Dlp case study 5

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Our unique approach to DLP allows for quick deployment and on-demand scalability, while providing full data visibility and no-compromise protection. Learn more about data loss prevention software in Data Protection , our series covering the fundamentals of data security. Data loss prevention DLP is a set of tools and processes used to ensure that sensitive data is not lost, misused, or accessed by unauthorized users. Once those violations are identified, DLP enforces remediation with alerts, encryption , and other protective actions to prevent end users from accidentally or maliciously sharing data that could put the organization at risk. Data loss prevention software and tools monitor and control endpoint activities, filter data streams on corporate networks, and monitor data in the cloud to protect data at rest, in motion , and in use.
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DLP Case Studies

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A Business Case for Data Loss Prevention

Every organization fears losing its critical, confidential, highly restricted or restricted data. Fear of losing data amplifies for an organization if their critical data is hosted outside their premises, say onto a cloud model. The most famous among them are Symantec, McAfee, Web-sense, etc. Each DLP product is designed to detect and prevent data from being leaked. These products are applied to prevent all channels through which data can be leaked. Data is classified in the category of in-store, in-use and in-transit. We will lean about these classifications later in this article.
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Detecting malicious insiders: a new use case for data loss prevention

Please join StudyMode to read the full document. The Principle of Merit and Fitness The merit and fitness system is the process of promoting and hiring government employees based on their ability to perform a job, rather than on their political connections. The system secures efficiency in government service and promote social justice because it guarantees equal opportunity to all deserving applicants that desires a career in public service. Other than competitive examinations there are other methods in determining merit, by investigation of school records, experience in actual work, achievements attained that is relevant to the position to be filled and etc. Another basis would be the Presidential Decree No.
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With limited resources, DLP analysts scrambled to piece through the endless pile, trying to find the needle in the haystack and too often wasting time on false positives. Meanwhile the alert backlog only grew, elevating the risk of critical alerts being overlooked. As Nico described how DLP has evolved over the years, he brought up some good points. More enterprises are integrating DLP with user and entity behavior analytics UEBA to pare down and prioritize the mountain of alerts so that analysts only receive the most critical ones.
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