Category Archives: compliance

CCPA and GDPR UPDATE: Unstructured Enterprise Data in Scope of Compliance Requirements

An earlier version of this article appeared on Legaltech News

By John Patzakis

A core requirement of both the GDPR and the similar California Consumer Privacy Act (CCPA), which becomes enforceable on July 1, is the ability to demonstrate and prove that personal data is being protected. This requires information governance capabilities that allow companies to efficiently identify and remediate personal data of EU and California residents. For instance, the UK Information Commissioner’s Office (ICO) provides that “The GDPR places a high expectation on you to provide information in response to a SAR (Subject Access Request). Whilst it may be challenging, you should make extensive efforts to find and retrieve the requested information.”CCPA GDPR

However, recent Gartner research notes that approximately 80% of information stored by companies is “dark data” that is in the form of unstructured, distributed data that can pose significant legal and operational risks. With much of the global workforce now working remotely, this is of special concern and nearly all the company data maintained and utilized by remote employees is in the form of unstructured data. Unstructured enterprise data generally refers to searchable data such as emails, spreadsheets and documents on laptops, file servers, and social media.

The GDPR

An organization’s GDPR compliance efforts need to address any personal data contained within unstructured electronic data throughout the enterprise, as well as the structured data found in CRM, ERP and various centralized records management systems. Personal data is defined in the GDPR as: “any information relating to an identified or identifiable natural person (‘data subject’); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person.”

Under the GDPR, there is no distinction between structured versus unstructured electronic data in terms of the regulation’s scope. There is a separate guidance regarding “structured” paper records (more on that below). The key consideration is whether a data controller or processor has control over personal data, regardless of where it is located in the organization. Nonetheless, there is some confusion about the scope of the GDPR’s coverage across structured as well as unstructured electronic data systems.

The UK ICO is a key government regulator that interprets and enforces the GDPR, and has recently issued important draft guidance on the scope of GDPR data subject access rights, including as it relates to unstructured electronic information. Notably, the ICO notes that large data sets, including data analytics outputs and unstructured data volumes, “could make it more difficult for you to meet your obligations under the right of access. However, these are not classed as exemptions, and are not excuses for you to disregard those obligations.”

Additionally the ICO guidance advises that “emails stored on your computer are a form of electronic record to which the general principles (under the GDPR) apply.” In fact, the ICO notes that home computers and personal email accounts of employees are subject to GDPR if they contain personal data originating from the employers networks or processing activities. This is especially notable under the new normal of social distancing, where much of a company’s data (and associated personal information) is being stored on remote employee laptops.

The ICO also provides guidance on several related subjects that shed light on its stance regarding unstructured data:

Archived Data: According to the ICO, data stored in electronic archives is generally subject to the GDPR, noting that there is no “technology exemption” from the right of access. Enterprises “should have procedures in place to find and retrieve personal data that has been electronically archived or backed up.” Further, enterprises “should use the same effort to find information to respond to a SAR as you would to find archived or backed-up data for your own purposes.”

Deleted Data: The ICO’s view on deleted data is that it is generally within the scope of GDPR compliance, provided that there is no intent to, or a systematic ability to readily recover that data. The ICO says it “will not seek to take enforcement action against an organisation that has failed to use extreme measures to recreate previously ‘deleted’ personal data held in electronic form. We do not require organisations to use time and effort reconstituting information that they have deleted as part of their general records management.”

However, under this guidance organizations that invest in and deploy re-purposed computer forensic tools that feature automated un-delete capabilities may be held to a higher standard. Deploying such systems can reflect intent to as well as having the systematic technical ability to recover deleted data.

Paper Records: Paper records that are part of a “structured filing system” are subject to the GDPR. Specifically, if an enterprise holds “information about the requester in non-electronic form (e.g. in paper files or on microfiche records)” then such hard-copy records are considered personal data accessible via the right of access,” if such records are “held in a ‘filing system.” This segment of the guidance reflects that references to “unstructured data” in European parlance usually pertains to paper records. The ICO notes in separate guidance that “the manual processing of unstructured personal data, such as unfiled handwritten notes on paper” are outside the scope of GDPR.

