域名信息主动获取及备份系统的设计和实现*

为解决因国外根/顶级域名系统无法提供域名解析服务而影响我国互联网正常运行的问题,设计并实现了一种高效的DNS信息获取及备份恢复系统。通过被动获取DNS数据包与主动发送DNS请求相结合的方式,可获取网络中活跃的域名信息。利用基于可变长请求队列的发送速度自适应方法来有效控制请求效率,以适应网络带宽和DNS服务器负载。详细介绍了整个系统的设计和实现,并进行了性能测试与分析。该系统对建设国家根/顶级域名备份恢复系统具有重要参考价值。     

一种高效的DNS日志压缩算法

CN顶级域名的DNS日志从分布式站点传输到数据处理中心时,对海量数据存储和传输带宽提出极大挑战。针对该问题,提出一种高效的DNS日志压缩算法,利用DNS查询类型的冗余性和DNS查询时间、IP地址和域名等的重复性进行DNS日志压缩。实验结果证明了DNS日志压缩算法在DNS实时监控和分析系统中部署的有效性和高效性。     

海量域名日志数据分析与可视化研究及应用*

针对域名数据数量巨大且具有时空特征的特点,利用地理信息系统时空分析以及可视化的技术和方法对中国国家级域名.cn日志数据进行分析和研究。通过对域名数据的分析,了解域名解析总体规律及特征,得到热点域名及域名中蕴含的时空分布规律,为域名业务规划、服务站点布局调整提供分析数据。最后提出一种基于模拟退火算法的DNS站点优化布局方法,实验结果表明该方法可用于指导DNS服务站点的布局及DNS解析服务的调整,为.cn域名服务的整体布局提供决策依据。     

关键词

CN域名 国际互联网上的中国标识。 域名作为一种互联网络地址资源,利用遵循一定编码规则的字符形式,通过与IP地址之间的对应和转换,对互联网络上联网计算机进行定位与识别,从而实现各种网络应用服务(如网站访问、电子邮件、文件传输)。 CN域名是由我国管理的国家顶级域名,在国际互联网上代表中国。近年来,CN域名已经成为全球增长最快的国家顶级域名之一。     

一种基于域名错误的DNS重定向协议①

域名系统（DNS）重定向是为互联网服务提供商（ISP）和DNS应用服务提供商（ASP）的用户实现增值服务的有效功能。定义以不同于错误查询域名的按相关性排序的推荐域名列表作为错误描述。提出重定向服务器的两个转交过程,以利于正确及时地找到推荐域名。此外,提出使用延长资源记录的请求处理算法。定义重定向报文结构以在DNS协议内容纳重定向IP地址信息。     

基于文本和DNS查询的非常规域名检测研究

在钓鱼网站、远控木马等网络攻击中常使用大量的非常规域名。面对海量域名,已有非常规域名检测方法准确性有待提高。基于对使用非常规域名的网络攻击特征,以及对已有非常规域名检测方法的研究,提出了域名伪装特征,分隔特征域名标签被数字分割的最大单元数,DNS查询特征:单次DNS查询返回的IP个数和DNS查询返回IP集合的平均杰卡德距离;改进了发音特征域名元音字母占比。此外,提出一种基于文本特征和DNS查询特征的非常规域名检测方法,其中选取了新定义的特征,以及若干其他域名基本特征、发音特征和分隔特征,并基于机器学习方法区分常规域名和非常规域名。实验结果表明,提出的非常规域名检测方法与部分已有方法相比准确率有较大提高,可用于检测使用了非常规域名的恶意网络攻击。     

基于W-Kmeans算法的DNS流量异常检测

为了对DNS查询进行有效检测,及时发现DNS流量异常,提出了适合于检测DNS流量异常的权重Kmeans (WKmeans)算法.对CN顶级域2009年5月19日的原始查询日志抽取有用信息,提取相关的向量特征,对不同的向量特征赋予不同的权重值.利用W-Kmeans算法对查询日志进行聚类检测,并分析了算法各种参数选择的影响.5.19事件的DNS查询检测结果表明,W-Kmeans算法可以有效检测DNS流量异常的发生.     

