As cyber-attacks become more prevalent and sophisticated, it is becoming increasingly important for organizations to take a proactive approach to data protection. Similar to application security, a “Shift-Left” approach to data protection can help organizations identify and mitigate risks before they become real and cause a critical impact on their organizations.
In this blog post, we’ll delve into the importance of adopting not just a Shift-Left approach to data protection, but also embracing the concept of a comprehensive DataSecOps platform. A desirable DataSecOps platform would provide precise, continuous, scalable data discovery, classification, and cataloging capabilities, effectively identifying sensitive and high business impact (HBI) data and delivering Sensitive Data Intelligence (SDI). Your DataSecOps team should be able to leverage optimized and reliable Sensitive Data Intelligence to enhance security tools and processes, and make them Data-aware ensuring security is built-in into DataOps and not bolted on.
In order to achieve a robust DataSecOps platform, it’s important it provides seamless integrations with existing security orchestration, automation, and response (SOAR) platforms, as well as established data protection solutions. These might include tools you’ve already invested in and deployed across your environment, such as Data Loss Prevention (DLP), Data Archiving, Encryption, Tokenization, and Masking utilities. With dependable sensitive data intelligence, you can ‘shift left,’ adopting a more proactive data protection strategy. This approach transforms your existing tools and processes into ‘data-aware’ systems, enabling them to proactively invoke appropriate mitigative actions, thereby avoiding potential crises.
In today’s landscape, security teams often find themselves juggling competing demands from various stakeholders. These include the emerging Chief Data Officer, the influential Chief Privacy Officer, the meticulous Head of Compliance and Data Governance, and of course, the tireless heroes within the CIO / CISO offices. As the industry accelerates toward an era of Data Integration and Data Orchestration, propelled by the hype surrounding AI and Machine Learning, the IT and Security teams face increasing scrutiny. This is due to escalating privacy regulations, which bring added complexities in the form of increased Data Subject Requests (DSRs) and Data Subject Access Requests (DSARs) when your data is all over across your IT and Hybrid Cloud in Structured and Unstructured and Semi-Structure Data Stores, Data Lakes, Data Warehouses and Lakehouses.
In my opinion, a true DataSecOps platform can serve as a harmonizing element rather than a source of conflict when dealing with diverse requests from multiple stakeholders. Everyone is seeking more reliable and accurate intelligence about sensitive and HBI data, which has proliferated across hybrid IT and cloud environments. Therefore, a comprehensive DataSecOps platform is critical to managing these demands effectively while also helping with prioritization around security and privacy operations.
Data Classification and Discovery:
A critical aspect of a shift-left strategy for Data Protection is to invest in a holistic and highly accurate and scalable data classification and discovery engine as you build up your DataSecOps platform. Data classification involves categorizing data based on its sensitivity and business impact. Data discovery is the process of identifying where sensitive data resides within an organization’s network. This includes both structured and unstructured data, in-motion, at-rest, and perhaps even data in use, known and dark, that includes organizational crown jewels such as personally identifiable information (PII), Protected Health Information (PHI), and intellectual property. Once sensitive data is identified, organizations can take more proactive steps to reduce and eliminate ROT Data (Redundant, Obsolete, Trivial Data e.g. duplicate copies) and protect the business-critical data, including applying the right access controls, encryption, masking, and other mitigating controls.
Data Cataloging:
A truly effective DataSecOps platform should also provide data cataloging capabilities. This involves creating a metadata repository of all the sensitive data identified during the data classification and discovery process. The metadata should include details such as data type, location, sensitivity level, business context, owner, and usage. This metadata repository can be used to orchestrate the appropriate mitigative actions when sensitive data is at risk, such as data encryption or data masking, tokenization, DLP, IRM, etc.
Data Protection:
When adopting a DataSecOps platform, organizations get a reliable resource to safeguard their sensitive information proactively leveraging a variety of Data security and protection measures.
- Role-Based Access Controls (RBAC): This system is designed to restrict access based on the roles of the employees within the organization. This ensures that only authorized individuals can access the data they need for their roles. You can learn more about RBAC here.
- Zero Trust Segmentation (ZTS) and Zero Trust Network Access (ZTNA): ZTS segments the network, restricting lateral movement across the network, and reducing the “attack surface”. ZTNA aids this process by denying access by default, even if the user is already inside the network until the system verifies the user. You can read more about Zero Trust Architecture here.
- Zero-Knowledge Proof (ZKP): This cryptographic method allows one party to prove to another that they know a value, without conveying any information apart from the fact they know the value. More about Zero Knowledge Proof can be found here.
- Homomorphic Encryption: This form of encryption allows computations to be performed on data without decrypting it, presenting a considerable breakthrough in data privacy and security. You can learn more about Homomorphic Encryption here.
- Additionally, the DataSecOps platform should also be capable of leveraging data anonymization techniques like tokenization or masking, popular methods to reduce the potentially attackable surface. With tokenization or masking, the actual data is replaced with fictitious values, therefore, ensuring unauthorized entities can’t access the sensitive information. You can read more about data masking here.
Example:
Your DLP solution can detect an Excel File on G drive that was discovered, classified, and tagged as “PII Found” as part of your DataSecOps Shift-left strategy. The DataSecOps Platform can then invoke the right “Data Protection Play Book” leveraging your SOAR platform.
For instance:
- Create a Jira / SNOW incident ticket: “PII discovered on G Drive”
- Invoke File Data Encryption Solution to Encrypt the file
- Initiate your Archiving Solution to Archive / Backup the file
- Notify the User / Owner of the file
The Need for a Managed DataSecOps Solution
The DataSecOps platform requires skilled cybersecurity, data privacy, data operations skills, and AI talent (a min level understanding of Supervised Training/labeling), which is in short supply. Therefore, it can be challenging for organizations to develop and run their DataSecOps platform in-house. This is where a managed DataSecOps solution can help. Data protection and data privacy and governance experts can provide the necessary services to help customers identify their sensitive data, categorize it, and protect it from both internal and external cyber threats. This can help organizations address the cybersecurity and AI talent and skills gap that they face. A key strategy for DataSecOps management would be to leverage the needed expertise to build the right integrations with the existing investment in data protection tools and processes instead of taking the rip-and-replace approach.
In conclusion, a shift-left approach to data protection is a crucial next step for achieving an effective cybersecurity strategy. With a robust DataSecOps platform in place, organizations can identify their most sensitive data and proactively take appropriate mitigative actions to protect it. A managed DataSecOps solution can further help organizations address the cybersecurity talent and skills gap while providing proactive data protection and data governance services.
Our team of experts at WaveStrong has been helping customers by offering Managed Data Protection Services and partnering closely to achieve desired outcomes. We are continually expanding and optimizing our services and data protection solution portfolio while expanding our partnership ecosystems. We are committed to partnering with you, helping you Shift-left with your Data Protection, and building up a DataSecOps Platform so that together we can Discover, Classify and Protect Everything, Everywhere, all at one.
