Benefits
Encrypted Global File System
Implementing an encrypted global file system that consolidates storage, ensures immutability, and eliminates the need for traditional backups can significantly enhance data security and management. By integrating these components, you can create a robust and secure data management system that simplifies storage, enhances security, and ensures data integrity.
Features
Global Immutable Filesystem
A global immutable filesystem is an innovative approach to data management and security. By combining various Cloud object stores and file systems into a single, unified system, it ensures that the original files remain unchanged (immutable) while backing up all changes at frequent intervals, such as every 43 seconds.
AI-Driven Data Discovery & Classification
AI-driven data discovery and classification is a powerful approach to managing and securing your data across both cloud and on-premise environments. Here’s how it works and why it’s beneficial:
- Automated Data Discovery: AI algorithms can scan and identify data across various sources, including public clouds, data warehouses, SaaS applications, and on-premise storage. This ensures that no data is overlooked, including shadow data that might be misplaced or forgotten.
- Efficient Data Classification: AI can classify data types such as Personally Identifiable Information (PII) and Protected Health Information (PHI) with high accuracy. This helps in ensuring that sensitive data is properly managed and protected according to regulatory requirements.
- Enhanced Security: By accurately identifying and classifying data, AI-driven solutions can help in prioritizing risk, remediating exposures, and enforcing security controls. This reduces the likelihood of data breaches and ensures compliance with data protection regulations.
- Scalability and Speed: AI can process vast amounts of data quickly, making it scalable for large organizations with extensive data assets. This reduces the manual effort required and increases the efficiency of data management processes.
- Real-Time Monitoring: Continuous monitoring and classification ensure that any new or changed data is promptly identified and managed. This keeps your data landscape up-to-date and secure.
NextGen Cloud Data Encryption
NextGen Cloud Data Encryption is designed to provide robust security for your data, protecting it from advanced threats, including those posed by AI and quantum computers. Here are some key aspects:
- Quantum-Resistant Encryption: This involves using algorithms that are resistant to attacks from quantum computers. These algorithms are designed to secure data even against the powerful computational capabilities of quantum machines.
- Data Encryption at Rest: Encrypting data at rest ensures that stored data is protected. This means that even if someone gains unauthorized access to the storage medium, they cannot read the data without the encryption keys.
- Data Encryption in Transit: Encrypting data in transit protects it as it moves between different locations, such as between your on-premise systems and the cloud. This prevents interception and unauthorized access during transmission.
- AI-Driven Threat Detection: Leveraging AI to monitor and detect potential threats in real-time can enhance the security of your encrypted data. AI can identify unusual patterns and potential breaches, allowing for swift action.
- Compliance and Regulatory Adherence: Ensuring that your encryption methods comply with relevant regulations (such as GDPR, HIPAA) is crucial. This not only protects your data but also helps avoid legal penalties. Implementing these advanced encryption techniques can significantly enhance the security of your cloud data, making it resilient against both current and future threats.
Secure Encrypted Databases
Secure encrypted databases allow you to maintain the confidentiality and integrity of your data while still enabling you to perform necessary operations. Here’s how you can achieve this:
- Record-Level Decryption: By decrypting and updating one record at a time, you minimize the exposure of sensitive data. This approach ensures that only the specific data being accessed is decrypted, while the rest remains encrypted.
- Transparent Data Encryption (TDE): TDE encrypts the database files at the storage level. When a record is accessed, it is decrypted in memory, allowing you to view and update it without exposing the entire database.
- Field-Level Encryption: This method encrypts individual fields within a database record. It provides fine-grained control over which parts of the data are encrypted and decrypted, enhancing security.
- Access Controls and Auditing: Implementing strict access controls ensures that only authorized users can decrypt and update records. Auditing mechanisms can track who accessed or modified the data, adding an extra layer of security.
- Homomorphic Encryption: This advanced encryption technique allows computations to be performed on encrypted data without decrypting it. While still an emerging technology, it holds promise for secure data processing.
- Key Management: Effective key management practices are crucial. Using hardware security modules (HSMs) or cloud-based key management services can help securely store and manage encryption keys.