GDPR Article 4 defines a “filing system” as meaning “any structured set of personal data which are accessible according to specific criteria, whether centralized, decentralized or dispersed on a functional or geographical basis.” The only form of “unstructured data” that would not be subject to GDPR would be unfiled paper records like handwritten notes or legacy microfiche.

The CCPA  

The California Attorney General (AG) released a second and presumably final round of draft regulations under the California Consumer Privacy Act (CCPA) that reflect how unstructured electronic data will be treated under the Act. The proposed rules outline how the California AG is interpreting and will be enforcing the CCPA. Under § 999.313(d)(2), data from archived or backup systems are—unlike the GDPR—exempt from the CCPA’s scope, unless those archives are restored and become active. Additional guidance from the Attorney General states: “Allowing businesses to delete the consumer’s personal information on archived or backup systems at the time that they are accessed or used balances the interests of consumers with the potentially burdensome costs of deleting information from backup systems that may never be utilized.”

What is very notable is that the only technical exception to the CCPA is unrestored archived and back-up data. Like the GDPR, there is no distinction between unstructured and structured electronic data. In the first round of public comments, an insurance industry lobbying group argued that unstructured data be exempted from the CCPA. As reflected by revised guidance, that suggestion was rejected by the California AG.

For the GDPR, the UK ICO correctly advises that enterprises “should ensure that your information management systems are well-designed and maintained, so you can efficiently locate and extract information requested by the data subjects whose personal data you process and redact third party data where it is deemed necessary.” This is why Forrester Research notes that “Data Discovery and Classification are the foundation for GDPR compliance.”

Establish and Enforce Data Privacy Policies

So to achieve GDPR and CCPA compliance, organizations must first ensure that explicit policies and procedures are in place for handling personal information. Once established, it is important to demonstrate to regulators that such policies and procedures are being followed and operationally enforced. A key first step is to establish a data map of where and how personal data is stored in the enterprise. This exercise is actually required under the GDPR Article 30 documentation provisions.

An operational data audit and discovery capability across unstructured data sources allows enterprises to efficiently map, identify, and remediate personal information in order to respond to regulators and data subject access requests from EU and California citizens. This capability must be able to search and report across several thousand endpoints and other unstructured data sources, and return results within minutes instead of weeks or months as is the case with traditional crawling tools. This includes laptops of employees working from home.

These processes and capabilities are not only required for data privacy compliance but are also needed for broader information governance and security requirements, anti-fraud compliance, and e-discovery.

Implementing these measures proactively, with routine and consistent enforcement using solutions such as X1 Distributed GRC, will go a long way to mitigate risk, respond efficiently to data subject access requests, and improve overall operational effectiveness through such overall information governance improvements.

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How the Remote Workforce Impacts GDPR and CCPA Compliance

By John Patzakis

While our personal and business lives will hopefully return to normal soon, COVID-19 is only accelerating the trend of an increasingly remote and distributed workforce. This “new normal” will necessitate relying on the latest technology and updated workflows to comply with legal, privacy, and information governance requirements, including the GDPR and similar US-based laws.

A core requirement of both the GDPR and the similar California Consumer Privacy Act is the ability to demonstrate and prove that personal data is being protected, thus requiring information governance capabilities that allow companies to efficiently identify and remediate personal data of EU and California residents. For instance, the UK Information Commissioners Office (ICO) provides that “The GDPR places a high expectation on you to provide information in response to a SAR (Subject Access Request). Whilst it may be challenging, you should make extensive efforts to find and retrieve the requested information.”[1]CCPA Image

Under the GDPR, there is no distinction between structured versus unstructured electronic data in terms of the regulation’s scope. The key consideration is whether a data controller or processor has control over personal data, regardless of where it is located in the organization.

