Fast Generation of Pointerless Octree Duals

Geometry processing applications frequently rely on octree structures, since they provide simple and efficient hierarchies for discrete data. However, octrees do not guarantee direct continuous interpolation of this data inside its nodes. This motivates the use of the octree's dual structure, which is one of the simplest continuous hierarchical structures. With the emergence of pointerless representations, with their ability to reduce memory footprint and adapt to parallel architectures, the generation of duals of pointerless octrees becomes a natural challenge. This work proposes strategies for dual generation of static or dynamic pointerless octrees. Experimentally, those methods enjoy the memory reduction of pointerless representations and speed up the execution by several factors compared to the usual recursive generation.     

Sharp lower bounds on the extractable randomness from non-uniform sources

Extraction of uniform randomness from (noisy) non-uniform sources is an important primitive in many security applications, e.g. (pseudo-)random number generators, privacy-preserving biometrics, and key storage based on Physical Unclonable Functions. Generic extraction methods exist, using universal hash functions. There is a trade-off between the length of the extracted bit string and the uniformity of the string. In the literature there are proven lower bounds on this length as a function of the desired uniformity. The best known bound involves a quantity known as smooth min-entropy. Unfortunately, there exist at least three definitions of smooth entropy. In this paper we compare three of these definitions, and we derive improved lower bounds on the extractable randomness.We also investigate the use of almost universal hash functions, which are slightly worse at extracting randomness than universal hash functions, but are preferable in practice because they require far less resources in devices. We show that using them has negligible effect on the extractable randomness.     

实时数据仓库中一种改进的数据流更新算法

为实现数据仓库中数据的高效集成,针对数据偏斜分布现象,提出一种改进的数据流更新算法EH-JOIN。该算法对传统散列连接方法进行改进,利用索引将部分频繁使用的主数据存储在内存中,解决了高速数据流下的磁盘频繁访问问题。实验结果表明,与MESHJOIN算法和R-MESHJOIN算法相比,EH-JOIN算法的服务速率在磁盘存储关系集保持适当大小时分别提高了96%和81%,在内存大小不同时提高了57%和48%。     

基于同态哈希函数的云数据完整性验证算法

云存储已经成为未来存储发展的一种趋势,但也带来新的安全挑战,如云服务提供商可能出于某种目的篡改数据。为确保云数据的完整性,提出一种基于同态哈希函数的云数据完整性检查算法。该算法在可信第三方的审计下,通过聚合多个RSA签名,对云数据进行完整性验证。为不泄露用户数据信息,采用同态线性认证与随机掩蔽技术,实现隐私保护。分析结果表明,该算法不仅能有效地抵抗服务器的恶意攻击,而且支持数据更新,与现有审计算法相比,该算法在验证过程中能减少计算代价,在批量审计中降低通信量,从而提高验证的效率。     

命名数据网络中基于Hash映射的命名检索

命名数据网络(NDN)是一种以内容为中心的新型网络架构,可有效提高网络资源的共享利用率。但与传统的IPv4、IPv6相比,NDN命名的长度更长且具有可变性,因此实现NDN中命名的快速检索对提高网络性能具有重要作用。为此,提出一种基于Hash映射的分治命名检索方法,将命名分解为组件并进行CRC32映射后分别存储在相应的Hash表中,对Hash表中的数据进行快速排序后使用二分查找定位Hash值,并利用排序后Hash表的递增数据结构进行Hash冲突的快速检测,通过对Hash值添加标志位的方法解决冲突问题。实验结果表明,相比建立命名前缀树的检索方法,该分治命名检索方法可将NDN命名的存储空间压缩近65%,并且大幅提升了检索速度。     

基于逐层剪枝的中文高频重复模式快速提取算法

为了从大规模语料中快速提取高频重复模式,以递增n-gram模型为基础,使用散列数据结构提取重复串,并提出了一种基于低频字符和层次剪枝的逐层剪枝算法,用于过滤低频垃圾字串,减少I/O读写次数。在此基础上,应用改进的字串排序算法,使字符串排序可在O(n)时间内完成,从而有效提高重复模式的提取效率。实验表明,该算法是一种有效的重复模式提取算法,其I/O读写次数同语料规模呈线性关系,远小于使用首字符进行语料划分的方法,能快速有效地从规模远大于内存容量的文本语料中提取重复模式,特别适合于大规模语料的高频重复模式提取,对以重复模式为基础的新词识别、术语抽取等具有重要的支撑作用。     

Improving the performance of Invertible Bloom Lookup Tables

Invertible Bloom Lookup Tables (IBLTs) have been recently introduced as an extension of traditional Bloom filters. IBLTs store key-value pairs. Unlike traditional Bloom filters, IBLTs support both a lookup operation (given a key, return a value) and an operation that lists out all the key-value pairs stored. One issue with IBLTs is that there is a probability that a lookup operation will return “not found” for a key. In this paper, a technique to reduce this probability without affecting the storage requirement and only moderately increasing the search time is presented and evaluated. The results show that it can significantly reduce the probability of not returning a value that is actually stored in the IBLT. The overhead of the modified search procedure, compared to the standard IBLT search procedure, is small and has little impact on the average search time.     

客户端垃圾邮件过滤系统的设计

垃圾邮件不仅浪费大量的网络资源,并且给用户带来很大的不便,如何有效地防范垃圾邮件,已成为网络信息安全领域的主要课题之一。本文通过对传统垃圾邮件过滤技术的分析,提出了一种基于指纹的定量过滤方法。对白名单和黑名单过滤、定时过滤、基于指纹的定量过滤和贝叶斯过滤技术进行了整合,建立了一种客户端垃圾邮件过滤系统的模型,该系统具有较高的过滤准确性,并且能适应用户的个性化需求。     

混合网中的P2P资源共享机制

为减轻对等网络（P2P）应用造成的IPv4网络带宽紧张问题,提出了一种IPv4/IPv6混合网中基于层次化分布式散列表（DHT）的P2P资源共享机制. 该机制使得IPv6和IPv4节点可查询和获得彼此DHT覆盖网中的P2P资源,实现P2P应用在IPv4/IPv6之间的互操作. 仿真结果表明,该P2P资源共享机制能够适应IPv4/IPv6混合网的特性,并具备很好的扩展性和负载均衡特性.      

一种有效的无序多图像分组及其拓扑有序化的算法

针对大规模三维重建应用中多幅无序图像的分组及其有序化问题,提出一种鲁棒的无序图像分组方法。首先,对大量无序图像提取SIFT(scale invariant feature transform)特征,接着采用DBH(dichotomy based hash)算法对图像特征集合进行快速匹配,最后应用一种新的基于图像内容的图像相似度度量准则,将无序图像分组并采用视图生成树拓扑化组内图像。实验结果表明,该算法能快速有效地对无序图像分类并拓扑化。