Category Archives: Best Practices

Data Discovery “Is the Foundation of GDPR Compliance”

Recently, I attended a very informative Microsoft GDPR Summit in Redmond, Washington. Microsoft invited their key compliance partners to brief them on Microsoft’s strong support for GDPR compliance within their Office 365 ecosystem, and to engage them in their strategy. The summit featured a slate of legal, compliance and technology experts who provided compelling insight into the GDPR, including challenges and opportunities for organizations as the May 25 enforcement date approaches.

Enza Iannopollo, a featured keynote speaker from Forrester, is an industry analyst with a deep focus on information security, data privacy and GDPR compliance. She noted that per a recent Forrester security survey, only about 30 percent of organizations report GDPR readiness. In her talks with major organizations, Iannopollo sees a strong if not belated commitment as they scramble to achieve readiness ahead of May 18. In terms of what it takes to effectuate GDPR compliance, Iannopollo presented a slide which simply stated the following: “Data Discovery and classification are the foundation of GDPR compliance.” Iannopollo said this is because the GDPR effectively requires that an organization be able to identify and actually locate, with precision, personal data of EU data subjects across the organization.

The speakers identified both a proactive and reactive requirement of data discovery under the GDPR. Iannopollo commented that a robust data discovery capability is needed to produce an intelligent data map, to classify and actually remediate non-compliant data. This data audit process should done at the outset, and also routinely executed on a recurring basis.

For reactive capabilities, Microsoft deputy general counsel John Payseno noted in a separate session that once GDPR enforcement comes online on May 25, 2018, organizations will be required to respond to data subject requests (DSRs) from individual, or groups of, EU data subjects. The DSRs under the GDPR consist of requests for data erasure, data transfer, or a confirmation that data permissively kept is done so in a minimal fashion without excessive duplication or re-purposing outside of the granted consent. Payseno said that companies must be able to document and demonstrate compliance with these DSRs, in a manner generally akin to responding to a subpoena or other legal requirement.

So a clear takeaway from the Microsoft summit is that GDPR compliance requires the ability to demonstrate and prove that personal data is being protected, requiring data audit and discovery capabilities that allow companies to efficiently produce the documentation and other information necessary to respond to regulators and EU private citizen’s requests. As such, any GDPR compliance programs are ultimately hollow without consistent, operational execution and enforcement.

While Microsoft demonstrated their capabilities to conduct effective data discovery in their O365 cloud environment, they openly acknowledge a significant gap for addressing on-premise unstructured data. Effective GDPR compliance requires the ability to gain 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 weeks or months as is the case with traditional crawling tools.

X1 Distributed Discovery (X1DD) represents a unique approach, by enabling enterprises to quickly and easily search across multiple distributed endpoints and data servers for PII and other data 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, instead of days or weeks. With X1DD, organizations can also automatically migrate, collect, delete, or take other action on the data as a result of the search parameters.  Built on our award-winning and patented X1 Search technology, X1DD 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 while greatly mitigating risk and disruption to operations.

X1DD operates on-demand where your data currently resides — on desktops, laptops, servers, or even the Cloud — without disruption to business operations and without requiring extensive or complex hardware configurations. Beyond enterprise eDiscovery, GDPR and other information governance compliance functionality, X1DD includes the award-winning X1 Search, improving employee productivity while effectuating that all too illusive actual compliance with information governance programs, including GDPR.

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Filed under Best Practices, compliance, Corporations, Data Audit, GDPR, Hybrid Search, Information Governance, Uncategorized

Practice Tool: Sample FRE 902(14) Certification to Authenticate Social Media Evidence

Update: Law Firm Baker Hostetler has posted a good 902(14) model certification as well.

As part of our continuing coverage of Federal Rule of Evidence 902(14), which goes into effect on Friday December 1, 2017, we will be making available further resources and analysis over the next few weeks in support of this new and important development. To review, FRE 902(14) provides that electronic data recovered “by a process of digital identification” is to be self-authenticating, thereby not routinely necessitating the trial testimony of a forensic or technical expert where best practices are employed. Instead, such properly collected electronic evidence can be certified through a written declaration by a “qualified person.” This rule will have a significant impact on computer forensics and eDiscovery collection practices. A detailed discussion of Rule 902(14) can be found here.