The UK ICO, a key government regulator that interprets and enforces the GDPR, recently issued important draft guidance on the scope of GDPR data subject access rights, including as it relates to unstructured electronic information. Notably, the ICO notes that “emails stored on your computer are a form of electronic record to which the general principles (under the GDPR) apply.” In fact, the ICO notes that home computers and personal email accounts of employees are subject to GDPR if they contain personal data originating from the employers networks or processing activities.[2]

CCPA          

The California Attorney General released second and presumably final round draft regulations under the California Consumer Privacy Act (CCPA) that reflect how unstructured electronic data will be treated under the Act.[3] The proposed rules outline how the California AG is interpreting and will be enforcing the CCPA. Under § 999.313(d)(2) data from archived or backup systems are —unlike the GDPR— exempt from the CCPA’s scope, unless those archives are restored and become active: “A business shall comply with a consumer’s request to delete their personal information by: a. Permanently and completely erasing the personal information on its existing systems with the exception of archived or back-up systems.”

What is very notable is that the only technical exception to the CCPA is unrestored archived and back-up data. Like the GDPR, there is no distinction between unstructured and structured electronic data. The CCPA guidance broadly provides that companies must permanently delete personal information from their “existing systems.” In the first round of public comments, an insurance industry lobbying group argued that unstructured data be exempted from the CCPA. As reflected by revised guidance, that suggestion was rejected by the California Attorney General.

Further to this point, AMLaw 100 firm Davis Wright Tremaine provides public guidance on the CCPA as follows: “Access requests may be easier for companies that maintain databases, but most companies also collect unstructured data (such as emails, images, files, etc.) related to consumers. Given that ‘personal information’ includes any information capable of being associated with a consumer or a household, requests will encompass a wide range of data that a business possesses.”[4]

So to achieve GDPR and CCPA compliance, organizations must ensure not only that explicit policies and procedures are in place for handling personal information, but also the ability to prove that those policies and procedures are being followed and operationally enforced. The new normal of remote workforces is a critical challenge that must be addressed.

What has always been needed is gaining immediate visibility into unstructured distributed data across the enterprise, including on laptops and other unstructured data maintained by remote workforces, through the ability to search and report across several thousand endpoints and other unstructured data sources, and return results within minutes instead of days or weeks. The need for such an operational capability provided by best practices technology is further heightened by the urgency of CCPA and GDPR compliance.

Solving this collection challenge is X1 Distributed Discovery, which is specially designed to address the challenges presented by remote and distributed workforces.  X1 Distributed Discovery (X1DD) enables enterprises to quickly and easily search across up to thousands of distributed endpoints and data servers from a central location.  Legal and compliance teams can easily perform unified complex searches across both unstructured content and metadata, obtaining statistical insight into the data in minutes, and full results with completed collection in hours, instead of days or weeks.

To learn more about this capability purpose-built for remote eDiscovery collection and data audits, please contact us.

NOTES:

[1] https://ico.org.uk/media/about-the-ico/consultations/2616442/right-of-access-draft-consultation-20191204.pdf

[2] Id.

[3] https://oag.ca.gov/sites/all/files/agweb/pdfs/privacy/ccpa-text-of-second-set-clean-031120.pdf?

[4] https://www.dwt.com/blogs/privacy–security-law-blog/2019/07/consumer-rights-under-to-ccpa-part-1-what-are-they

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CaCPA Compliance Requires Effective Investigation and eDiscovery Capabilities

By John Patzakis

The California Consumer Protection Act, (CaCPA ), which will be in full force on January 1, 2020,  promises to profoundly impact major US and global organizations, requiring the overhaul of their data audit, investigation and information governance processes. The CaCPA requires that an organization have absolute knowledge of where all personal data of California residents is stored across the enterprise, and be able to remove it when required. Many organization with a global reach will be under obligations to comply with both the GDPR and CaCPA, providing ample requirement justification to bolster their compliance efforts.

