound assumption that the designated receiver is willing to abuse his private key regardless of its exposure. Recently, several key-exposure-free chameleon hashes have been constructed based on RSA assumption and SDH （strong Diffie-Hellman） assumption. In this paper, we propose a factoring-based chameleon hash scheme which is proven to enjoy all advantages of the previous schemes. In order to support it, we propose a variant Rabin signature scheme which is proven secure against a new type of attack in the random oracle model.     

国际变色龙品牌的商业广告表现研究——以日化行业为例

广告作为一种传播符号,对于品牌塑造是至关重要的,但同时也有文化与地域的差别。在日化行业,一些外国日用个人护理产品品牌呈现出了强大的变色龙效应,使所有消费群体都受到了影响。针对这一现象,本文主要从广告人物形象、广告情感因素、广告表现元素三个方面对这些国际变色龙品牌的商业广告表现进行了分析研究,以从中找出国际品牌实现其本土化变色龙效应的一些可借鉴经验。     

基于身份的多重变色龙散列函数的构造及应用

定义并构造了模n下的整体同态加密系统,利用该类系统的整体同态性构造了基于身份的多重变色龙散列函数,并给出了该函数的应用--基于身份的多重变色龙签名,它不仅具有普通变色龙签名的特点,而且签名结果对于所有指定接收人中任意一个人都具有不可传递性,省去了公钥证书管理的代价,且伪造签名并不会引发所有指定接收人中任何个人密钥的泄露.     

新的基于变色龙的车载通信安全与隐私保护

在车载自组网（VANET）中许多服务和应用需要保护数据通信的安全,为提高驾驶的安全性和舒适性,一些与交通状况有关的信息就要被周期性地广播并分享给司机,如果用户的身份和信息没有隐私和安全的保证,攻击者就会通过收集和分析交通信息追踪他们感兴趣的车辆,因此,匿名消息身份验证是VANET中不可或缺的要求。另一方面,当车辆参与纠纷事件时,证书颁发机构能够恢复车辆的真实身份。为解决车载通信这一问题,郭等人在传统方案的基础上提出一种基于椭圆曲线的变色龙散列的隐私保护验证协议。虽然此方案较之前方案具有车辆身份可追踪性和高效率性,但分析表明此方案不满足匿名性。对郭等人的方案进行安全性分析并在此基础上做出改进。     

一种具有灵活公钥的自生成证书公钥加密方案

Self-Generated-Certificate Public Key Cryptography (SGC-PKC), is the enhanced version of Certificateless Public Key Cryptography (CL-PKC). It preserves all advantages of CLPKC. Similar to CL-PKC, every user is given a partial private key by the KGC and generates his own private key and corresponding public key. In addition, it can defend against the Denialof- Decryption (DoD) Attack. In this paper, we propose a new approach to construction SGC-PKE scheme that derived from a new application of chameleon hash and give a concrete scheme. It is the first scheme which has flexible public key and reaches Girault's trusted level 3, the same level as is enjoyed in a traditional PKI.     

Turncoat Polypeptides: We Adapt to Our Environment

A common interpretation of Anfinsen's hypothesis states that one amino acid sequence should fold into a single, native, ordered state, or a highly similar set thereof, coinciding with the global minimum in the folding-energy landscape, which, in turn, is responsible for the function of the protein. However, this classical view is challenged by many proteins and peptide sequences, which can adopt exchangeable, significantly dissimilar conformations that even fulfill different biological roles. The similarities and differences of concepts related to these proteins, mainly chameleon sequences, metamorphic proteins, and switch peptides, which are all denoted herein “turncoat” polypeptides, are reviewed. As well as adding a twist to the conventional view of protein folding, the lack of structural definition adds clear versatility to the activity of proteins and can be used as a tool for protein design and further application in biotechnology and biomedicine.     

基于变色龙认证树的云边端协同流式数据完整性验证模型

物联网环境中的终端设备会产生大量的流式数据,如环境感知数据、工业控制数据、人体健康数据等,这些数据全部上传到云服务器会造成巨大的网络负担,云边协同的计算方式能够极大地缓解网络带宽以及云服务器的计算压力,加快数据的处理,提升服务响应能力。但是,云边协同计算同样面临着数据被窃取、篡改等问题。这些承载着重要信息的流式数据一旦遭到窃取或篡改,很可能造成严重的损失。为此,文章基于流式数据完整性验证重要方法——变色龙认证树,构建了一个支持数据机密性的云边端协同流式数据完整性验证模型(Cloud-edge-device Collaborative Integrity Verification Scheme for Streaming Data,CCIVS-SD),该模型包括5种实体:终端设备、边缘节点、云服务器、数据使用者和可信任第三方。文章给出模型的实体构成、形式化定义以及通信协议,并对模型进行分析,结果表明该模型能够完成流式数据插入、查询和完整性验证,并且能够保护数据的机密性。     

Contextual Counterpoint

In recent decades, conservationists and planners have co-opted contextualism, reducing it to a tool for enforcing urban conformity. Here Charles Jencks reclaims contextualism as a dynamic design strategy. He identifies four different contextual treatments that as well as ensuring continuity are potentially transformative. Copyright © 2011 John Wiley & Sons, Ltd.     

基于数据处理与若干群体算法优化的GRU/LSTM水质时间序列预测

为提高水质时间序列预测精度,提出一种基于小波包变换（WPT）和变色龙优化算法（CSA）、猎豹优化（CO）算法和山瞪羚优化（MGO）算法的优化门限循环控制单元（GRU）、长短期记忆神经网络（LSTM）的预测模型。首先利用WPT对pH值、DO、COD_Mn、NH₃—N时间序列进行平稳化处理,得到若干个规律性较强的子序列分量;其次简要介绍了CSA、CO、MGO算法原理,利用CSA、CO、MGO分别寻优GRU、LSTM超参数,建立WPT-CSA-GRU、WPT-CO-GRU、WPT-MGO-GRU、WPT-CSA-LSTM、WPT-CO-LSTM、WPT-MGO-LSTM模型;最后利用所建立的模型对pH值及DO、COD_Mn、NH₃—N浓度各分量进行预测和重构,并建立WPT-GRU、WPT-LSTM和WPT-CSA-SVM、WPT-CO-SVM、WPT-MGO-SVM模型作对比分析模型,以云南省昆明市观音山断面为例,通过pH值及DO、COD_Mn、NH₃—N浓度预测对模型进行了验证。结果表明：WPT-CSA-GRU、WPT-CO-GRU、WPT-MGO-GRU、WPT-CSA-LSTM、WPT-CO-LSTM、WPT-MGO-LSTM模型对实例pH值及DO、COD_Mn、NH₃—N浓度的预测精度优于其他对比模型,具有较好的预测效果,其中尤以WPT-CSA-GRU、WPT-CO-GRU、WPT-MGO-GRU模型的预测精度最高;CSA、CO、MGO能有效调优GRU、LSTM超参数,显著提高GRU、LSTM预测性能;所构建的6种模型预测精度高且计算规模小,是有效的水质时间序列预测模型,可为相关水质预测研究提供参考。