Accurate P2P traffic identification based on data transfer behavior

Peer-to-Peer (P2P) technology is one of the most popular techniques nowadays, and accurate identification of P2P traffic is important for many network activities. The classification of network traffic by using port-based or payload-based analysis is becoming increasingly difficult when many applications use dynamic port numbers, masquerading techniques, and encryption to avoid detection. A novel method for P2P traffic identification is proposed in this work, and the methodology relies only on the statistics of end-point, which is a pair of destination IP address and destination port. Features of end-point behaviors are extracted and with which the Support Vector Machine classification model is built. The experimental results demonstrate that this method can classify network applications by using TCP or UDP protocol effectively. A large set of experiments has been carried over to assess the performance of this approach, and the results prove that the proposed approach has good performance both at accuracy and robustness.

Accurate Classification of P2P Traffic by Clustering Flows

P2P traffic has always been a dominant portion of Internet traffic since its emergence in the late 1990s. The method used to accurately classify P2P traffic remains a key problem for Internet Service Producers （ISPs） and network managers. This paper proposes a novel approach to the accurate classification of P2P traffic at a fine-grained level, which depends solely on the number of special flows during small time intervals. These special flows, named Clustering Flows （CFs）, are de- fined as the most frequent and steady flows generated by P2P applications. Hence we are able to classify P2P applications by detecting tlle appearance of corresponding CFs. Com- pared to existing approaches, our classifier can realise high classification accuracy by ex- ploiting only several generic properties of flows, instead of extracting sophisticated fea- tures from host behaviours or transport layer data. We validate our framework on a large set of P2P traffic traces using a Support Vector Machine （SVM）. Experimental results show that our approach correctly classifies P2P ap- plications with an average true positive rate of above 98% and a negligible false positive rate of about 0.01%.

P2P Streaming Traffic Classification in High-Speed Networks

The growing P2P streaming traffic brings a variety of problems and challenges to ISP networks and service providers.A P2P streaming traffic classification method based on sampling technology is presented in this paper.By analyzing traffic statistical features and network behavior of P2P streaming,a group of flow characteristics were found,which can make P2P streaming more recognizable among other applications.Attributes from Netflow and those proposed by us are compared in terms of classification accuracy,and so are the results of different sampling rates.It is proved that the unified classification model with the proposed attributes can identify P2P streaming quickly and efficiently in the online system.Even with 1:50 sampling rate,the recognition accuracy can be higher than 94%.Moreover,we have evaluated the CPU resources,storage capacity and time consumption before and after the sampling,it is shown that the classification model after the sampling can significantly reduce the resource requirements with the same recognition accuracy.

EPFIA: Extensible P2P Flows Identification Architecture

The fundament of managing P2P traffic is identifying various P2P flows accurately. Although many P2P flows identification methods are presented nowadays, there are no ideas for either integrating these independent methods together or being extended fast to support new method. In this work, an extensible P2P flows identification architecture (EPFIA for short) is proposed. In order to identify many specific P2P flows, EPFIA uses many different identification methods simultaneously, and obtains the highest efficiency via adjusting their identification sequence. An online mechanism of renewing identification methods is designed, which can extend new identification method without compiling the whole program. Applying policy mechanism, identification methods can be updated, started and halted remotely. The experiment results of running the prototype system show us that EPFIA could effectively promote the performance of system and support online renew P2P identification methods and manage them remotely.

Research on P2P Traffic Monitoring System based on DPI Technology

This paper focuses on the key technologies of P2P technology and network traffic monitoring, which focuses on AC automaton and bypass interference control technology, and on based of it, we design a new P2P traffic monitoring system. The system uses DPI and DFI recognition technology, as well as straight loss and bypass interference control technology, basically meet the recognition and control of P2P traffic. Finally, the test results show that this system recognition accuracy of P2P traffic is high, good control effect, function and performance meet the design requirements.

Identifying file-sharing P2P traffic based on traffic characteristics

This article focuses on identifying file-sharing peer-to-peer （P2P） （such as BitTorrent （BT）） traffic at the borders of a stub network. By analyzing protocols and traffic of applications, it is found that file-sharing P2P traffic of a single user differs greatly from traditional and other P2P （such as QQ） applications＇ traffic in the distribution of involved remote hosts and remote ports. Therefore, a method based on discreteness of remote hosts （RHD） and discreteness of remote ports （RPD） is proposed to identify BT-like traffic. This method only relies on flow information of each user host in a stub network, and no packet payload needs to be monitored. At intervals, instant RHD for concurrent transmission control protocol and user datagram protocol flows for each host are calculated respectively through grouping flows by the stub network that the remote host of each flow belongs to. On given conditions, instant RPD are calculated through grouping flows by the remote port to amend instant RHD. Whether a host has been using a BT-like application or not can be deduced from instant RHD or average RHD for a period of time. The proposed method based on traffic characteristics is more suitable for identifying protean file-sharing P2P traffic than content-based methods Experimental results show that this method is effective with high accuracy.