CCPA Image

According to data security and privacy attorney Patrick Burke, who was recently a senior New York State Financial Regular overseeing cybersecurity compliance before heading up the data privacy law practice at Phillips Nizer, CaCPA compliance effectively requires a robust digital investigation capability. Burke, speaking in a webinar earlier this month, noted that under the “CaCPA, California residents can request that all data an enterprise holds on them be identified and also be removed. Organizations will be required to establish a capability to respond to such requests. Actual demonstrated compliance will require the ability to search across all data sources in the enterprise for data, including distributed unstructured data located on desktops and file servers.” Burke further noted that organizations must be prepared to produce “electronic evidence to the California AG, which must determine whether there was a violation of CaCPA…as well as evidence of non-violation (for private rights of action) and of a ‘cure’ to the violation.”

The CaCPA contains similar provisions as the GDPR, which both specify processes and capabilities organizations must have in place to ensure the personal data of EU and California residents is secure, accessible, and can be identified upon request. These common requirements, enumerated below, can only be complied with through an effective enterprise eDiscovery search capability:

  • Data minimization: Under both the CaCPA and the GDPR, enterprises should only collect and retain as little personal data on California residents EU subjects as possible. As an example, Patrick Burke, who routinely advises his legal clients on these regulations, notes that unauthorized “data stashes” maintained by employees on their distributed unstructured data sources is a key problem, requiring companies to search all endpoints to identify information including European phone numbers, European email address domains and other personal identifiable information.
  • Enforcement of right to be forgotten: An individual’s personal data must be identified and deleted on request.
  • Effective incident response: If there is a compromise of personal data, an organization must have the ability to perform enterprise-wide data searches to determine and report on the extent of such breaches and resulting data compromise within seventy-two (72) hours under the GDPR. There are less stringent, but similar CaCPA requirements.
  • Accountability: Log and provide audit trails for all personal data identification requests and remedial actions.
  • Enterprise-wide data audit: Identify the presence of personal data in all data locations and delete unneeded copies of personal data.

Overall, a core requirement of both CaCPA and GDPR compliance is the ability to demonstrate and prove that personal data is being protected, requiring information governance capabilities that allow companies to efficiently produce the documentation and other information necessary to respond to auditors’ requests. Many consultants and other advisors are helping companies establish privacy compliance programs, and are documenting policies and procedures that are being put in place.

However, while policies, procedures and documentation are important, such compliance programs are ultimately hollow without consistent, operational execution and enforcement. CIOs and legal and compliance executives often aspire to implement information governance programs like defensible deletion and data audits to detect risks and remediate non-compliance. However, without an actual and scalable technology platform to effectuate these goals, those aspirations remain just that. For instance, recent IDG research suggests that approximately 70% of information stored by companies is “dark data” that is in the form of unstructured, distributed data that can pose significant legal and operational risks.

To achieve GDPR and CaCPA compliance, organizations must ensure that explicit policies and procedures are in place for handling personal information, and just as important, the ability to prove that those policies and procedures are being followed and operationally enforced. What has always been needed is gaining immediate visibility into unstructured distributed data across the enterprise, through the ability to search and report across several thousand endpoints and other unstructured data sources, and return results within minutes instead of days or weeks. The need for such an operational capability provided by best practices technology is further heightened by the urgency of CaCPA and GDPR compliance.

A link to the recording of the recent webinar “Effective Incident Response Under GDPR and CaCPA”, is available here.

 

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Incident Reporting Requirements Under GDPR and CCPA Require Effective Incident Response

By John Patzakis

The European General Data Protection Regulation (GDPR) is now in effect, but many organizations have not fully implemented compliance programs. For many organizations, one of the top challenges is complying with the GDPR’s tight 72-hour data breach notification window. Under GDPR article 33, breach notification is mandatory where a data breach is likely to “result in a risk for the rights and freedoms of individuals.” This must be done within 72 hours of first having become aware of the breach.  Data processors will also be required to notify their customers, the controllers, “without undue delay” after first becoming aware of a data breach.GDPR-stamp

In order to comply, organizations must accelerate their incident response times to quickly detect and identify a breach within their networks, systems, or applications, and must also improve their overall privacy and security processes. Being able to follow the GDPR’s mandate for data breach reporting is equally important as being able to act quickly when the breach hits. Proper incident response planning and practice are essential for any privacy and security team, but the GDPR’s harsh penalties amplify the need to be prepared.

