Inteligência cibernética e uso de recursos semânticos na detecção de perfis falsos no contexto do Big Data
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Data
2016-04-29
Autores
Oliveira, José Antonio Maurilio Milagre de [UNESP]
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
O desenvolvimento da Internet transformou o mundo virtual em um repositório infindável de informações. Diariamente, na sociedade da informação, pessoas interagem, capturam e despejam dados nas mais diversas ferramentas de redes sociais e ambientes da Web. Estamos diante do Big Data, uma quantidade inacabável de dados com valor inestimável, porém de difícil tratamento. Não se tem dimensão da quantidade de informação capaz de ser extraída destes grandes repositórios de dados na Web. Um dos grandes desafios atuais na Internet do “Big Data” é lidar com falsidades e perfis falsos em ferramentas sociais, que causam alardes, comoções e danos financeiros significativos em todo o mundo. A inteligência cibernética e computação forense objetivam investigar eventos e constatar informações extraindo dados da rede. Por sua vez, a Ciência da Informação, preocupada com as questões envolvendo a recuperação, tratamento, interpretação e apresentação da informação, dispõe de elementos que quando aplicados neste contexto podem aprimorar processos de coleta e tratamento de grandes volumes de dados, na detecção de perfis falsos. Assim, por meio da presente pesquisa de revisão de literatura, documental e exploratória, buscou-se revisar os estudos internacionais envolvendo a detecção de perfis falsos em redes sociais, investigando técnicas e tecnologias aplicadas e principalmente, suas limitações. Igualmente, apresenta-se no presente trabalho contribuições de áreas da Ciência da Informação e critérios para a construção de ferramentas que se destinem à identificação de perfis falsos, por meio da apresentação de uma proposta de modelo conceitual. Identificou-se, na pesquisa, que a Ciência da Informação pode contribuir com a construção de aplicações e frameworks para que usuários possam identificar e discernir perfis reais de perfis questionáveis, diariamente despejados na Web.
The development of the Internet changed the virtual world in an endless repository of information. Every single day, in an information-society, people change, catch and turn out files in different tools of social network and Web surrounding. We are in front of “The Big Data”, an endless amount of data with invaluable, but hard treating. It doesn’t have some dimension of measure information to be able of extracting from these big Web data repositories. One of the most challenges nowadays on the Internet from the “Big Data” is to identify feelings, anticipating sceneries dealing with falsehood and false profiles social tools, which cause fanfare, upheavals and significant financial losses worldwide in front of our true scene. The cyber intelligence has by objective to look for events and finding information, subtracting dates from the Web. On the other hand, the Information Science, worried with the questions involving recovery, processing, interpretation and presentation of information that has important areas of study capable of being applied in this context hone the collection and treatment processes of large volumes of information (datas). Thus, through this research literature review, documentary and exploratory, the researcher aimed to review the International studies implicating the analysis of large volumes of data on social networking tools in falsehoods detection, investigating applied techniques and technologies and especially their limitations. Based on the identified concepts and areas of Information Science, also (equaly), it’s the scope of this research to show a suggestion of “framework” that is able to detect or indicate falsehoods, specifically, has the ability to detect profiles, false identities and misinformation, rumors, or unreliable information, processing large volumes of data on social networking tools. It was identified with this research, the Information Science can contribute to building skilled frameworks to provide criteria so that users can identify and discern actual content of questionable content, dumped daily on the Web.
The development of the Internet changed the virtual world in an endless repository of information. Every single day, in an information-society, people change, catch and turn out files in different tools of social network and Web surrounding. We are in front of “The Big Data”, an endless amount of data with invaluable, but hard treating. It doesn’t have some dimension of measure information to be able of extracting from these big Web data repositories. One of the most challenges nowadays on the Internet from the “Big Data” is to identify feelings, anticipating sceneries dealing with falsehood and false profiles social tools, which cause fanfare, upheavals and significant financial losses worldwide in front of our true scene. The cyber intelligence has by objective to look for events and finding information, subtracting dates from the Web. On the other hand, the Information Science, worried with the questions involving recovery, processing, interpretation and presentation of information that has important areas of study capable of being applied in this context hone the collection and treatment processes of large volumes of information (datas). Thus, through this research literature review, documentary and exploratory, the researcher aimed to review the International studies implicating the analysis of large volumes of data on social networking tools in falsehoods detection, investigating applied techniques and technologies and especially their limitations. Based on the identified concepts and areas of Information Science, also (equaly), it’s the scope of this research to show a suggestion of “framework” that is able to detect or indicate falsehoods, specifically, has the ability to detect profiles, false identities and misinformation, rumors, or unreliable information, processing large volumes of data on social networking tools. It was identified with this research, the Information Science can contribute to building skilled frameworks to provide criteria so that users can identify and discern actual content of questionable content, dumped daily on the Web.
Descrição
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Computação forense, Inteligência cibernética, Big Data, Web Semântica, Perfis falsos, Computer forensics, Intelligence cybernetics, Semantic Web, Fake profiles