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Privacidade e Proteção com Inteligência de Dados Sensíveis
Published on abril 16, 2021 AUTHOR Srinivas Avasarala
A Securiti tem o prazer de anunciar a disponibilidade de nossa mais nova oferta Sensitive Data Intelligence, que expande nosso portfólio de tecnologias de gerenciamento de privacidade para endereçar os desafios dos times de governança de dados, risco e segurança, em uma única plataforma abrangente.
Os dados se tornaram a força motriz da nova economia, com as empresas focadas em aproveitar os dados para encontrar novas maneiras de entregar valor aos clientes e gerar novos fluxos de receita. Ao mesmo tempo, a quantidade de dados está aumentando a uma taxa impressionante. Uma empresa média tem mais de 400+ sistemas de dados diferentes, espalhados por compartilhamentos de arquivos locais, bancos de dados, data warehouses empresariais, soluções de armazenamento em nuvem, aplicativos SaaS, data warehouses em nuvem, data lakes em nuvem para análises baseadas em aprendizado de máquina e muito mais. Essa expansão de dados cria vários desafios para grandes organizações.
As principais iniciativas e projetos de negócios realizados por organizações, embora extraiam um valor significativo dos dados processados, precisam considerar as implicações de privacidade, risco e segurança dos enormes volumes de dados que coletam e processam. Por meio de conversas com nossos parceiros e clientes, encontramos alguns cenários típicos em que eles estavam lidando com esses problemas.
- Projetos de data lake: as empresas estão cada vez mais aproveitando a ciência de dados para executar novos tipos de análises baseadas em aprendizado de máquina em dados brutos combinados de uma variedade de fontes em data lakes. Mas a visibilidade dos tipos de dados presentes no data lake é muito limitada. Isso é significativo ao construir modelos de autoatendimento para consumo de dados com forte governança de dados e políticas de acesso.
- Projetos de migração de dados em nuvem: as iniciativas de transformação digital por CIOs são normalmente orientadas para a nuvem e envolvem a migração de dados de on-premises para a nuvem ou a criação de novos aplicativos e cargas de trabalho em ambientes com várias nuvens. Eles precisam entender quais informações pessoais ou confidenciais estão em seu ambiente para tomar as decisões de migração dos dados. O modelo de consumo flexível da nuvem torna um desafio manter um inventário atualizado dos ativos de dados, os dados dentro dos ativos e os controles dos ativos. Após a migração, as organizações precisarão contar com mecanismos automatizados para monitorar e gerenciar esses dados.
- Ciclo de desenvolvimento seguro e com privacidade: Na nova economia, toda empresa, independentemente de sua indústria vertical, também é uma empresa de software, pois constrói e entrega soluções e serviços aos seus clientes digitalmente. As iniciativas de privacidade desde o design e ciclo de desenvolvimento de software seguro ajudaram a aumentar a conscientização do desenvolvedor quanto aos requisitos de privacidade e segurança no início do processo de desenvolvimento. Mas as metodologias de desenvolvimento ágil apresentam desafios à medida que novos dados são coletados/armazenados ou registro de dados em logs de aplicativos são introduzidos periodicamente, exigindo monitoramento contínuo de ambientes de desenvolvimento, preparação e produção.
- Iniciativas de mapeamento de dados: Os programas de conformidade de privacidade exigem que as empresas mantenham um registro de suas atividades de processamento de dados. As equipes de privacidade que historicamente dependem de questionários manuais preenchidos por proprietários de dados estão procurando desenvolver seus processos com descoberta e controles de dados automatizados, dada a natureza dinâmica dos dados. Isso mantém seus registros mais precisos e atualizados.
- Projetos de atendimento de requisições de titulares de dados: Empresas B2C em verticais como varejo, turismo, saúde e serviços financeiros, que atendem a milhões de clientes, agora estão sobrecarregadas com requisitos de leis de privacidade que concedem aos usuários direitos de acesso às suas informações. Com o número crescente de violações de dados, o volume dessas requisições de acesso de titulares está aumentando. E as equipes de privacidade, juntamente com seus colegas de TI, precisam investir em ferramentas automatizadas que possam detectar e vincular dados pessoais a identidades específicas.