Today we are providing an example of a Rule 902(14) certification for the authentication of social media evidence collected by X1 Social Discovery. This sample document is for general information purposes only. Your use of this example 902(14) certification is at your own risk, and you should not use this sample documents without first seeking professional legal advice. The provision of this sample document (and the document itself) does not constitute legal advice or opinions of any kind. So with those legal disclaimers, here is the sample 902(14) certification:

Certification under Federal Rule of Evidence 902(14)

(Example Only for demonstration purposes)

 

I, __________________, hereby declare and certify:

 

  1. I am currently a (paralegal) (computer forensic specialist) (electronic discovery specialist) employed by “My Organization” (“My Organization”). My Organization specializes in the discovery, collection, investigation, and production of electronic information for investigating and handling computer-related crimes and misuse as well as for in support of discovery for civil litigation matters. I am responsible for conducting computer forensic investigations and providing electronic discovery and litigation support.

 

  1. I have participated in more than 100 investigations and preservation efforts from social media sites and other Internet websites, and was the lead on approximately 20 of those investigations. These investigations involved finding relevant electronic information in support of internal investigations, civil litigation and criminal matters. In the course of these investigations, I was responsible for performing in-depth analyses and providing documentation and related materials in support of criminal and civil matters for law firms/litigation support consulting firms, (or for law enforcement agencies at the federal and local level)

 

  1. I have accumulated extensive experience in the identification, preservation, retrieval, analysis, and documentation of computer-related information, including both data at rest and social media evidence and other internet based electronic evidence in support of computer investigations and ongoing litigation matters.

 

  1. I am a licensed user of X1 Social Discovery (“X1”), the leading software used by law firms, law enforcement, government regulatory agencies and litigation support consultants world-wide. X1 Social Discovery is available for purchase by the general public and is generally accepted in the eDiscovery and computer investigation industry. X1 Social Discovery aggregates comprehensive social media content and web-based data into a single user interface, while preserving critical metadata not possible through image capture “screenshot”, or simple computer screen printouts.

 

  1. X1 Social Discovery includes an automated function to generate an MD5 “hash value” immediately upon the collection of an item of social media evidence or a webpage. The Committee notes to Federal Rule of Evidence 902(14) define a hash value as follows: “Today, data copied from electronic devices, storage media, and electronic files are ordinarily authenticated by ‘hash value.’ A hash value is a number that is often represented as a sequence of characters and is produced by an algorithm based upon the digital contents of a drive, medium, or file. If the hash values for the original and copy are different, then the copy is not identical to the original. If the hash values for the original and copy are the same, it is highly improbable that the original and copy are not identical. Thus, identical hash values for the original and copy reliably attest to the fact that they are exact duplicates.”

 

  1. X1 Discovery, Inc., the software company that develops X1 Social Discovery, makes freely available a separate hash value verification software utility that will recalculate the hash value of an item of electronic evidence that was previously collected by X1 Social Discovery to verify that the evidence has not changed since it was collected by X1. If the “verification” hash value generated by the verification utility is the same as the hash value originally calculated by X1 Social Discovery at the time of the acquisition of the item of electronic evidence, then the identical hash values reliably attest to the fact that the evidence, and any exact duplicates thereof, have not changed.

 

  1. I was retained by attorneys for Defendants to provide examination, preservation and analysis of social media evidence in the present case. Pursuant to this request I collected numerous social media evidence from Twitter, Instagram, and Facebook using the X1 Social Discovery software. Attached as Exhibit “A” are the following items of social media evidence:

 

  1. A Facebook post that was publicly available on Plaintiff’s Facebook dated July 10, 2017, which was acquired by me on September 3, 2017 at 3:45pm.
  2. A Twitter post (Tweet) that was publicly available on Acme company’s Twitter feed dated July 13, 2017, which was acquired by me on September 3, 2017 at 3:48pm.
  3. An Instagram post that was publicly available on Plaintiff’s spouses’ Instagram feed dated July 18, 2017, which was acquired by me on September 3, 2017 at 3:55pm.

 

  1. When the items described above were acquired by X1 Social Discovery, the software automatically generated and assigned a hash value based upon the contents of the evidence. This is termed the “acquisition hash.” Using the hash value verification software utility, I recalculated the hash value of the 3 items listed above, on 12/4/17, shortly before I prepared this declaration. The verification hash in all instances were the same as the acquisition hash value, as set forth in the following table:

902 Certification Table

  1. The identical hash values reliably attest to the fact that the evidence has not changed.

 

I declare under penalty of perjury under the laws of the United States of America that the foregoing is true and correct. Executed this _th day of December 2017 in Los Angeles, California.

 

 

______________________

Signature of Declarant

 

Download a copy of this example Certification here >

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Filed under Authentication, Best Practices, Social Media Investigations, Uncategorized

New Federal Rule of Evidence to Directly Impact Computer Forensics and eDiscovery Preservation Best Practices

At X1, an essential component of our mission is to develop and support exceptional technology for collecting electronic evidence to meet eDiscovery, investigative and compliance requirements. It is also our goal to keep you abreast of important developments in the industry that could ultimately impact collection strategies in the future and, consequently, your business.  To that end, we believe key new Federal Rules of Evidence will have a very significant impact on the practices of our customers and partners.

