NetCluster: A clustering-based framework to analyze internet passive measurements data

Internet measured data collected via passive measurement are analyzed to obtain localization information on nodes by clustering (i.e., grouping together) nodes that exhibit similar network path properties. Since traditional clustering algorithms fail to correctly identify clusters of homogeneous nodes, we propose the NetCluster novel framework, suited to analyze Internet measurement datasets. We show that the proposed framework correctly analyzes synthetically generated traces. Finally, we apply it to real traces collected at the access link of Politecnico di Torino campus LAN and discuss the network characteristics as seen at the vantage point.     

Titans’ revenge: Detecting Zeus via its own flaws

Malware is one of the main threats to the Internet security in general, and to commercial transactions in particular. However, given the high level of sophistication reached by malware (e.g. usage of encrypted payload and obfuscation techniques), malware detection tools and techniques still call for effective and efficient solutions. In this paper, we address a specific, dreadful, and widely diffused financial malware: Zeus.The contributions of this paper are manifold: first, we propose a technique to break the encrypted malware communications, extracting the keystream used to encrypt such communications; second, we provide a generalization of the proposed keystream extraction technique. Further, we propose Cronus, an IDS that specifically targets Zeus malware. The implementation of Cronus has been experimentally tested on a production network, and its high quality performance and effectiveness are discussed. Finally, we highlight some principles underlying malware—and Zeus in particular—that could pave the way for further investigation in this field.     

Identifying and understanding urban sport areas using Nokia Sports Tracker

Current advancements in pervasive technologies allow users to create and share an increasing amount of whereabouts data. Thus, some rich datasets on human mobility are becoming available on the web. In this paper we extracted approximately 790,000 mobility traces from a web-based repository of GPS tracks—the Nokia Sports Tracker Service. Using data mining mechanisms, we show that this data can be analyzed to uncover daily routines and interesting schemes in the use of public spaces. We first show that our approach supports large-scale analysis of people’s whereabouts by comparing behavioral patterns across cities. Then, using Kernel Density Estimation, we present a mechanism to identify popular sport areas in individual cities. This kind of analysis allows us to highlight human-centered geographies that can support a wide range of applications ranging from location-based services to urban planning.     

Workflows for Heliophysics

In this paper we describe how we have introduced workflows into the working practices of a community for whom the concept of workflows is very new, namely the heliophysics community. Heliophysics is a branch of astrophysics which studies the Sun and the interactions between the Sun and the planets, by tracking solar events as they travel throughout the Solar system. Heliophysics produces two major challenges for workflow technology. Firstly it is a systems science where research is currently developed by many different communities who need reliable data models and metadata to be able to work together. Thus it has major challenges in the semantics of workflows. Secondly, the problem of time is critical in heliophysics; the workflows must take account of the propagation of events outwards from the sun. They have to address the four dimensional nature of space and time in terms of the indexing of data. We discuss how we have built an environment for Heliophysics workflows building on and extending the Taverna workflow system and utilising the myExperiment site for sharing workflows. We also describe how we have integrated the workflows into the existing practices of the communities involved in Heliophysics by developing a web portal which can hide the technical details from the users, who can concentrate on the data from their scientific point of view rather than on the methods used to integrate and process the data. This work has been developed in the EU Framework 7 project HELIO, and is being disseminated to the worldwide Heliophysics community, since Heliophysics requires integration of effort on a global scale.     

A novel electromyographic signal simulator for muscle contraction studies

Mathematical simulation has been widely used in biomedical and biological sciences. In the case of the surface electromyographic (SEMG) activity, some models have been proposed aiming to study muscle contraction strategies that are used during different tasks and conditions. Most of SEMG simulators are based on energy modulation of a Gaussian noise. This work proposes a novel simulator in which the user-defined parameters are associated with the motor units (MUs) recruitment and their firing rate. Comparison between the mean spectrum of real SEMG signals collected in isometric contraction of the muscle biceps brachii and the mean spectrum obtained from simulated SEMG signals showed a good agreement, pointing the proposed simulator seems to be capable to generate consistent electromyographic signals in time and frequency domains and that can be used in many studies, in particular in the evaluation of automatic methods aimed to detect muscular contraction.     

Beam search algorithms for the single machine total weighted tardiness scheduling problem with sequence-dependent setups

In this paper, we consider the single machine weighted tardiness scheduling problem with sequence-dependent setups. We present heuristic algorithms based on the beam search technique. These algorithms include classic beam search procedures, as well as the filtered and recovering variants. Previous beam search implementations use fixed beam and filter widths. We consider the usual fixed width algorithms, and develop new versions that use variable beam and filter widths.     

Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move

Applications of Bayesian networks in systems biology are computationally demanding due to the large number of model parameters. Conventional MCMC schemes based on proposal moves in structure space tend to be too slow in mixing and convergence, and have recently been superseded by proposal moves in the space of node orders. A disadvantage of the latter approach is the intrinsic inability to specify the prior probability on network structures explicitly. The relative paucity of different experimental conditions in contemporary systems biology implies a strong influence of the prior probability on the posterior probability and, hence, the outcome of inference. Consequently, the paradigm of performing MCMC proposal moves in order rather than structure space is not entirely satisfactory. In the present article, we propose a new and more extensive edge reversal move in the original structure space, and we show that this significantly improves the convergence of the classical structure MCMC scheme.     

Artificial institutions: a model of institutional reality for open multiagent systems

Software agents’ ability to interact within different open systems, designed by different groups, presupposes an agreement on an unambiguous definition of a set of concepts, used to describe the context of the interaction and the communication language the agents can use. Agents’ interactions ought to allow for reliable expectations on the possible evolution of the system; however, in open systems interacting agents may not conform to predefined specifications. A possible solution is to define interaction environments including a normative component, with suitable rules to regulate the behaviour of agents. To tackle this problem we propose an application-independent metamodel of artificial institutions that can be used to define open multiagent systems. In our view an artificial institution is made up by an ontology that models the social context of the interaction, a set of authorizations to act on the institutional context, a set of linguistic conventions for the performance of institutional actions and a system of norms that are necessary to constrain the agents’ actions.     

Measuring the structural similarity among XML documents and DTDs

Measuring the structural similarity between an XML document and a DTD has many relevant applications that range from document classification and approximate structural queries on XML documents to selective dissemination of XML documents and document protection. The problem is harder than measuring structural similarity among documents, because a DTD can be considered as a generator of documents. Thus, the problem is to evaluate the similarity between a document and a set of documents. An effective structural similarity measure should face different requirements that range from considering the presence and absence of required elements, as well as the structure and level of the missing and extra elements to vocabulary discrepancies due to the use of synonymous or syntactically similar tags. In the paper, starting from these requirements, we provide a definition of the measure and present an algorithm for matching a document against a DTD to obtain their structural similarity. Finally, experimental results to assess the effectiveness of the approach are presented.