Sensitive Data Intelligence
As organizações hoje contam com uma combinação de métodos manuais, ferramentas de descoberta de dados legadas adaptadas e produtos pontuais para enfrentar os desafios acima. Estes provaram ser inadequados ou ineficazes. Com Sensitive Data Intelligence, oferecemos aos nossos clientes uma plataforma única com os seguintes recursos abrangentes:
- Descoberta automatizada de ativos de dados em toda a empresa, incluindo ambientes locais, híbridos e com várias nuvens.
- Detecção imediata de mais de 100+ atributos de dados pessoais em mais de uma dúzia de categorias, incluindo IDs governamentais, IDs de dispositivos, IDs online, dados financeiros, jurídicos, médicos, etc. Isso inclui categorias especiais de dados definidas pelo LGPD, GDPR e outras leis de privacidade.
- Pontuação de risco de dados para fornecer uma abordagem centrada em risco para gerenciar os dados que estão sendo coletados e processados. Nosso modelo proprietário potencializa fatores de risco, como tipo de dados, localização dos dados, residência do titular dos dados e volume de dados e pode ser prontamente ampliado. A solução permite que os clientes encontrem facilmente pontos de atenção e direcionem os esforços de correção de forma adequada. As tendências de pontuação de risco também apresentam indicadores de risco, como cópias de dados e transferências internacionais de dados.
- Análise de dados estruturados com insights sobre tipos de dados e volumes em bancos de dados, esquemas e tabelas.
- Classificação de dados não estruturados usando técnicas baseadas em aprendizado de máquina em categorias diversificadas (Vendas, Médicos, RH, etc), tipos (formulário de consentimento médico, imposto de renda, holerite, etc) em vários formatos. Além disso, as organizações podem definir seus próprios esquemas usando perfis de conteúdo baseados em regras. Uma biblioteca de perfis integrados, como PCI, PII, PHI, GLBA e FERPA, ajuda os clientes a iniciarem imediatamente.
- Rotulagem de arquivos usando rótulos de classificação do Microsoft Information Protection. Além disso, marcar com metadados relacionados à privacidade, como categorias de dados pessoais, categorias de titulares e finalidade.
- Um mecanismo de política para automatizar e orquestrar controles nos vários armazenamentos de dados usando uma biblioteca integrada de modelos de política mapeados para citações regulamentares e controles padronizados.
Este é o início de nossa jornada e em breve estaremos expandindo a solução com automação adicional que traz maiores níveis de eficiência para equipes de privacidade, governança de dados, risco e segurança. Confira nossa brochura para mais detalhes.
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- Automate data subject access request handling
- Secure fulfillment of data access
- Automate the processing of rectification requests
- Automate object and restriction of processing requests
- Automate erasure requests
- Continuous monitoring and tracking
- Automate People Data Graph
- Meet cookie compliance
- Monitor and track consent
- Assess DPA readiness
- Map data flows
- Manage vendor risk
- Automate data subject access request handling
- Secure fulfillment of data access
- Automate the processing of rectification requests
- Automate erasure requests
- Automate object and restriction of processing requests
- Continuous monitoring and tracking
- Automate People Data Graph
- Meet cookie compliance
- Monitor and track consent
- Assess PDPO readiness
- Map data flows
- Manage vendor risk
- Breach Response Notification
- Automate data subject access request handling
- Secure fulfillment of data access
- Automate the processing of rectification requests
- Automate erasure requests
- Automate object and restriction of processing requests
- Continuous monitoring and tracking
- Automate People Data Graph
- Meet cookie compliance
- Monitor and track consent
- Assess DPA readiness
- Map data flows
- Manage vendor risk
- Breach Response Notification
- Continuous monitoring and tracking
- Automate People Data Graph
- Monitor and track consent
- Assess TRA CPR readiness
- Map data flows
- Manage vendor risk
- Customize DSR Request Portal
- Automate Data Subject Access Request Handling
- Secure Fulfillment of Data Access
- Automate Processing of Rectification Requests
- Automate Erasure Requests
- Automate Objection & Restriction of Processing Requests
- Continuous Monitoring & Tracking
- Automate People Data Graph
- Meet Cookie Compliance
- Monitor & Track Consent
- Assess PIPA Readiness
- Map Data Flows
- Manage Vendor Risk
- Breach Response Notification
BackSnowflake is a cloud based data warehouse that allows organizations to run large scale data analytics projects to uncover business insights, run or train machine learning models, and modernize their data infrastructure.