In a nutshell, the new development is a significant planned amendment to Federal Rule of Evidence 902 that will go into effect one year from now. This amendment, in the form of new subsection (14), is anticipated by the legal community to significantly impact eDiscovery and computer forensics software and its use by establishing that electronic data recovered “by a process of digfederalrulesofevidence-188x300_flat2ital identification” is to be self-authenticating, thereby not routinely necessitating the trial testimony of a forensic or technical expert where best practices are employed, as certified through a written affidavit by a “qualified person.” Notably, the accompanying official Advisory Committee notes specifically reference the importance of both generating “hash values” and verifying them post-collection as a means to meet this standard for self-authentication. This digital identification and verification process can only be achieved with purpose-built computer forensics or eDiscovery collection and preservation tools.

Rule 902, in its current form, enumerates a variety of documents that are presumed to be self-authenticating without other evidence of authenticity. These include public records and other government documents, notarized documents, newspapers and periodicals, and records kept in the ordinary course of business. New subpart (14) will now include electronic data collected via a process of digital identification as a key addition to this important rule.

Amended Rule 902, in pertinent part, reads as follows:

Rule 902. Evidence That Is Self-Authenticating
The following items of evidence are self-authenticating; they require no extrinsic evidence of authenticity in order to be admitted:
* * *
(14) Certified Data Copied from an Electronic Device, Storage Medium, or File.
Data copied from an electronic device, storage medium, or file, if authenticated by a process of digital identification, as shown by a certification of a qualified person that complies with the certification requirements of Rule 902(11) or (12).

The reference to the “certification requirements of Rule 902(11) or (12)” is a process by which a proponent seeking to introduce electronic data into evidence must present a certification in the form of a written affidavit that would be sufficient to establish authenticity were that information provided by a witness at trial. This affidavit must be provided by a “qualified person,” which generally would be a computer forensics, eDiscovery or information technology practitioner, who collected the evidence and can attest to the requisite process of digital identification utilized.

In applying Rule 902(14), the courts will heavily rely on the accompanying Judicial Conference Advisory Committee notes, which provide guidance and insight concerning the intent of the laws and how they should be applied. The Advisory Committee notes are published alongside the statute and are essentially considered an extension of the rule. The second paragraph of committee note to Rule 902(14) states, in its entirety, as follows:

“Today, data copied from electronic devices, storage media, and electronic files are ordinarily authenticated by ‘hash value.’ A hash value is a number that is often represented as a sequence of characters and is produced by an algorithm based upon the digital contents of a drive, medium, or file. If the hash values for the original and copy are different, then the copy is not identical to the original. If the hash values for the original and copy are the same, it is highly improbable that the original and copy are not identical. Thus, identical hash values for the original and copy reliably attest to the fact that they are exact duplicates. This amendment allows self-authentication by a certification of a qualified person that she checked the hash value of the proffered item and that it was identical to the original. The rule is flexible enough to allow certifications through processes other than comparison of hash value, including by other reliable means of identification provided by future technology.”

The Advisory Committee notes further state that Rule 902(14) is designed to streamline the admission of electronic evidence where its foundation is not at issue, while providing a notice procedure where “the parties can determine in advance of trial whether a real challenge to authenticity will be made, and can then plan accordingly.” While this rule provides that properly certified electronic data is now afforded a strong presumption of authenticity, the opponent may still lodge an objection, but the opponent now has the burden to overcome that presumption.  Additionally, the opponent remains free to object to admissibility on other grounds, such as relevance or hearsay.

Significant Impact Expected

While Rule 902(14) applies to the Federal Courts, the Rules of Evidence for most states either mirror or closely resemble the Federal Rules of Evidence, and it is thus expected that most if not all 50 states will soon adapt this amendment.

Rule 902(14) will most certainly and significantly impact computer forensics and eDiscovery practitioners by reinforcing best practices. The written certification required by Rule 902(14) must be provided by a “qualified person” who utilized best practices for the collection, preservation and verification of the digital evidence sought to be admitted. At the same time, this rule will in effect call into question electronic evidence collection methods that do not enable a defensible “digital identification” and verification process. In fact, the Advisory Committee notes specifically reference the importance of computer forensics experts, noting that a “challenge to the authenticity of electronic evidence may require technical information about the system or process at issue, including possibly retaining a forensic technical expert.”