It is important, however, to note that the GDPR does not mandate reporting for every network security breach. It only requires reporting for breaches impacting the “personal data” of EU subjects. And Article 33 specifically notes that reporting is not required where “the personal data breach is unlikely to result in a risk to the rights and freedoms of natural persons.”

The California Consumer Privacy Act contains similar provisions. Notification is only required if a California resident’s data is actually compromised.

So after a network breach is identified, determining whether the personal data of an EU or California citizen was actually compromised is critical not only to comply where a breach actually occurred, but also limit unnecessary or over reporting where an effective response analysis can rule out an actual personal data breach.

These breaches are perpetrated by outside hackers, as well as insiders. An insider is any individual who has authorized access to corporate networks, systems or data.  This may include employees, contractors, or others with permission to access an organizations’ systems. With the increased volume of data and the increased sophistication and determination of attackers looking to exploit unwitting insiders or recruit malicious insiders, businesses are more susceptible to insider threats than ever before.

Much of the evidence of the scope of computer security incidents and whether subject personal data was actually compromised are not found in firewall logs and typically cannot be flagged or blocked by intrusion detection or intrusion prevention systems. Instead, much of that information is found in the emails and locally stored documents of end users spread throughout the enterprise on file servers and laptops. To detect, identify and effectively report on data breaches, organizations need to be able to search across this data in an effective and scalable manner. Additionally, proactive search efforts can identify potential security violations such as misplaced sensitive IP, or personal customer data or even password “cheat sheets” stored in local documents.

To date, organizations have employed limited technical approaches to try and identify unstructured distributed data stored across the enterprise, enduring many struggles. For instance, forensic software agent-based crawling methods are commonly attempted but cause repeated high computer resource utilization for each search initiated and network bandwidth limitations are being pushed to the limits rendering this approach ineffective, and preventing any compliance within tight reporting deadlines. So being able to search and audit across at least several hundred distributed end points in a repeatable and expedient fashion is effectively impossible under this approach.

What has always been needed is gaining immediate visibility into unstructured distributed data across the enterprise, through the ability to search and report across several thousand endpoints and other unstructured data sources, and return results within minutes instead of days or weeks. None of the traditional approaches come close to meeting this requirement. This requirement, however, can be met by the latest innovations in enterprise eDiscovery software.

X1 Distributed GRC  represents a unique approach, by enabling enterprises to quickly and easily search across multiple distributed endpoints from a central location.  Legal, cybersecurity, and compliance teams can easily perform unified complex searches across both unstructured content and metadata, and obtain statistical insight into the data in minutes, instead of days or weeks. With X1 Distributed GRC, organizations can proactively or reactively search for confidential data leakage and also keyword signatures of personal data breach attacks, such as customized spear phishing attacks. X1 is the first product to offer true and massively scalable distributed searching that is executed in its entirety on the end-node computers for data audits across an organization. This game-changing capability vastly reduces costs and quickens response times while greatly mitigating risk and disruption to operations.

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USDOJ Expects Companies to Proactively Employ Data Analytics to Detect Fraud

By John Patzakis and Craig Carpenter

In corporate fraud enforcement actions, The US Department of Justice considers the effectiveness of a company’s compliance program as a key factor when deciding whether to bring charges and the severity of any resulting penalties. Recently, prosecutors increased their emphasis on this policy with new evaluation guidelines about what prosecutors expect from companies under investigation.DOJ

The USDOJ manual features a dedicated section on assessing the effectiveness of corporate compliance programs in corporate fraud prosecutions, including FCPA matters. This section is a must read for any corporate compliance professional, as it provides detailed guidance on what the USDOJ looks for in assessing whether a corporation is committed to good-faith self-policing or is merely making hollow pronouncements and going through the motions.