Key Features
The Amazon S3 (Simple Storage Service) is a web-service which allows for scalable storage solutions for data archival, backup, and recovery purposes.
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Microsoft O365 is the ubiquitous productivity suite for every business worker. Users rely on Office products such as OneDrive and SharePoint to collaborate with their co-workers.
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Organizations want to migrate their on-premises data to cloud data stores to take advantage of scale and flexibility while reducing operational cost of managing on-premises infrastructure. However, due to privacy regulations such as GDPR, CCPA administrators have to ensure that data is migrated in compliance with these laws.
Key Features
Protecting sensitive content is a priority for all organizations, however, due to volume of sensitive content and
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While data aids in business decision making, global privacy regulations such as GDPR, CPRA require organization to identify personal & sensitive data & use only for its intended purpose and implement adequate protection.
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The California Consumer Privacy Act (CCPA) was signed into law on June 28, 2018 and is scheduled to come into effect on January 01, 2020. Often compared to GDPR, CCPA protects consumers from mismanagement of their personal data and gives the consumer control over what data is collected, processed, shared or sold.
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The EU General Data Protection Regulation (GDPR) came into effect on May 25, 2018 and changed the global privacy landscape. It has broadened the definition of processing activities and personal data, impacting companies worldwide, and has tightened the rules to obtain consent before processing information.
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The Lei Geral de Proteção de Dados (LGPD) is modeled with similarities to the General European Data Protection Regulation (GDPR) and contains sixty-five articles. It was approved on August 14, 2018 and its validity has undergone several changes, the last relevant fact being MPV 959. LGPD is in effect since September 18, 2020. The sanctions by the ANPD (Brazilian Data Protection Authority) were postponed to August 2021. The LGPD allows people have more rights over their data and expects organizations to comply with their regulations or face heavy penalties or fines.
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The government of New Zealand has recently replaced its long-existing Privacy Act of 1993 with a modernized version, the Privacy Act 2020. The New Zealand Privacy Act 2020 (NZPA) will take effect from December 1, 2020.
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The Personal Data Protection Act, B.E. 2562 (2019) ('PDPA') is Thailand's first consolidated data protection law, which was published in the Thai Government Gazette on 27 May 2019. This law was said to go into effect on 27 May 2020. However, in May 2020, the Thai Cabinet through a Royal Decree has deferred the enforcement of certain data protection provisions of the PDPA until 31 May 2021.
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In order to protect the data of individuals in South Africa, Parliament assented to the Protection of Personal Information Act (POPIA) on 19th November 2013. The commencement date of section 1, Part A of Chapter 5, section 112 and section 113 was 11 April 2014. The commencement date of the remaining sections (excluding section 110 and 114(4)) was 1st July 2020. As per the Regulator’s Operational Readiness Plan the Regulator will be able to take enforcement actions for the violation of POPIA by July 1st 2021.
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The DIFC Data Protection Law, 2020 lays down regulations regarding the collection, disclosure and processing of personal data in the DIFC, a special economic zone in Dubai. It also gives rights to individuals whom the personal data relates to and provides power to the Commissioner of Data Protection to enforce the law, enact regulations and approve industry-wide Codes of Conduct.
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The Australia Privacy Act 1988 (Privacy Act) was enacted to protect the privacy of data subjects and regulate how Australian agencies and organizations with an annual turnover of more than $3 million handle their customers’ personal information.
