As data continues to rise in importance as the most important asset for most new edge businesses, every organization must ensure that its data is safeguarded no matter where it exists in the world.
The entire security condition of your software and hardware assets, code repositories, cloud applications, data pipelines, networks, services, and information is referred to as your enterprise's security posture.
Cloud Data Security Posture Management is a subset of security basics that is aimed towards improving companies’ data management across cloud networks, apps, and data stores.
What is Data Security Posture Management?
Data Security Posture Management (Data) is a robotic set of security solutions and automation that enables the organization’s Security, IT and Data teams to get visibility and manage the data security posture of their datastores and applications. While CSPM is looking at the security posture of the cloud infrastructure itself, focused on major public cloud providers ; DSPM is diving into the data layer regadlress where it is located including Snowflake, Databricks, MongoAtlas and more...
With Saasment you can automatically find and fix security risks to prevent human error across your cloud assets.
Data Security Posture Management Features
When it comes to data discovery, it's all about finding and protecting sensitive or regulated information. Because it's such an important part of preparedness for compliance, data discovery has become one of the most popular business intelligence trends in recent years. Analyzing sensitive data, such as personally identifiable information (PII) or electronically protected health information (ePHI) is part of the data discovery process. Data discovery allows security teams to detect and safeguard sensitive data while also ensuring its integrity, security, and accessibility.
Data Access Management
In order to protect the security, privacy, and integrity of corporate data, companies can utilize Data Access Control to grant permissions to authorized users, staff, and third parties. Security best practices and government legislation like GDPR, HIPAA, and NIST set these standards. Organizations are frequently required by these rules to audit and regulate the entities that have access to sensitive data.
Monitoring of Database Activity
A set of instruments called Database Activity Monitoring (DAM) can also be used to detect and report on fraudulent, unlawful, or other unwanted conduct while having a minimum influence on user activities and output. In recent years, the tools have progressed beyond the fundamental analysis of user behavior in and around relational database management systems (RDBMSs) to include a highly extensive set of features, consisting of identification and categorization, intrusion prevention, vulnerability management, identity and access management integration, support for unstructured data security, application-level analysis, and risk management assistance, to name a few.
Pre-transfer data encoding or transformation is known as Cloud Data Encryption. Using mathematical techniques, encryption converts data (plaintext) into an unreadable form (ciphertext) that keeps it hidden from malevolent and unauthorized users.
Error Identification and Resolution
Errors, bugs, or breaches in your cloud infrastructure might subject you to danger if you have Cloud Data Misconfiguration. Data breaches, cloud breaches, insider threats, or external malicious attackers leveraging the cloud pose a security risk, as they can exploit your network's flaws, and allow an intruder to obtain access.
Machine learning algorithms and protocols notify DBDR of policy breaches and dangerous activity, which enables SOCs to filter the signal from the noise and prioritize their backlog.