Fine-grained P2P traffic classification by simply counting flows

The continuous emerging of peer-to-peer(P2P) applications enriches resource sharing by networks, but it also brings about many challenges to network management. Therefore, P2 P applications monitoring, in particular,P2 P traffic classification, is becoming increasingly important. In this paper, we propose a novel approach for accurate P2 P traffic classification at a fine-grained level. Our approach relies only on counting some special flows that are appearing frequently and steadily in the traffic generated by specific P2 P applications. In contrast to existing methods, the main contribution of our approach can be summarized as the following two aspects. Firstly, it can achieve a high classification accuracy by exploiting only several generic properties of flows rather than complicated features and sophisticated techniques. Secondly, it can work well even if the classification target is running with other high bandwidth-consuming applications, outperforming most existing host-based approaches, which are incapable of dealing with this situation. We evaluated the performance of our approach on a real-world trace. Experimental results show that P2 P applications can be classified with a true positive rate higher than 97.22% and a false positive rate lower than 2.78%.

P2P network traffic control mechanism based on global evaluation values

Peer-to-peer（P2P） computing technology has been widely used on the Internet to exchange data. However, it occupies much network bandwidth, and thus greatly influences traditional business on the Internet. Besides, problems about free-riders and ＇tragedy of the commons＇ in the P2P environment estrange from it P2P users who constantly contribute to the network with quality resources. This article proposes a new P2P network traffic control mechanism based on global evaluation values. It aims to help individual users to avoid peak traffic time as much as possible, ease network congestion and protect traditional business on the Internet, as well as differentiating priority grades of peers according to their contributions and stimulating them to share their valuable resources actively. This article first analyzes the current state of network traffic, and then elaborates on P2P network traffic control policies and proposes the peer＇s priority level differentiation mechanism based on global evaluation values. Finally, after the testing results and analysis of the proposed P2P network traffic control mechanism are discussed, conclusions are drawn.

Anchor Vertex Selection for Enhanced Reliability of Traffic Offloading Service in Edge-Enabled Mobile P2P Social Networks

As the rapid growth of mobile social networks,mobile peer-to-peer(P2P)communications and mobile edge computing(MEC)have been developed to reduce the traffic load and improve the computation capacity of cellular networks.However,the stability of social network is largely ignored in the advances of P2P and MEC,which is related to the social relations between users.It plays a vital role in improving the efficiency and reliability of traffic offloading service.In this paper,we integrate an edge node and the nearby P2P users as a mobile P2P social network and introduce the problem of adaptive anchored(k,r)-core to maintain the stability of multiple mobile P2P networks.It aims to adaptively select and retain a set of critical users for each network,whose participation is critical to overall stability of the network,and allocate certain resource for them so that the maximum number of users of all networks will remain engaged and the traffic of cellular network can be minimized.We called the retained users as anchor vertices.To address it,we devise a peer-edge-cloud framework to achieve the adaptive allocation of resources.We also develop a similarity based onion layers anchored(k,r)-core(S-OLAK)algorithm to explore the anchor vertices.Experimental results based on a real large-scale mobile P2P data set demonstrate the effectiveness of our method.

Ghosts in the shell:identification of microglia in the human central nervous system by P2Y12 receptor

Microglia are the tissue resident macrophages of the brain and represent the sole immune population located in the parenchyma of the central nervous system （CNS）. These cells are hidden be-tween neurons, astrocytes as well as oligodendrocytes and account for only 5-10% of CNS cells. Even though microglia were already identified in 1913 by the Spanish neuroanatomist Ramon y Cajal and further seminally investigated by his student Pio del Rio Hortega,

分枝杆菌菌种快速荧光初步鉴定方法的研究

目的 使用液体培养基 ,建立一种分枝杆菌 (Mycobacterium)菌种初步鉴定的非放射快速荧光检测法。方法 应用自制的非放射荧光检测管 ,利用水溶性对硝基苯甲酸 (P NitrobenzoicAcid ,PNB)和噻吩 - 2 -羧酸肼 (2 Thiophenecarborylicacidhydrazide ,TCH)对 15株分枝杆菌标准菌株和 78株分枝杆菌临床分离菌株做体外抑菌试验 ,确定其在菌群鉴定试验中的应用浓度。结果 PNB的应用浓度为 10 0 μg/ml ,可有效地区别结核杆菌复合群与非结核分枝杆菌 ;TCH的应用浓度为 2 .5 μg/ml ,可有效地区别结核分枝杆菌和牛分枝杆菌。菌群鉴定结果 7～ 10d可得到报告。结论 本法经济实用 ,并将分枝杆菌菌群鉴定结果报告时间由传统的L J方法的 2 8d缩短为 7～ 10d。

罗丹明B试法鉴定Tl^(3+)用NaNTU消除Au^(3+)和H^(2+)的干扰

在实验的基础上 ,提出了在用罗丹明B试法鉴定Tl3+ 时 ,用N -烯丙基 -N′ - (对苯磺酸钠 )硫脲掩蔽Au3+ 和H 2 + 离子的干扰 ,与传统的消除干扰的方法相比 ,具有条件容易控制、操作简便。

罗丹明B试法鉴定UO_2^(2+)用N-烯丙基-N′-(对苯磺钠)硫脲掩蔽Fe^(3+)的干扰

以实验为基础 ,提出了用罗丹明 B试法鉴定 UO2 +2 时 ,用 N-烯丙基 - N′- (对苯磺酸钠 )硫脲掩蔽Fe3 +离子的干扰 .与传统的消除干扰的方法相比 ,具有条件容易控制 ,操作简便等优点 .

