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O que é a análise de comportamento do usuário (UBA)?
Definição de análise de comportamento do usuário (UBA) A análise de comportamento do usuário (UBA, pelas iniciais em inglês) é a prática de coletar e analisar dados de atividade do usuário para criar uma linha de base de seus padrões e preferências normais de comportamento. Ao desenvolver essas linhas de base para cada usuário e monitorar suas atividades em tempo real em relação a elas, a UBA ajuda as organizações a detectar irregularidades. Quando ocorre um comportamento suspeito, as equipes podem identificar possíveis ameaças à segurança , tentativas de acesso não autorizado e violações de dados.
Como funciona a UBA? A análise de comportamento do usuário funciona coletando e analisando dados de atividade do usuário em seu sistema ou rede. Aqui está uma rápida visão geral de como ela funciona:
Primeiro, a UBA coleta dados sobre um usuário de diversas fontes e regiões em seu ambiente de TI, como arquivos de log, tráfego de rede e uso de aplicações. A UBA estabelece uma linha de base de comportamento normal para o usuário (incluindo atividades e interações comuns nas quais o usuário se envolve, bem como informações passivas, como a localização geográfica) por meio de um processo denominado criação de perfil comportamental.
Em seguida, a UBA aplica machine learning , modelagem estatística e outras análises avançadas para detectar desvios da linha de base do usuário ou do comportamento de pares que podem indicar tentativas de acesso não autorizado e outras ameaças à segurança. Ela examina essas anomalias para determinar seus riscos potenciais e, em seguida, atribui pontuações de risco com base em sua gravidade.
Se a detecção de anomalia exceder o limite de risco de uma regra de detecção, a tecnologia alertará a equipe de segurança, que poderá então investigar e responder à atividade potencialmente maliciosa.
A UBA garante que as linhas de base dos usuários não fiquem estagnadas, evoluindo constantemente para melhorar os perfis comportamentais dos usuários a cada ação. O machine learning atualiza constantemente as análises, procurando novos padrões de atividade e outros novos dados. Isso ajuda a UBA a ficar melhor na detecção de anomalia com o passar do tempo.
Por que a análise de comportamento do usuário é importante? A análise de comportamento do usuário ajuda as organizações a detectar e responder a ameaças que usam contas de usuário, como ameaças internas, contas comprometidas, e uso indevido e abuso de privilégios. Estes são alguns exemplos de indicadores de ameaças internas e controle de contas:
O usuário acessa um banco de dados que nunca usou antes e baixa dados sensíveis O usuário baixa quantidades anormalmente grandes de dados O usuário explora/acessa sistemas ou aplicações suspeitos O comportamento do usuário difere significativamente de outros que fazem o mesmo trabalho A UBA também pode detectar invasores externos e outras ameaças que vêm de fora. Estes são alguns exemplos de ataques externos:
O usuário faz login em um local incomum, sugerindo comprometimento da conta
Ataques de força bruta, como repetidas tentativas de login malsucedidas ou padrões de login estranhos que podem indicar que um invasor está tentando obter acesso Atividade de rede suspeita, como tentativas de comunicação de comando e controle ou de exfiltração de dados Outros comportamentos maliciosos, como tentativas de aumentar privilégios, explorar vulnerabilidades ou realizar ações não autorizadas
A UBA permite que as equipes analisem as atividades dos usuários que levam a um incidente de segurança, entendam o escopo do incidente e tomem as medidas apropriadas para mitigar o impacto. Os analistas recebem pontos de partida baseados em evidências para investigação, visualizações ricas para análises eficazes e acesso direto aos dados para resposta rápida. Ao monitorar o comportamento do usuário em busca de violações de políticas, a UBA pode detectar possíveis ameaças internas e também ajudar sua organização a cumprir os requisitos de conformidade.
A UEBA adapta-se continuamente com base nas mudanças nos padrões gerais do usuário para ajustar o que aciona seu limite de alerta. Para funcionários que realizam o mesmo trabalho, ela cria comparações entre grupos de pares, permitindo a detecção de anomalias em relação aos pares. Dessa forma, é menos provável que alterações coletivas nos perfis dos usuários se apresentem como anomalias que exigem investigação, e contas de usuários sem dados suficientes para uma linha de base podem ter suas atividades comparadas com as de seus pares.
