Web Browser Fingerprinting is a process in which the users are, with high likelihood, uniquely identified by the extracted features from their devices, generating an identifier key (fingerprint). Although it can be used for malicious purposes, especially regarding privacy invasion, Web Browser Fingerprinting can also be used to enhance security (e.g. as a factor in two-factor authentication). This paper investigates the use of Web Audio API as a Web Browser Fingerprinting method capable of identifying the devices. The idea is to prove or not if audio can provide features capable to identify users and devices. Our initial results show that the proposed method is capable of identifying the device’s class, based on features like device’s type, web browser’s version and rendering engine.
In a world rich in interconnected and complex data, the non-relational database paradigm can better handle large volumes of data at high speed with a scale-out architecture, which are two essential requirements for large industries and world-class applications. This article presents AMANDA, a flexible middleware for automatic migration between relational and non-relational databases based on a user-defined schema that offers support for multiple sources and target databases. We evaluate the performance of AMANDA by assessing the migration speed, query execution, query performance, and migration correctness, from two Relational Database Management Systems (RBMSs), i.e., Postgres and MySQL, to a non-relational database (NoSQL), i.e., DGpraph. The results show that AMANDA successfully migrates data 26 times faster than previous approaches, when considering Northwind. Regarding the IMDB database, it took 7 days to migrate 5.5 GB of data.
In past decades, the requirements that database management systems (DBMSs) must achieve have become increasingly stringent (speed, data volume). This increase in complexity led to the development of a wide range of non-relational databases strategies, each one suited for specific scenarios. In this context, Graph Database Management Systems (GDBMSs) became popular to represent social networks and other domains that can be intuitively represented as graph-like structures. In this paper, we represent Version Control System data, specifically Git, from a large software project in a graph structure and compared three popular GDBMSs: Neo4j, Janus Graph and Dgraph. We evaluated read/write operations performance for common activities, such as inserting new commits into the graph and retrieving the complete commit history of a specific project. With this contribution, researches and engineers may choose, assertively, the better solution for their needs.
Web fingerprinting é o processo no qual o usuário é, com alta probabilidade, identificado de forma única a partir das características extraídas de seu dispositivo, gerando uma chave identificadora (fingerprint). Embora possa ser usado para propósitos maliciosos, Web fingerprinting também pode ser usado com boas intensões: melhorar usabilidade em páginas Web, melhorar a autenticação de dois fatores e assim por diante. Esse trabalho investiga a Web Audio API como um método de Web Fingerprinting capaz de identificar a classe do dispositivo. Como resultado, foi descoberto que o método é capaz de identificar a classe do dispositivo, com base em características como tipo do dispositivo, versão e motor de renderização do navegador Web.
Web fingerprinting é uma técnica que consiste em obter caracter ísticas relacionadas ao software e hardware do dispositivo. De posse dessas características, uma chave de identificação pode ser gerada com alta probabilidade de ser única, dessa forma, identificando unicamente o usuário. Sua adoção dar-se a partir de duas perspectivas: benigna (autenticação e evitar fraudes) e maligna (rastrear usuários e explorar vulnerabilidades). Neste trabalho é proposto uma ferramenta que emprega Web fingerprinting para gerenciar as permissões de postagens dos usuários em ambientes de sistemas colaborativos.
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