L1-Introduction to Data Security.pptx models
- 1. Data breaches • which occur when data is accessed in an unauthorized manner, are a major concern for organizations of all shapes, sizes and industries. • Data breaches are attributed to a number of cyber incidents, including the following: • accidental leaks or exposures • phishing attacks • distributed denial-of-service attacks • physical breaches • lack of access controls • backdoors
- 2. • Types of data security • Before an organization can secure data, it has to know what data it has. • This is where a data inventory --a record of all the data created, used and stored by a company -- is key. The process starts with data discovery, or learning what and where the data is. • Data classification follows, which involves labeling data to make it easier to manage, store and secure. The four standard data classification categories are as follows: • public information • confidential information • sensitive information • personal information
- 3. Few data security technologies • Because no single form of data exists, no single magic-bullet technique can secure all data. A defense-in-depth data security strategy is made up of a combination of tools, techniques and policies. Must-have data security technologies include the following: • Encryption • Data masking • Access control • Data loss prevention (DLP) • Data backup and resiliency
- 5. • Encryption • Encryption is the process of converting readable plaintext into unreadable ciphertext using an encryption algorithm, or cipher. If encrypted data is intercepted, it is useless as it cannot be read or decrypted by anyone who does not have the associated encryption key. • Symmetric and asymmetric encryption are two commonly used ciphers: • Symmetric encryption uses a single secret key for both encryption and decryption. The Advanced Encryption Standard is the most commonly used algorithm in symmetric key cryptography. • Asymmetric encryption uses two interdependent keys: a public key to encrypt the data and a private key to decrypt the data. The Diffie-Hellman key exchange and Rivest-Shamir-Adleman are two common asymmetric algorithms.
- 6. Data masking • Data masking involves changing data so it cannot be read. Masked data looks similar to the authentic data set but reveals no sensitive information. • Legitimate data is replaced so the masked data maintains the characteristics of the data set as well as referential integrity across systems, thereby ensuring the data is realistic, irreversible and repeatable. • Below are some common data masking techniques: • substitution • shuffling • variance • masking out • nullifying
- 7. Access control • involves two main processes: • Authentication is the process of ensuring users are who they say they are. • Authorization is the process of ensuring authenticated users have access to the necessary data and resources. • Authentication and authorization are components of an enterprise identity and access management (IAM) strategy. • Other fundamental IAM processes and techniques include multifactor authentication (MFA), principle of least privilege access, role-based access control and privileged access management. • Also important is following password hygiene best practices, such as setting minimum password lengths, requiring unique passwords and considering regular password changes.
- 8. Data loss prevention • An integral tool for any enterprise security strategy is a DLP platform. • It monitors and analyzes data for anomalies and policy violations. • Its many features can include data discovery, data inventory, data classification and analysis of data in motion, at rest and in use. • Many DLP tools integrate with other technologies, such as SIEM systems, to create alerts and automated responses.
- 9. Data backup • Data backup involves creating copies of files and databases to a secondary, and often tertiary and quaternary, location. • If the primary data fails, is corrupted or gets stolen, a data backup ensures it can be returned to a previous state rather than be completely lost. • Data backup is essential to disaster recovery plans.
- 10. Data Security Best Practices • An organization can take several steps in addition to the data security technologies above to ensure robust data security management. • External and internal firewalls: Using external and internal firewalls ensures effective data protection against malware and other cyberattacks. • Data security policy: An organization should adopt a clear and comprehensive data security policy, which should be known by all staff. • Data backup: Practicing backup of all data ensures the business will continue uninterrupted in the event of a data breach, software or hardware failure, or any type of data loss. Backup copies of critical data should be robustly tested to ensure adequate insurance against data loss. Furthermore, backup files should be subjected to equal security control protocols that manage access to core primary systems. • Data security risk assessment: it is prudent to carry out regular assessments of data security systems to detect vulnerabilities and potential losses in the event of a breach. The assessment can also detect out-of-date software and any misconfigurations needing redress.
- 11. • Quarantine sensitive files: Data security software should be able to frequently categorize sensitive files and transfer them to a secure location. • Data file activity monitoring: Data security software should be able to analyze data usage patterns for all users. It will enable the early identification of any anomalies and possible risks. Users may be given access to more data than they need for their role in the organization. The practice is called over-permission, and data security software should be able to profile user behaviour to match permissions with their behavior. • Application security and patching: Relates to the practice of updating software to the latest version promptly as patches or new updates are released. • Training: Employees should continually be trained on the best practices in data security. They can include training on password use, threat detection, and social engineering attacks. Employees who are knowledgeable about data security can enhance the organization’s role in safeguarding data.