Data Classification
Data classification, in the context of security and cybersecurity, is the process of categorizing data based on its sensitivity, value, and the level of protection required. This classification system helps organizations better manage and safeguard their data assets by applying appropriate security controls, access restrictions, and retention policies to different data types.
Critical aspects of data classification include:
Sensitivity Levels: Data is typically classified into several sensitivity levels, such as public, internal use, confidential, or highly confidential. The sensitivity level reflects the potential impact of unauthorized access or disclosure on the organization's security and compliance.
Data Types: Data types, including personal information, financial records, intellectual property, and business documents, may be subject to specific data classification categories.
Access Control: Data classification guides access control measures, determining who has access to data based on their roles and the data's sensitivity. Highly classified data may have restricted access, while less sensitive data may be more widely accessible.
Encryption: More sensitive data may need to be encrypted to prevent unauthorized access both during transmission and storage.
Retention and Disposal: Data classification influences how long data should be retained and when it should be securely disposed of or archived.
Handling and Sharing: Data classification policies dictate how data should be handled, shared, and transmitted. Highly classified data may require special precautions when shared with third parties.
Compliance: Data classification helps organizations comply with data protection regulations by ensuring that sensitive data is treated according to legal requirements.
Data classification is an essential component of an organization's data security strategy, as it enables a structured and risk-based approach to data protection. It helps organizations allocate resources and security measures more effectively, reducing the likelihood of data breaches and ensuring that sensitive information is handled appropriately throughout its lifecycle.
ThreatNG is a comprehensive solution encompassing External Attack Surface Management (EASM), Digital Risk Protection (DRP), and Security Ratings, with a focus on assessing "Data Leak Susceptibility," enhances an organization's Data Classification strategy by proactively identifying vulnerabilities within its external digital presence. This proactive strategy helps create precise data classification criteria by facilitating more accurate data categorization based on risk and sensitivity. It works in unison with current security solutions, particularly data security instruments like encryption and data loss prevention (DLP). For instance, when ThreatNG identifies external vulnerabilities that may expose sensitive data to potential breaches, it can inform the organization's DLP system. The DLP system can then adapt its monitoring and protection measures to prioritize safeguarding the identified data, ensuring it is appropriately classified and protected. This integrated approach refines the organization's data classification strategy and strengthens its overall data security posture within the external digital environment.
