Data classification methods and guidelines

Email Alerts

Register now to receive SearchFinancialSecurity.com-related news, tips and more, delivered to your inbox.
By submitting you agree to receive email from TechTarget and its partners. If you reside outside of the United States, you consent to having your personal data transferred to and processed in the United States. Privacy
  • Data classification best practices in financial services

    Data classification is critical in the highly regulated financial industry. Learn key steps for data classification. 

  • How to secure data backup

    Financial-services firms are among the many organizations that have reported losing backup tapes with sensitive customer data. In this tip, W. Curtis Preston explains how to secure data backup and the pros and cons associated with the three basic me... 

  • By addressing data privacy, companies avoid public scrutiny

    Some organizations may believe data privacy laws don't affect them, but those groups may be deluding themselves. Authors Craig Norris and Tom Cadle explain why, and offer a comprehensive overview of the responsibilities that come with handling sensit... 

  • Security information management finally arrives, thanks to enhanced features

    In this tip, Mike Rothman reveals how network-behavior analysis and log management technologies have brought some new life to the SIM market. 

  • How to classify security for enterprise file folders

    Many organizations provide default access to network files and folders, meaning everyone has access to everything. However, the open access model does not address the complexity that comes with multiple levels of information confidentiality. In this ... 

  • Encryption best practices

    Encryption is a necessary security tool in financial companies, but government mandates limit how much data you can encrypt and where it can be deployed. Learn how to determine what's the best plan for encryption at your financial services organizati... 

  • Data leakage detection and prevention

    While corporate data loss is not a new concern, newer technologies are emerging to help combat the threat. In this tip, Joel Dubin advises how to reduce data leaks, reviews products that can identify network vulnerabilities and keep mobile device dat... 

  • Storage vulnerabilities you can't afford to miss

    In this tip, Keavin Beaver identifies eight common storage security vulnerabilites that are often overlooked and examines why network admins should develop a layered security strategy to protect sensitive data. 

  • The TJX data security breach: 10-K filing shows IAM and compliance mistakes

    Analysis of TJX's recent 10-K regulatory filing with the Securities and Exchange Commission exposes the company's lack of basic security and non-compliance with industry standards. But as Joel Dubin writes, a closer look highlights lessons from which... 

  • Data governance and classification

    Protecting data begins with well executed asset inventory and continues by constantly keeping tabs on where sensitive information is. Mark Weatherford, executive officer and chief information security officer of California's Office of Information Sec... 

  • Data encryption: Q&A with Eric Leighninger

    Eric Leighninger, the chief security architect for Allstate Insurance Co. answers audience members' questions on topics like data classification, Department of Defense standards and post-implementation patch updates, following his presentation on ent... 

  • Data encryption: Pre-implementation best practices

    Encryption is one of the must-have technologies for financial institutions, but implementation can be a tricky process. In this video, Eric Leighninger of Allstate Insurance Co. offers best practices on laying the groundwork for full-disk encryption ... 

About Data classification methods and guidelines

Before businesses safeguard mission-critical data, they must know how to conduct data classification processes. Learn about data classification procedures, methods and guidelines and how to use data mining to conduct inventory, map data to business processes and define classification levels.