Sensitive data is the foundation of your organization’s intellectual property, revenue stream, and competitive advantage. That makes it imperative to protect your data from all types of internal and external threats, from disgruntled or careless employees to cybercriminals motivated by money or malice. There are also compliance issues and new security regulations that organizations need to consider. Data breaches result in billions of dollars being spent on lawsuits or on legal penalties.
Data security and privacy challenge organizations to meet different but very critical and complementary issues: Data security governs access to data throughout its lifecycle, whereas data privacy defines that access based on privacy policies and laws—for instance, who views personal, financial, health, or confidential data. Both are challenged today with the growth and proliferation of data from cloud, analytic, and big data initiatives, and the continued barrage of data breaches.
MAGNOOS considers a data-centric approach by securing the data at its source, you can minimize risk throughout your business and protect data as it moves across your organization, in and out of applications, wherever the data is consumed by the business or shared with business partners.
MAGNOOS security solutions detect and protect critical data across the enterprise; lowering risk associated with cloud modernization, Hadoop, customer centricity, and data governance initiatives. Gain actionable data discovery & classification, risk scoring, behavioral analytics, and automated protection for structured, unstructured, cloud, big data, and relational systems.
MAGNOOS along with Informatica offers the following solutions to provide data security and privacy controls to prevent unauthorized access to and disclosure of sensitive, private, and confidential information:
Dynamic Data Masking de-identifies data and controls unauthorized access to production environments. Dynamically masks sensitive information and blocks, audits, and alerts end users, IT personnel, and outsourced teams who access sensitive information while ensuring compliance with privacy regulations.
IT organization can apply sophisticated, flexible data masking rules based on a user’s authentication level.
Apply security actions in real time to dynamically mask, scramble, hide, block, audit, and alert about unauthorized access based on screen, table, column, row, and cell access level.
Enable quick and consistent access restriction across tools, applications, and environments by defining data masking policies once and applying them multiple times. You can apply data masking algorithms to any sensitive data, in any format.
While supporting virtualized and cloud-computing environments, Informatica Dynamic Data Masking prevents unauthorized access to custom applications, packaged applications, data warehouses, and operational data stores without performance impact.
Provides business critical information only to those required to see the data, based on selectively applied security rules.
Functional appearance and integrity of masked data is maintained for complex applications by synchronizing data values across rows and tables.
Cost-Effectively Protect Business Applications and Production Databases
Quickly Customize Security Solutions for Maximum ROI
Support Outsourcing and Cloud Initiatives While Protecting Information
Provides secure, automated provisioning of non-production datasets to meet the needs of testing and development teams. IT organizations can achieve shorter development cycles and faster deployment while improving compliance with data privacy regulations.
Create and centrally manage masking processes from a single, high-performance environment that readily handles large data volumes. Leverage the scalability and robustness of the Informatica Platform and its enterprise-wide connectivity to mask sensitive data regardless of database (Oracle, DB2, SQL Server, Sybase, Teradata), platform (Windows, UNIX/Linux, z/OS), or location.
Maintain structural rules to de-identify values by using masking algorithms such as substitution, blurring, sequential, randomization, and nullification, plus special techniques for credit card numbers, SSNs, account numbers, and financial data. Substitute production information with realistic prepackaged or user-defined data sets.
Pre-identify sensitive data and recommend appropriate algorithms with data masking accelerators. Rapidly deploy data privacy policies with accelerators for ERP, SFA, CRM, and SCM applications, including Oracle E-Business Suite, SAP, PeopleSoft, and Siebel.
Quickly apply masking algorithms to any sensitive data, in any format. Access and mask a wide variety of databases, mainframes, and business applications, including Oracle, IBM DB2, Microsoft SQL Server, IMS, VSAM, JD Edwards, and Baan. Create data masking rules and standards across all enterprise systems.
Reduce Risk of Data Breaches
Improve the Quality of Development, Testing, and Training Activities
Support Compliance with Data Privacy Mandates and Regulations
Analysing the data vulnerability provides insights into sensitive data risks by automating the process of collecting all the information around sensitive data, analyzing, monitoring, and providing a 360-degree view of sensitive data risk. This enables security and IT teams to rapidly apply the right policies and controls to the most critical data. It replaces costly, time-consuming manual efforts with automated discovery, identification, detection, scoring, and analysis of sensitive data risks.
Organizations can interactively analyze the top data stores, departments, and location with the highest risks as well as visually trace the sources of unprotected sensitive data and the replication of sensitive data across data stores in the organization. By continuously monitoring, tracking, and trending standardized risk scores for each data store, in each department, and across the enterprise, organizations can measure progress for each group as well as in aggregate over time.
The level of sensitive data risk is determined by analyzing multiple factors including protection status, user access, activity, location, data cost, classification, and proliferation. This analysis produces risk scores that pinpoint the highest risk areas to prioritize remediation activities. Organizations can measure the effectiveness of security investments by tracking how risk scores trend over time.
Automating the discovery of sensitive data across large numbers of databases, big data repositories, and cloud data stores. It uses flexible, high-performance, scalable scanning to uncover sensitive data and show results quickly and clearly.
Analyzing data proliferation from Informatica data flows and provides an aggregated and visual map of sensitive data proliferation, identifying sensitive data that has the greatest proliferation.
Correlating information about user access control as well as activity against sensitive data provides a much richer dimension that enables detection of abnormal activities and insider and outsider threats.
Information security teams can define alert rules to notify them when high risk conditions are detected, such as a when a high volume of sensitive data is leaving a highly regulated country.
Rich array of dashboards that clearly present the state of sensitive data risk to decision makers and stakeholders. These reports let security practitioners and decision makers share a common platform for tactical and strategic analysis and decision making.
Enabling you to leverage your existing IT and security assets by incorporating information already captured and stored by other data security solutions, delivering a much richer analysis.
Prioritize Security Investments
Eliminate Costly, Error-Prone Manual Efforts
Streamline Sensitive Data Audit and Governance
Visibility to Sensitive Data Proliferation
Ensure critical data leaves the application/system without any data leak/loss.
Dynamically masks sensitive information and blocks, audits, and alerts end users, IT personnel, and outsourced teams who access sensitive information while ensuring compliance with privacy regulations.
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