注册CN二级域名了吗？

7月9日.我国四大CN域名注册服务商联合宣布,将在国家域名注册管理机构中国互联网络信息中心(CNNIC)的指导下,在全国范围共推CN顶级域名注册。实际上,早在3月17日,中国互联网信息中心就对外宣布:CN二级域名全面开放,广大用户可以按照“先到先得”的原则在中国国家顶级域名CN下直接申请注册自己喜欢的域名,如www.xxx.cn。中国互联网信息中心(CNNIC)工作委员会副主任钱华林曾表示:“CNNIC将努把CN作成网络世界中标识中国身份的首选。” 目前广大行业企业用户对CN二级域名注册的反应如何?他们的域名注册和域名使用现状是什么?如何看待域名问题?本期采访了北京饭店,中国平安保险公司、哈药集团、华泰财产保险、北方工业大学等24家知名企事业单位的信息主管。     

域名服务体系安全问题研究

域名服务是互联网的基础服务。域名服务体系不同于域名系统(DNS),仅提高域名系统的安全并不能解决整个域名服务的安全问题。基于中国互联网络信息中心运行国家CN域名的经验,创新的提出域名服务体系的概念,并对域名服务体系的安全问题进行了论述分析。首先介绍了域名系统的基础知识及全球域名体系,然后研究分析了域名服务体系中的5个主要角色和7个主要数据流,结合数据流分析了其中主要的安全问题,并提出了安全防范措施。     

速变服务网络行为特征分析

速变(Fast-Flux)服务网络通过返回不断变化的DNS解析结果,以大量被攻陷主机的IP地址作为服务地址,利用被攻陷主机进行重定向形成服务网络。长时间跟踪并记录了分布在全球6大洲的300个DNS服务器对23000多个域名的解析结果。根据DNS解析数据,文章对比其他研究成果从多个维度对Fast-Flux恶意域名和Fast-Flux服务网络的行为特征进行了全面讨论,并进一步开展特征辨识度分析。关于 Fast-Flux 服务网络行为特征的分析揭示了FFSN新的行为变化,为恶意域名检测、网络资源保护等提供了依据。     

Query verification schemes for cloud-hosted databases: a brief survey

Database query verification schemes provide correctness guarantees for database queries. Typically such guarantees are required and advisable where queries are executed on untrusted servers. This need to verify query results, even though they may have been executed on one’s own database, is something new that has arisen with the advent of cloud services. The traditional model of hosting one’s own databases on one’s own servers did not require such verification because the hardware and software were both entirely within one’s control, and therefore fully trusted. However, with the economical and technological benefits of cloud services beckoning, many are now considering outsourcing both data and execution of database queries to the cloud, despite obvious risks. This survey paper provides an overview into the field of database query verification and explores the current state of the art in terms of query execution and correctness guarantees provided for query results. We also provide indications towards future work in the area.     

Querying a messy web of data with Avalanche

Recent efforts have enabled applications to query the entire Semantic Web. Such approaches are either based on a centralised store or link traversal and URI dereferencing as often used in the case of Linked Open Data. These approaches make additional assumptions about the structure and/or location of data on the Web and are likely to limit the diversity of resulting usages.In this article we propose a technique called Avalanche, designed for querying the Semantic Web without making any prior assumptions about the data location or distribution, schema-alignment, pertinent statistics, data evolution, and accessibility of servers. Specifically, Avalanche  finds up-to-date answers to queries over SPARQL endpoints. It first gets on-line statistical information about potential data sources and their data distribution. Then, it plans and executes the query in a concurrent and distributed manner trying to quickly provide first answers.We empirically evaluate Avalanche  using the realistic FedBench data-set over 26 servers and investigate its behaviour for varying degrees of instance-level distribution “messiness” using the LUBM synthetic data-set spread over 100 servers. Results show that Avalanche  is robust and stable in spite of varying network latency finding first results for 80% of the queries in under 1 s. It also exhibits stability for some classes of queries when instance-level distribution messiness increases. We also illustrate, how Avalanche  addresses the other sources of messiness (pertinent data statistics, data evolution and data presence) by design and show its robustness by removing endpoints during query execution.     

Effcient Distributed Skyline Queries for Mobile Applications

In this paper, we consider skyline queries in a mobile and distributed environment, where data objects are distributed in some sites (database servers) which are interconnected through a high-speed wired network, and queries are issued by mobile units (laptop, cell phone, etc.) which access the data objects of database servers by wireless channels. The inherent properties of mobile computing environment such as mobility, limited wireless bandwidth, frequent disconnection, make skyline queries more complicat...     

