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In the era of the Internet, people are active in multiple online services, and they usually have accounts on more than one online service. Each account is a virtual identity of the user. In order to trace individual's online behavior at any time and any places, linking virtual identities belonging to the same natural person across different online service domains is very important. Existing methods...
In-network caching is an important feature of ICN (Information Centric Networking). There are prior arts focusing on designing a highly efficient caching strategy by exploiting either node data or content data respectively. However, simply exploiting these data itself is not enough to reduce the cost of network operation and increase the quality of user experience, as there is no consideration on...
With the development of the Internet, e-commerce industry rises rapidly. Online shopping becomes more and more convenient and fast. However it is very difficult for consumers to find satisfied commodity because of abundant and mixed commodity. Especially when people purchase the items which they are not familiar with or consume in a strange place. The study of the recommended system is to figure out...
The detection of anomalies in network traffic, such as low volume attacks and abnormalities, has become a pressing problem in today’s large volume of Internet traffic. To this end, various anomaly detection techniques have been developed, including techniques based on long-range dependence (LRD) behavior estimation of network traffic. However, the existing LRD-based techniques analyze the aggregated...
The popularization of the Internet provide people with more quick and direct access to information channel, the network search data record the netizens' tens of thousands of search concerns and needs to provide the necessary data base for the research of social and economic behavior. Search behaviors' anonymity just can meet the venereal-disease suspected patients' privacy need. This paper will use...
This paper considers fundamental measurements which drive TCP flows: throughput, RTT and loss. It is clear that throughput is, in some sense, a function of both RTT and loss. In their seminal paper Padyhe et al [1] begin with a mathematical model of the TCP sliding window evolution process and come up with an equation showing that TCP throughput is (roughly) proportional to 1/RTT√p where p is the...
Self-service technologies appeal to service providers because they can standardize service delivery, reduce labor and service costs, and reach new consumers who are unreachable through the bricks-and-mortar channels. Our focus in this paper is on Internet banking. Scholars have proposed a variety of different models to explain the factors affecting Internet banking initial use intention formation...
According to the problem of the constant increase of internet data and the current Internet information retrieval system has been unable to meet the needs of data and information retrieval, this paper puts forward the data mining based Internet information retrieval system. The paper first uses data mining to excavate association rules, and evaluates the entire behavior simulation of users resources...
We design a user interest model based on ordered pair behavior in order to improve the stabilization of the existing models. An innovation in this paper is the view that user interest model can be organized by user ordered pair behavior relevance. The main idea is to accumulate the value of user behavior, and then subtract the behavior value of some unrelated behavior according to the proportion of...
The Content Distribution Networks (CDN) are based on one of the most fruitful ideas in nowadays Internet. There is an increasing competition between CDN providers that place their Web servers in various locations, closer to end users. The future Internet solutions have to assure however that users are not only able to observe the live events and download different content via caching systems, but...
We present our initial experimental findings from the collaborative deployment of network Anomaly Detection (AD) sensors. Our system examines the ingress http traffic and correlates AD alerts from two administratively disjoint domains: Columbia University and George Mason University. We show that, by exchanging packet content alerts between the two sites, we can achieve zero-day attack detection capabilities...
The real data of the network traffic were analyzed to find out characteristic parameters for autonomic provisioning. An observed strong non-linearity (bursts) leads to heteroskedastic (time dependent conditional variance) model applications. The non-linear time series model and statistical method were applied. It was found that upper limit of burst variations could be quantitatively estimated with...
The wireless networked sensors embedded with everyday objects will become an integral part of Future Internet, where the interaction among people, computer and those objects will shift the current Internet to a new paradigm, namely the Internet of Things. The terabyte torrent of data generated by billions of sensors belonging to a large number of distributed heterogeneous sensor networks in Future...
The rapidly increasing series of Internet-scale disrupted threat is a pressing problem for every organization that utilizes the network. Many research institutions focus on collaborative security, of which collaborative intrusion detection is an important component. Sharing data among widely distributed intrusion detection systems is essential. To this end, IDWG (intrusion detection working group)...
The classification of network users is very important in user behavior analysis. The algorithm which was based entropy and latent Dirichlet allocation (LDA) was used in this paper. It is important but difficult to select an appropriate number of topics for a specific dataset. Entropy was first used to solve the problem. A concept named difference-entropy was built to determine the number of topics...
Research of self-similarity has been the focus of flow prediction due to the complexity of self-similar traffic, but the LRD (long range dependence) traffic has the disadvantages of the high modeling algorithm complexity and poor precision. Therefore we tried to propose a way that can make the LRD traffic change to SRD (short range dependence) which is more simple than LRD in the field of modeling...
This paper criticises the notion that long-range dependence is an important contributor to the queuing behaviour of real Internet traffic. The idea is questioned in two different ways. Firstly, a class of models used to simulate Internet traffic is shown to have important theoretical flaws. It is shown that this behaviour is inconsistent with the behaviour of real traffic traces. Secondly, the notion...
Recommendation systems are essentially solving a prediction problem where, given that p items have already been selected or rated by a user, the goal is to propose k target items most likely to be appreciated by her/him. Many models have been proposed to identify these target items but the results are not always satisfactory in practice because they often only include the most popular items and ignore...
Honeypots are flexible security tools for gathering artefacts associated with a variety of Internet attack activities. While existing work on honeypot traffic analysis focuses mainly on identifying existing attacks, this paper describes a technique for detecting new attacks based on principal component analysis. The proposed technique requires no prior knowledge of attack types and has low computational...
Understanding Internet link delay is an important key of taking full advantage of Internet resources. In this paper, we find that the link delay follows gamma distribution using maximum likelihood estimation based on data measured in a large-scale network. The correlations between the link delay and the edge load, the node degree, and the betweenness are analyzed respectively. The link delay distribution...
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