Malware distributions and graph structure of the Web

Knowledge about the graph structure of the Web is important for understanding this complex socio-technical system and for devising proper policies supporting its future development. Knowledge about the differences between clean and malicious parts of the Web is important for understanding potential treats to its users and for devising protection mechanisms. In this study, we conduct data science methods on a large crawl of surface and deep Web pages with the aim to increase such knowledge. To accomplish this, we answer the following questions. Which theoretical distributions explain important local characteristics and network properties of websites? How are these characteristics and properties different between clean and malicious (malware-affected) websites? What is the prediction power of local characteristics and network properties to classify malware websites? To the best of our knowledge, this is the first large-scale study describing the differences in global properties between malicious and clean parts of the Web. In other words, our work is building on and bridging the gap between \textit{Web science} that tackles large-scale graph representations and \textit{Web cyber security} that is concerned with malicious activities on the Web. The results presented herein can also help antivirus vendors in devising approaches to improve their detection algorithms

Local Structure in the Web

posterInternational audienceThe web graph has been widely adopted as the core describing the web structure [4]. However, little attention has been paid to the relationship betweenthe web graph and the location of the pages. It has already been noticed that links are often local (i.e. from a page to another page of the same server) and this can be used for efficient encoding of the web graph [9,7]. Locality in the web can be further modelled by the clustered graph induced by the prefix tree of URLs. The web tree's internal nodes are the commonprefixes of URLs and its leaves are the URLs themselves. A prefix ordering of URLs according to this tree allows to observe local structure in the web directly on the adjacency matrix M of the web graph. M splits in two terms : M = D + S, where D is diagonal by blocks and S is a very sparse matrix. The blocks of D that can be observed along the diagonal are sets of pages strongly related together

Local Structure in the Web

posterInternational audienceThe web graph has been widely adopted as the core describing the web structure [4]. However, little attention has been paid to the relationship betweenthe web graph and the location of the pages. It has already been noticed that links are often local (i.e. from a page to another page of the same server) and this can be used for efficient encoding of the web graph [9,7]. Locality in the web can be further modelled by the clustered graph induced by the prefix tree of URLs. The web tree's internal nodes are the commonprefixes of URLs and its leaves are the URLs themselves. A prefix ordering of URLs according to this tree allows to observe local structure in the web directly on the adjacency matrix M of the web graph. M splits in two terms : M = D + S, where D is diagonal by blocks and S is a very sparse matrix. The blocks of D that can be observed along the diagonal are sets of pages strongly related together

QoS-Aware Middleware for Web Services Composition

The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online Business-to-Business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different Quality of Service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming

Food web structure and community composition : a comparison across space and time in the North Sea

Ecological communities are constantly changing as a response to environmental and anthropogenic pressures. Yet, how changes in community composition influence the structure of food webs over time and space remains elusive. Using ecological network analysis, we assessed how food web structure changed across six distinct areas of the North Sea over a sixteen-year time-period. We used multivariate analyses to disentangle and compare spatio-temporal dynamics in community composition (i.e. changes in species abundances) and food web structure (i.e. changes in network properties). Specifically, we assessed how changes in community composition were reflected in food web structure. Our results revealed a strong spatial coupling between community composition and food web structure along a south-north gradient. However, the temporal covariation between community composition and food web structure depended on the spatial scale. We observed a temporal mismatch at regional scale, but a strong coupling at local scale. In particular, we found that community composition can be influenced by hydro-climatic events over large areas, with diverse effects manifesting in local food web structure. Our proposed methodological framework quantified and compared spatio-temporal changes in community composition and food web structure, providing key information to support effective management strategies aimed at conserving the structure and functioning of ecological communities in times of environmental change.Peer reviewe

The Three Dimensional Structural Shape of the Gravitational Potential in the Local Group

The Local Group is a small galaxy cluster with the membership of 62 nearby galaxies including the Milky Way and M31. Although the Local Group has yet to be virialized, it interacts with the surrounding matter as one gravitationally bound system. To understand the formation and evolution of the Local Group as well as its member galaxies, it is important to reconstruct the gravitational potential field from the surrounding matter distribution in the local cosmic web. By measuring the anisotropy in the spatial distribution of the Local Group galaxies, which is assumed to be induced by the local gravitational tidal field , we resolve the three dimensional structure of the gravitational potential in the vicinity of the Milky Way smoothed on the Local Group mass scale. Our results show that (i) the minor principal axis of the Local Group tidal field is in the equatorial direction of alpha_{p}=15^{h}00^{m} and delta_{p}=20^{d}; (ii) it has a prolate shape with axial ratio of 0.5 +/- 0.13; (iii) the global tides in the Local Group is quite strong, which may provide a partial explanation for the low abundance of dwarf galaxies in the Local Group.Comment: accepted for publication in MNRAS, revised version, 3D potential structure in LG found, error analysis significantly improved, 8 pages, 5 figure