In the eDiscovery context, I have previously highlighted the perils of both custodian self-collection for enterprise ESI collection and “print screen” methods for social media and website preservation. Rule 902(14) should provide the final nail in the coffin for those practices. For instance, if key social media evidence is collected through manual print screen, which is not a “process of digital identification” under Rule 902(14), then not only will the proponent of that evidence fail to take advantage of the efficiencies and cost-savings provided by the rule, they will also invite heightened scrutiny for not preserving the evidence utilizing best practices. The same is true for custodian self-collection in the enterprise. Many emails and other electronic documents preserved and disclosed by the producing party are often favorable to their case.  Without best practices utilized for enterprise data collection, such as with X1 Distributed Discovery, that information may not be deemed self-authenticating under this new rule.

In the law enforcement field, untrained patrol officers or field investigators are too often collecting electronic evidence in a manual and haphazard fashion, without utilizing the right tools that qualify as a “process of digital identification.” So for an example, if an untrained investigator collects a web page via the computer’s print screen process, that printout will not be deemed to be self-authenticating under Rule 902(14), and will face significant evidentiary hurdles compared to a properly collected web page via a solution such as X1 Social Discovery.

Also being added to Federal Rule of Evidence 902 is subpart (13), which provides that “a record generated by an electronic process or system that produces an accurate result” is similarly self-authenticating. This subpart will also have a beneficial impact on the computer forensics and eDiscovery field, but to a lesser degree than subpart (14). I will be addressing Rule 902(13) in a future post. The public comment period on amendments (13) and (14) is now closed and the Judicial Conference of the United States has issued its final approval. The amendments are currently under review by the US Supreme Court. If the Supreme Court approves these amendments as expected, they will become effective on December 1, 2017 absent Congressional intervention.

To learn more about this Rule 902(14) and other related topics, we’d like to invite you to watch this 45 minute webinar discussion led by David Cohen, Partner and Chair of Records & eDiscovery Group at Reed Smith LLP. The 45 minute webinar includes a Q&A following the discussion. We look forward to your participation.

Watch now > 

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Filed under Authentication, Best Practices, eDiscovery, eDiscovery & Compliance, Enterprise eDiscovery, Information Governance, Social Media Investigations

Effective Information Governance Requires Effective Enterprise Technology

Information governance is the compilation of policies, processes, and controls enforced and executed with effective technology to manage electronically stored information throughout the enterprise. Leading IT industry research firm Gartner states that “the goal of information governance is to ensure compliance with laws and regulations, mitigate risks and protect the confidentiality of sensitive company and customer data.” A strong, proactive information governance strategy that strikes the balance between under-retention and over-retention of information can provide dramatic cost savings while significantly reducing risk.

However, while policies, procedures and documentation are important, information governance 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, data migration, 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 risk and cost.

To date, organizations have employed limited technical approaches to try and execute on their information governance initiatives, enduring many struggles. For instance, software agent-based crawling methods are commonly attempted and can cause repeated high user computer resources utilization for each search initiated and network bandwidth limitations being pushed to the limits rendering the approach ineffective. So being able to search and audit across at least several hundred distributed end points in a repeatable and quick fashion is effectively impossible under this approach.

Another tactic attempted by some CIOs to attempt to address this daunting challenge is to periodically migrate disparate data from around the global enterprise into a central location. The execution of this strategy will still leave the end user’s computer needing to be scanned as there is never a moment when all users in the enterprise have just finished this process with no new data created. That means now that both the central repository and the end-points will need to be searched and increasing the complexity and management of the job. Boiling the ocean through data migration and centralization is extremely expensive, highly disruptive, and frankly unworkable as it never removes the need to conduct constant local computer searching, again through problematic crawling methods.

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 other approaches outlined above come close to meeting this requirement and in fact actually perpetuate information governance failures.

X1 Distributed Discovery (X1DD) represents a unique approach, by enabling enterprises to quickly and easily search across multiple 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, instead of days or weeks. With X1DD, organizations can also automatically migrate, collect, or take other action on the data as a result of the search parameters.  Built on our award-winning and patented X1 Search technology, X1DD 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 while greatly mitigating risk and disruption to operations.

X1DD operates on-demand where your data currently resides — on desktops, laptops, servers, or even the Cloud — without disruption to business operations and without requiring extensive or complex hardware configurations. Beyond enterprise eDiscovery and information governance functionality, organizations offer employees at the same time, the award-winning X1 Search, improving productivity while effectuating that all too illusive actual compliance with information governance programs.

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Filed under Best Practices, eDiscovery & Compliance, Information Governance, Information Management, Records Management, SharePoint, X1 Search 8