The USDOJ manual advises prosecutors to determine if the corporate compliance program “is adequately designed for maximum effectiveness in preventing and detecting wrongdoing by employees and whether corporate management is enforcing the program or is tacitly encouraging or pressuring employees to engage in misconduct to achieve business objectives,” and that “[p]rosecutors should therefore attempt to determine whether a corporation’s compliance program is merely a ‘paper program’ or whether it was designed, implemented, reviewed, and revised, as appropriate, in an effective manner.”

Recently, Deputy Assistant Attorney General Matthew Miner provided important additional guidance through official public comments establishing that the USDOJ will be assessing whether compliance officers proactively employ data analytics technology in their reviews of companies that are under investigation.

Miner noted that the Justice Department has had success in spotting corporate fraud by relying on data analytics, and said that prosecutors expect compliance officers to do the same: “This use of data analytics has allowed for greater efficiency in identifying investigation targets, which expedites case development, saves resources, makes the overall program of enforcement more targeted and effective.” Miner further noted that he “believes the same data can tell companies where to look for potential misconduct.” Ultimately, the federal government wants “companies to invest in robust and effective compliance programs in advance of misconduct, as well as in a prompt remedial response to any misconduct that is discovered.”

Finally, “if misconduct does occur, our prosecutors are going to inquire about what the company has done to analyze or track its own data resources—both at the time of the misconduct, as well as at the time we are considering a potential resolution,” Miner said. In other words, companies must demonstrate a sincere commitment to identifying and investigating internal fraud with proper resources employing cutting edge technologies, instead of going through the motions with empty “check the box” processes.

With these mandates from government regulators for actual and effective monitoring and enforcement through internal investigations, organizations need effective and operational mechanisms for doing so. In particular, any anti-fraud and internal compliance program must have the ability to search and analyze unstructured electronic data, which is where much of the evidence of fraud and other policy violations can be best detected.

But to utilize data analytics platforms in a proactive instead of a much more limited reactive manner, the process needs to be moved “upstream” where unstructured data resides. This capability is best enabled by a process that extracts text from unstructured, distributed data in place, and systematically sends that data at a massive scale to an analytics platform, with the associated metadata and global unique identifiers for each item.  One of the many challenges with traditional workflows is the massive data transfer associated with ongoing data migration of electronic files and emails, the latter of which must be sent in whole containers such as PST files. This process alone can take weeks, choke network bandwidth and is highly disruptive to operations. However, the load associated with text/metadata only is less than 1 percent of the full native item. So the possibilities here are very compelling. This architecture enables very scalable and proactive solutions to compliance, information security, and information governance use cases. The upload to AI engines would take hours instead of weeks, enabling continual machine learning to improve processes and accuracy over time and enable immediate action to be taken on identified threats or otherwise relevant information.

The only solution that we are aware of that fulfills this vision is X1 Enterprise Distributed GRC. X1’s unique distributed architecture upends the traditional collection process by indexing at the distributed endpoints, enabling a direct pipeline of extracted text to the analytics platform. This innovative technology and workflow results in far faster and more precise collections and a more informed strategy in any matter.

Deployed at each end point or centrally in virtualized environments, X1 Enterprise allows practitioners to query many thousands of devices simultaneously, utilize analytics before collecting and process while collecting directly into myriad different review and analytics applications like RelativityOne and Brainspace. X1 Enterprise empowers corporate eDiscovery, compliance, investigative, cybersecurity and privacy staff with the ability to find, analyze, collect and/or delete virtually any piece of unstructured user data wherever it resides instantly and iteratively, all in a legally defensible fashion.

X1 displayed these powerful capabilities with Compliance DS in a recent webinar with a brief but substantive demo of our X1 Distributed GRC solution, emphasizing our innovative support of analytics engines through our game-changing ability to extract text in place with a direct feed into AI solutions.

Here is a link to the recording with a direct link to the 5 minute demo portion.

In addition to saving time and money, these capabilities are important to demonstrate a sincere organizational commitment to compliance versus maintaining a mere “paper program” – which the USDOJ has just said can provide critical mitigation in the event of an investigation or prosecution.

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