O que é a análise de comportamento de entidades e usuários (UEBA)? A análise de comportamento de entidades e usuários (UEBA, pelas iniciais em inglês) é um conceito de segurança cibernética cunhado pela empresa de análise Gartner em 2015. A UEBA reflete uma expansão dos objetivos da UBA.
A UEBA amplia a intenção da UBA ao analisar não apenas o comportamento do usuário, mas observando também o comportamento de outras entidades dentro do seu sistema, como dispositivos e endpoints. A UEBA avalia a atividade de usuários e entidades para obter uma visão clara do quadro geral de segurança. Ao monitorar e correlacionar vários pontos de dados, como comportamento do usuário, atividade do host e tráfego de rede, a UEBA identifica anomalias que podem indicar atividades maliciosas.
Tanto a UBA quanto a UEBA podem ser integradas a outros sistemas e ferramentas de segurança, como sistemas de gerenciamento de eventos e informações de segurança (SIEM) , soluções de prevenção contra perda de dados (DLP) e EDR. Essas integrações melhoram a segurança geral do seu sistema ao proporcionar uma visão mais abrangente e integrada de ameaças e incidentes.
Qual é a diferença entre UBA e EDR (detecção e resposta de endpoint)? A diferença entre UBA e EDR é que a detecção e resposta de endpoint é uma solução de segurança cibernética que monitora e responde a incidentes de segurança no nível do endpoint. Os endpoints são notebooks, servidores e outros dispositivos conectados a uma rede. A UBA, por outro lado, concentra-se na análise e no monitoramento dos padrões comportamentais de usuários individuais dentro de um sistema ou rede.
O EDR implanta sensores nesses endpoints e coleta dados diretamente deles. O EDR foi projetado para detectar e responder a uma ampla gama de ameaças baseadas em endpoints, incluindo infecções por malware e tentativas de acesso não autorizado. As equipes de segurança podem usar UBA e EDR em conjunto como parte de uma estratégia de segurança cibernética com defesa em profundidade.
Desafios e limitações da análise de comportamento do usuário Existem alguns desafios da análise de comportamento do usuário a serem considerados:
A UBA depende de dados precisos e abrangentes para gerar insights significativos. Fontes de dados incompletas ou inconsistentes ou outros problemas de qualidade dos dados limitarão sua eficácia. A desvantagem da UBA, como ferramenta analítica não determinística, é que não se pode esperar que ela detecte todos os verdadeiros positivos. Em relação aos métodos baseados em regras, a UBA normalmente tem uma atuação de destaque com novos vetores de ataque e técnicas inéditas e sofisticadas, mas ela não é perfeita. Por outro lado, os algoritmos de UBA podem produzir alertas falsos positivos para um comportamento normal do usuário. Isso pode criar um trabalho desnecessário para sua equipe. É possível que você se depare com preocupações éticas e de privacidade se estiver coletando e analisando dados de usuários para a UBA. Sua organização precisa garantir que medidas adequadas de consentimento e privacidade estejam em vigor. A UBA lida com grandes volumes de dados gerados por todos os usuários da sua rede. Para tecnologias mal preparadas, o processamento e a análise de quantidades tão vastas de dados podem sobrecarregar os recursos do sistema. Sua organização pode superar esses desafios investindo tempo em práticas adequadas de higiene, normalização e armazenamento de dados. Outras prioridades poderão incluir a garantia do cumprimento da privacidade e a combinação da UBA com outras medidas de segurança para uma estratégia de defesa abrangente.
Utilize a analítica de segurança de última geração do Elastic Security para prevenção, investigação e resposta a ameaças com rapidez e escala. O Elastic Security permite:
Monitoramento contínuo . Colete e prepare dados de todo o seu ambiente digital, retenha-os indefinidamente e analise-os com eficiência.Investigação e resposta . Ofereça à sua equipe acesso rápido a dados de muitos anos, fluxos de trabalho ágeis e funcionalidades completas de colaboração.Proteção automatizada contra ameaças . Reduza os riscos monitorando e protegendo todo o seu ambiente digital em tempo real.Caça a ameaças . Conte com a velocidade, os insights valiosos e o contexto rico de que você precisa para detectar ameaças que chegam de surpresa e também as esperadas.Comece a usar o Elastic Security hoje para proteger sua organização amanhã.