Data breaches have become an inevitability in today‘s hyperconnected world. The average cost of a data breach has risen dramatically in recent years, from $3.86 million in 2018 to $4.24 million in 2021, according to the Ponemon Institute. High profile breaches like the 2021 Facebook data leak and 2020 MGM Resorts hoteli breach expose the sensitive data of millions of users and incur massive financial and reputational damages.
With stringent data privacy laws like GDPR and CCPA now in effect and threats rapidly evolving, organizations must make data security a top strategic priority in 2024. Implementing robust security measures can help safeguard sensitive data, avoid costly non-compliance fines, and protect customer trust and loyalty. Here are six best practices recommended based on my decade of experience as a data security consultant.
1. Comprehensively Assess and Classify All Data
The first step is gaining complete visibility into your data landscape. Conduct an exhaustive audit to identify and catalog all structured data like databases and unstructured data across business systems. Scan repositories, interview data owners, and use data discovery tools to ensure no assets are missed.
Once discovered, classify data into categories based on sensitivity level and business impact. Common data types include:
- Personally identifiable information (PII): Data relating to an identifiable person like name, email, social security number etc.
- Personal health information (PHI): Health data like medical history and treatment records.
- Intellectual property (IP): Sensitive business information like trade secrets, patents, and designs.
- Financial data: Compensation, payments, account details etc.
- Operational data: Non-sensitive business data.
Accurate classification allows you to apply security controls commensurate to data sensitivity, delete non-essential data, and inform data access policies.
2. Develop Granular Data Access Policies and Entitlements
Leverage your classification to develop stringent data access policies based on the principle of least privilege. Link access entitlements directly to user roles and data sensitivity. Examples of access policies include:
- Role-based access control (RBAC): Permissions based on job responsibilities.
- Attribute-based access control (ABAC): Permissions based on attributes like department, tenure etc.
- Rule-based: Permissions based on contextual rules.
Strictly limit access duration to the required period. Rotate access periodically and segregate duties to minimize insider threat risks. Integrate encryption, tokenization, and masking to restrict availability of sensitive data.
Systematic restrictions on data access prevent unauthorized exposure and abuse that can lead to breach incidents.
3. Monitor Access and Usage of Sensitive Data
Vigilantly monitoring access and usage of sensitive data is crucial for early threat detection. Log, monitor, and analyze all data queries, modifications, and transactions. Detect unusual access patterns like:
- Increased volume or velocity of access
- Access from irregular locations or unfamiliar devices
- Access outside working hours
- Attempted access of anomalous data
Combine behavior analytics to flag suspicious user behavior indicative of compromised credentials or malicious intent. An IBM study found 60% of insider attacks are caused by negligent employees. Techniques like user entity behavior analytics (UEBA) can uncover risky behaviors.
Regularly review permissions and revoke stale entitlements to reduce data exposure from user lifecycle changes.
4. Adopt Privacy-Enhancing Technologies
Integrating privacy-enhancing technologies (PETs) enhances data security and minimizes risk of unauthorized exposure. PETs allow sensitive data analysis while protecting privacy. Major categories of PETs include:
Encryption: Secure data via cryptographic methods like homomorphic and searchable encryption.
Anonymization: Scrub identifying information using tokenization, k-anonymity, generalization etc.
Federated Learning: Build ML models from decentralized data sources.
Trusted Execution Environments: Hardware-based secure enclaves like Intel SGX.
Multi-party Computation: Jointly compute on data without sharing underlying datasets.
Synthetic Data Generation: Use AI to generate fake datasets preserving privacy.
Assess your use cases and select appropriate PETs to enable data usage while preventing compromise of raw sensitive data.
5. Prepare and Test Incident Response Plans
Despite rigorous security controls, data breaches can still occur due to sophisticated cyber attacks, system outages, or plain human error. Developing and testing a detailed incident response plan is critical for minimizing breach impact. Key elements include:
Documented playbooks covering containment, eradication and recovery procedures.
Communication protocols for promptly engaging key stakeholders like legal, PR etc.
Designated response teams with defined roles aligned to response procedures.
Testing protocols like simulations to validate plan effectiveness and training responders.
Keep the plan updated by incorporating learnings from exercises and new response scenarios into playbooks.
6. Instill a Culture of Security Awareness
Despite advanced security tools, employees unfamiliar with safe data practices often inadvertently trigger breach incidents. Develop strong security awareness across your organization through:
Policy education: Ensure employees understand data policies, proper access needs, and handling.
Threat simulations: Use phishing simulations and ethical hacking exercises to build threat awareness.
Security training: Conduct role-specific security trainings, especially for data access.
Awareness events: Hold events like conferences, Q&As during cybersecurity month.
Gamification: Increase engagement through games testing security knowledge.
You can track metrics like training completion rates and phishing susceptibility to measure effectiveness. Building a security-focused culture is the ultimate defense against insider and human-caused breaches.
With data volumes and cyber risks steadily growing, organizations must prioritize data security now more than ever. Follow these six best practices – comprehensively assess your data, limit access, monitor activity, leverage PETs, prepare response plans, and build employee awareness. Interested in technologies that can help implement these data security measures? See our recommendations on top cybersecurity software and data management platforms. For additional guidance, feel free to connect with me!