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Singapore’s Personal Data Protection Act (PDPA) comprises various provisions governing the collection, disclosure, use, and care of personal data. It recognizes the rights of individuals to have more control over their personal data and the needs of organizations to collect, use, or disclose personal data for legitimate and reasonable purposes.
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On April 13, 2000, the Personal Information Protection and Electronic Documents Act (PIPEDA) received Royal Assent. It came into force in stages, beginning on January 1, 2001. PIPEDA came fully into effect on January 1, 2004. The legislation applies to organizations that collect, use or disclose personal information in the course of commercial activities.
Key Features
After the invalidation of Privacy Shield, many companies are relying on the SCCs in order to continue transferring data of EU citizens to companies based in countries who are not deemed adequate for data transfer.
After the CJEU judgement, it is clear that these companies have to conduct Risk Assessments with the data recipients in these countries in order to ensure they have enough controls to mitigate any potential data or regulatory risk.
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On 2nd March, 2019, the Department of Health—Abu Dhabi (DoH), launched the Abu Dhabi Healthcare Information and Cyber Security (ADHICS) Standard. This is the first standard that aims to provide healthcare professionals and entities a comprehensive guide to the regulation of healthcare data in Abu Dhabi. This law ensures the highest levels of privacy and security of patients’ data, in line with international standards, is maintained.
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On January 31, 2020, the government of Saudi Arabia issued the Executive Regulations to the Saudi E-Commerce Law 2019 (“ECL”) that was in effect since October 2019. The Executive Regulations together with the ECL (“Law”) aim to protect consumers’ personal data by requiring organizations to take appropriate technical and administrative measures.
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Turkey was one of the first countries to start the trend of legislating data protection. Turkey published “Law on the Protection of Personal Data No. 6698 (LPPD) covering personal data protection on April 07, 2016.” The LPPD is based on the European Union Data Protection Directive 95/46/EC and has several similarities with the GDPR. It aims to give data subjects’ control over their personal data and outlines obligations that organizations and individuals dealing with personal data must comply with. The LPPD has also provided comprehensive guidelines for the transfer of personal data to the third parties.
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In December 2019, India, following several other countries' footsteps on the privacy laws' developments, introduced the Personal Data Protection Bill (PDPB) to regulate the processing, collection, and storage of personal data.
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On 13 October 2020, the National People's Congress of the Republic of China submitted the long awaited draft of the Personal Information Protection Law (Draft PIPL) to the Standing Committee meeting for preliminary review. This draft was officially released for the public consultation on 21 October, 2020. The consultation period will last until 19 November 2020.
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The Irish Data Protection Act, 2018 (Irish DPA) implements the General Data Protection Regulation (GDPR) and transposes the European Union Law Enforcement Directive in Ireland. Since it incorporates most of the provisions from the GDPR and the Law Enforcement Directive with limited additions and deletions as per the national law, it is considered to be the principal data protection legislation in Ireland.
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The Personal Data (Privacy) Ordinance (Cap. 486) as amended in 2012 (the “PDPO) is the primary legislation in Hong Kong which was enacted to protect the privacy of individuals’ personal data, and regulate the collection, holding, processing, disclosure, or use of personal data by the organizations.. The Data Protection Principles ( the “DPPs or DPP ''), which are contained in Schedule 1 to the PDPO, outline how entities should collect, handle, disclose, and use personal data.
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In 2012, the Philippines passed the comprehensive privacy law, Data Privacy Act 2012 Republic Act. No, 10173 (the "DPA"). The DPA recognizes the rights of individuals to have more control over their personal data while ensuring a free flow of information to promote innovation and growth.
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The United Arab Emirates (UAE) has a Federal Telecommunication Law ( Federal Law) which requires that a company must hold a license in order to provide public communications services and operate public telecommunication networks. Under this Federal Law, a Telecommunication Regulatory Authority (TRA) was established which regulates the telecommunication sector in the UAE.
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South Korea has a general law and several special laws that cover data protection and individuals' privacy. South Korea's data protection regime is considered one of the strictest data protection regimes owing to its notification requirements, opt-in consent, extensive data subject rights, mandatory data breach notifications, and heavy sanctions in case of non-compliance.
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