Motivated by the lack of ready-to-use solutions, in this paper we present a flexible and accessible toolkit for structure and content mining, able to crawl, download, extract and index resources from the Web.
by optimizing query results) and enforcing data/user security (e.g.
Possible benefits include improving user experience (e.g. Searching and retrieving information from the Web is a primary activity needed to monitor the development and usage of Web resources. ( Paper, pdf) ĭesign, Implementation and Test of a Flexible Tor-Oriented Web Mining Toolkit Our findings show that, among other things, the graph of Tor hidden services presents some of the character- istics of social and surface web graphs, along with a few unique peculiarities, such as a very high percentage of nodes having no outbound links. In doing so, other than assessing the renowned volatility of Tor hidden services, we make it possible to distinguish time dependent and structural aspects of the Tor graph. We separately study these three graphs and their shared "stable" core. We consider three different snapshots obtained by extensively crawling Tor three times over a 5 months time frame. In this paper, we describe the topology of the Tor graph (aggregated at the hidden service level) measuring both global and local properties by means of well-known metrics. Something that still remains largely unknown is the structure of the graph defined by the network of Tor services. Other work aimed at estimating the number of available hidden services and classifying them. So far, most research work on the Tor network aimed at discovering protocol vulnerabilities to de-anonymize users and services. Tor hidden services allow offering and accessing various Internet resources while guaranteeing a high degree of provider and user anonymity. Spiders like Onions: on the Network of Tor Hidden Services Finally, a broad interesting set of novel insights/considerations over the Tor Web organization and content are provided. Among its contributions: a study on automatic Tor Web exploration/data collection approaches the adoption of novel representative metrics for evaluating Tor data a novel in-depth analysis of the hidden services graph a rich correlation analysis of hidden services' semantics and topology. The present paper aims at addressing such lack of information. Even less is known on the relationship between content similarity and topological structure. Since there are no foolproof techniques for automatically discovering Tor hidden services, little or no information is available about the topology of the Tor Web graph. The attention of the research community has focused on assessing the security of the Tor infrastructure (i.e., its ability to actually provide the intended level of anonymity) and on discussing what Tor is currently being used for. However, the unique characteristics of the Tor network limit the applicability of standard techniques and demand for specific algorithms to explore and analyze it. The exploration and analysis of Web graphs has flourished in the recent past, producing a large number of relevant and interesting research results. Other than guaranteeing an anonymous access to normal websites, Tor allows running anonymous and untraceable services, known as hidden services, that can only be accessed using a Tor-enabled browser.Įxploring and Analyzing the Tor Hidden Services Graph Its servers, run by volunteers over the Internet, work as routers to allow Tor users to access the Internet anonymously, evading traditional network surveillance and traffic analysis mechanisms. It is a communication network designed as a low-latency, anonymity-guaranteeing and censorship-resistant network, relying on an implementation of the so-called onion routing protocol. Among darknets, Tor ( The Onion Router) is probably the most known and used. This is the collection of web resources that exist on darknets, describable as overlay networks, which despite leaning on the public Internet require specific software, configuration or authorization to access. Web mining becomes an even more interesting/challenging task when the target includes the submerged Internet contents usually known as "deep" Web not crawled/indexed by traditional search engines.Ī recent research trend is especially focused on the subset of the deep Web usually called "dark" Web. As the Web has become the main means for information exchange and retrieval, a whole body of work focuses on gaining a better understanding of its content and shape, in order to improve usability and security.
0 kommentar(er)