N-烯丙基-N′-(对苯磺酸钠)硫脲在Sr^(2+)的鉴定中对干扰离子的掩蔽作用

以实验为基础 ,提出了用玫瑰红酸钠试法鉴定 Sr2 +时 ,用 N-烯丙基 -N′-(对苯磺酸钠 )硫脲同时掩蔽 Ag+、Au3 +、Hg2 +三种离子对鉴定 Sr2 +离子的干扰的简便有效的方法 .

A Proximity-Aware BitTorrent System via Tracker-Side Biased Neighbor Selection

To address cross-ISP traffic problem caused by BitTorrent,we present our design and evaluation of a proximity-aware BitTorrent system. In our approach,clients generate global proximity-aware information by using landmark clustering;the tracker uses this proximity to maintain all peers in an orderly way and hands back a biased subset consisting of the peers who are physically closest to the requestor. Our approach requires no co-operation between P2P users and their Internet infra structures,such as ISPs or CDNs,no constantly path monitoring or probing their neighbors. The simulation results show that our approach can not only reduce unnecessary cross-ISP traffic,but also allow downloadsing fast.

N—烯丙基—N′—(对苯磺酸钠)硫脲在锑的鉴定中对干扰离子的掩蔽作用

本文以实验为基础，提出了用罗丹明Ｂ试法鉴定Ｓｂ（Ｖ）时，用Ｎ—烯丙基—Ｎ′—（对苯磺酸钠）硫脲同时掩蔽Ｈｇ２＋、Ｂｉ３＋、Ｆｅ３＋、Ａｕ３＋四种离子对鉴定Ｓｂ（Ｖ）的干扰的简便有效的方法。

草酸铵试法鉴定Ca^(2+)用NaNTU掩蔽Ag^+和Hg^(2+)

在实验的基础上,提出了用草酸铵试法鉴定钙时,用N-烯丙基-N′-(对苯磺酸钠)硫脲掩蔽Ag+和Hg2+离子干扰,与传统的H2S沉淀消除的干扰的方法相比,具有操作简便、条件易控制、无污染等优点.

采油用调剖剂中对溴乙基苄氯的合成与鉴定

本文根据有机合成原理设计了对溴乙基苄氯的合成路线并对合成的条件进行了优化,然后提纯产品,通过熔点测定、薄层色谱(TLC)、红外谱图(IR)、质谱(MS)和核磁共振谱图(NMR)对产品进行结构鉴定。结果表明,此产品即所需目标产物。

巴戟天中环烯醚萜苷和蒽醌在电喷雾离子源负离子模式下的质谱裂解行为

利用电喷雾-四极杆-飞行时间串联质谱(ESI-Q-TOF MS/MS)技术,在负离子模式下,探讨巴戟天中4种环烯醚萜苷和2种蒽醌成分的质谱裂解途径。通过[M-H]-获得化合物的相对分子质量信息,进一步对[M-H]-进行碰撞诱导解离,获得相应化合物的裂解途径。结果表明,环烯醚萜苷主要的裂解途径是首先脱去母环上的功能基团,如中性丢失H_2O、CO_2、CH_3COOH和糖单元等部分;其次是二氢吡喃环和糖环的断裂,m/z113、101为环烯醚萜苷母环断裂的特征碎片离子。蒽醌类化合物的裂解行为是连续失去CO,也可以失去CO_2。这些质谱裂解行为的研究有助于环烯醚萜苷和蒽醌类化合物的结构解析,也可为其他同类化合物的鉴定提供依据。

青钱柳叶乙酸乙酯部位化学成分的研究

目的研究我国特有植物青钱柳叶中的化学成分。方法利用硅胶色谱法、Sephadex LH-20柱色谱和半制备HPLC等技术手段进行分离纯化,并通过波谱学方法鉴定化合物的结构。结果从青钱柳叶的乙酸乙酯提取物中分离出11个化合物,分别为鉴定为hirsutrin(1)、高山苷B(2)、山柰酚(3)、sterubin(4)、丁香酸(5)、香草酸(6)、2-羟基-5-甲氧基苯甲酸(7)、2-methoxy-4-hydroxycinnamic acid(8)、cis-p-hydroxycinnamic acid(9)、对羟基苯甲酸(10)和对羟基苯甲醛(11)。结论除化合物3和6外其他化合物是首次从该植物中分离得到。