一种入侵容忍的密钥分发方案

提出了一种入侵容忍的密钥分发方案。在该方案中，密钥的生成由若干服务器通过秘密共享机制协作完成，每个服务器并不知道所生成的密钥，只持有其秘密份额。密钥分发的过程同样基于秘密共享实现，由用户获取各服务器所持有的秘密份额进行恢复从而获取密钥。分析表明，该方案中不存在唯一失效点，即使一定数量的服务器被攻击者控制后，系统仍然可以完成密钥分发。     

‘MaaS’: fast retrieval of E-file in cloud using metadata as a service

In cloud era as the data stored is enormous, efficient retrieval of data with reduced latency plays a major role. In cloud, owing to the size of the stored data and lack of locality information among the stored files, metadata is a suitable method of keeping track of the storage. This paper describes a novel framework for efficient retrieval of data from the cloud data servers using metadata with less amount of time. Performance of queries due to availability of files for query processing can be greatly improved by the efficient use of metadata and its analysis thereof. Hence this paper proposes a generic approach of using metadata in cloud, named ‘MaaS—Metadata as a Service’. The proposed approach has exploited various methodologies in reducing the latency during data retrieval. This paper investigates the issues on creation of metadata, metadata management and analysis of metadata in a cloud environment for fast retrieval of data. Cloud bloom filter, a probabilistic data structure used for efficient retrieval of metadata is stored across various metadata servers dispersed geographically. We have implemented the model in a cloud environment and the experimental results show that methodology used is efficient on increasing the throughput and also by handling large number of queries efficiently with reduced latency. The efficacy of the approach is tested through experimental studies using KDD Cup 2003 dataset. In the experimental results, proposed ‘MaaS’ has outperformed other existing methods.     

A two-phase queuing system with access control and correlated arrival processes

A two-phase queuing system with access control is studied whose first phase consists of an infinite number of servers, while the second one consists of a finite number of servers. To the first phase, a Markovian input flow of queries arrives. On completion of the first-phase service, the customer either leaves the system or is passed to the second phase. In addition, a Markovian input flow of queries that do not require any first-phase service arrives to the second phase. An algorithm for finding a steady-state distribution of the system’s state probabilities is given, and some problems of the system’s paramaters optimization are considered.     

Efficient Distributed Skyline Queries for Mobile Applications

In this paper, we consider skyline queries in a mobile and distributed environment, where data objects are distributed in some sites (database servers) which are interconnected through a high-speed wired network, and queries are issued by mobile units (laptop, cell phone, etc.) which access the data objects of database servers by wireless channels. The inherent properties of mobile computing environment such as mobility, limited wireless bandwidth, frequent disconnection, make skyline queries more complicated. We show how to efficiently perform distributed skyline queries in a mobile environment and propose a skyline query processing approach, called efficient distributed skyline based on mobile computing (EDS-MC). In EDS-MC, a distributed skyline query is decomposed into five processing phases and each phase is elaborately designed in order to reduce the network communication, network delay and query response time. We conduct extensive experiments in a simulated mobile database system, and the experimental results demonstrate the superiority of EDS-MC over other skyline query processing techniques on mobile computing.     

Boolean similarity measures for resource discovery

As the number of Internet servers increases rapidly, it becomes difficult to determine the relevant servers when searching for information. The authors develop a new method to rank Internet servers for Boolean queries. Their method reduces time and space complexity from exponential to polynomial in the number of Boolean terms. They contrast it with other known methods and describe its implementation     

WWW集群服务器的数据副本分布方式研究

为了有效地提高WWW服务器的吞吐能力、反应速度和可扩展性,国际上许多著名站点纷纷转向采用WWW集群服务器来替代原有的单一主机服务器.采用不同副本分布方式的WWW集群服务器,其数据可靠性也有所不同.对不同数据副本分布方式进行探讨,同时,论证了最优副本分布方案.     

Distributed top-k query processing by exploiting skyline summaries

Recently, a trend has been observed towards supporting rank-aware query operators, such as top-k, that enable users to retrieve only a limited set of the most interesting data objects. As data nowadays is commonly stored distributed over multiple servers, a challenging problem is to support rank-aware queries in distributed environments. In this paper, we propose a novel approach, called DiTo, for efficient top-k processing over multiple servers, where each server stores autonomously a fraction of the data. Towards this goal, we exploit the inherent relationship of top-k and skyline objects, and we employ the skyline objects of servers as a data summarization mechanism for efficiently identifying the servers that store top-k results. Relying on a thresholding scheme, DiTo retrieves the top-k result set progressively, while the number of queried servers and transferred data is minimized. Furthermore, we extend DiTo to support data summarizations of bounded size, thus restricting the cost of summary distribution and maintenance. To this end, we study the challenging problem of finding an abstraction of the skyline set of fixed size that influences the performance of DiTo only slightly. Our experimental evaluation shows that DiTo performs efficiently and provides a viable solution when a high degree of distribution is required.