1,720,964 research outputs found
Emerging and Established Trends to Support Secure Health Information Exchange
Get PDFThis work aims to provide information, guidelines, established practices and standards,
and an extensive evaluation on new and promising technologies for the implementation
of a secure information sharing platform for health-related data. We focus strictly on
the technical aspects and specifically on the sharing of health information, studying
innovative techniques for secure information sharing within the health-care domain,
and we describe our solution and evaluate the use of blockchain methodologically for
integrating within our implementation. To do so, we analyze health information sharing
within the concept of the PANACEA project that facilitates the design, implementation,
and deployment of a relevant platform. The research presented in this paper provides
evidence and argumentation toward advanced and novel implementation strategies
for a state-of-the-art information sharing environment; a description of high-level
requirements for the transfer of data between different health-care organizations or
cross-border; technologies to support the secure interconnectivity and trust between
information technology (IT) systems participating in a sharing-data “community”;
standards, guidelines, and interoperability specifications for implementing a common
understanding and integration in the sharing of clinical information; and the use of cloud
computing and prospectively more advanced technologies such as blockchain. The
technologies described and the possible implementation approaches are presented in
the design of an innovative secure information sharing platform in the health-care domain
Peel the onion: Recognition of Android apps behind the Tor Network
Get PDFIn this work we show that Tor is vulnerable to app deanonymization attacks on
Android devices through network traffic analysis. For this purpose, we describe
a general methodology for performing an attack that allows to deanonymize the
apps running on a target smartphone using Tor, which is the victim of the
attack. Then, we discuss a Proof-of-Concept, implementing the methodology, that
shows how the attack can be performed in practice and allows to assess the
deanonymization accuracy that it is possible to achieve. While attacks against
Tor anonymity have been already gained considerable attention in the context of
website fingerprinting in desktop environments, to the best of our knowledge
this is the first work that highlights Tor vulnerability to apps
deanonymization attacks on Android devices. In our experiments we achieved an
accuracy of 97%
Towards the usage of invariant-based app behavioral fingerprinting for the detection of obfuscated versions of known malware
No full textApp fingerprints can be used to verify whether two apps are the same, and are useful tools for malware detection because they can allow to recognize obfuscated versions of known malware. Fingerprinting an app on the base of static features is known to fail against obfuscation, as it is successful in hiding the static characteristics that reveal the malicious nature of an app. In this paper we propose a novel way to compute app fingerprints, which is based on behavioral features. The aim is to capture the semantics of the app, so that obfuscation results ineffective. The technique we introduce exploits invariants, found among pairs of metrics, collected during app execution, and produces a fingerprint consisting of the list of the correlation values of these pairs. We present an experimental evaluation carried out on a real Android device, whose obtained results support the methodology we propose, and show it can be a viable research direction to investigate further
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
AndroDFA: Android Malware Classification Based on Resource Consumption
Get PDFThe vast majority of today's mobile malware targets Android devices. An important task of malware analysis is the classification of malicious samples into known families. In this paper we propose AndroDFA: an approach to Android malware family classification based on dynamic analysis of resource consumption metrics available from the proc file system. These metrics can be easily measured during sample execution. From each malware we extract features through detrended fluctuation analysis (DFA) and Pearson's correlation, then a support vector machine is employed to classify malware into families. We provide an experimental evaluation based on malware samples from two datasets, namely Drebin and AMD. With the Drebin dataset, we obtain a classification accuracy of 82%, %proving that our methodology achieves an accuracy comparable with works from the state of art like DroidScribe. However, compared to DroidScribe, our approach is easier to reproduce because it is based on publicly available tools only, does not require any modification to the emulated environment or Android OS and, by design, can also be used on physical devices rather than exclusively on emulators. The latter is a key factor because modern mobile malware can detect the emulated environment and hide their malicious behavior. The experiments on the AMD dataset give similar results, with an overall mean accuracy of 78%. Furthermore, we make the software we developed publicly available, to ease the reproducibility of our results
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
NIRVANA: A Non-intrusive Black-Box Monitoring Framework for Rack-Level Fault Detection
No full textMany organizations today still manage mid or large in-house data centers that require very expensive maintenance efforts, including fault detection. Common monitoring frameworks used to quickly detect faults are complex to deploy/maintain, expensive, and intrusive as they require the installation of probes on monitored hw/sw to collect raw data. Such intrusiveness can be problematic as it imposes installation/management overhead and may interfere with security/privacy policies. In this paper we introduce NIRVANA, a novel monitoring system for fault detection that works at rack-level and is (i) non-intrusive, i.e., it does not require the installation of software probes on the hosts to be monitored and (ii) black-box, i.e., agnostic with respect to monitored applications. At the core of our solution lies the observation that aggregated features that can be monitored at rack-level in a non-intrusive and black-box way, show predictable behaviors while the system works in both fault-free and faulty states, it is therefore possible to detect and identify faults by monitoring and analyzing any perturbations to these behaviors. An extensive experimental evaluation shows that non-intrusiveness does not significantly hamper the fault detection capabilities of the monitoring system, thus validating our approach
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
The overlay scan attack: inferring topologies of distributed pub/sub systems through broker saturation
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