Tag Archives: search

Authenticating Internet Web Pages as Evidence: a New Approach

By John Patzakis and Brent Botta

In recent posts, we have addressed the issue of evidentiary authentication of social media data. (See previous entries here and here). General Internet site data available through standard web browsing, instead of social media data provided by APIs or user credentials, presents slightly different but just as compelling challenges.

The Internet provides torrential amounts of evidence potentially relevant to litigation matters, with courts routinely facing proffers of data preserved from various websites. This evidence must be authenticated in all cases, and the authentication standard is no different for website data or chat room evidence than for any other. Under Federal Rule of Evidence 901(a), “The requirement of authentication … is satisfied by evidence sufficient to support a finding that the matter in question is what its proponent claims.” United States v. Simpson, 152 F.3d 1241, 1249 (10th Cir. 1998).

Ideally, a proponent of the evidence can rely on uncontroverted direct testimony from the creator of the web page in question. In many cases, however, that option is not available. In such situations, the testimony of the viewer/collector of the Internet evidence “in combination with circumstantial indicia of authenticity (such as the dates and web addresses), would support a finding” that the website documents are what the proponent asserts. Perfect 10, Inc. v. Cybernet Ventures, Inc. (C.D.Cal.2002) 213 F.Supp.2d 1146, 1154. (emphasis added) (See also, Lorraine v. Markel American Insurance Company, 241 F.R.D. 534, 546 (D.Md. May 4, 2007) (citing Perfect 10, and referencing MD5 hash values as an additional element of potential “circumstantial indicia” for authentication of electronic evidence).

One of the many benefits of X1 Social Discovery is its ability to preserve and display all the available “circumstantial indicia” – to borrow the Perfect 10 court’s term — to the user in order to present the best case possible for the authenticity of Internet-based evidence collected with the software. This includes collecting all available metadata and generating a MD5 checksum or “hash value” of the preserved data.

But html web pages pose unique authentication challenges and merely generating an MD5 checksum of the entire web page, or just the web page source file, provides limited value because web pages are constantly changing due to their very fluid and dynamic nature. In fact, a web page collected from the Internet in immediate succession would very likely calculate two different MD5 checksums. This is because web pages typically feature links to many external items that are dynamically loaded upon each page view. These external links take the form of cascading style sheets (CSS), graphical images, JavaScripts and other supporting files. This linked content can be stored on another server in the same domain, but is often located somewhere else on the Internet.

When the Web browser loads a web page, it consolidates all these items into one viewable page for the user. Since the Web page source file contains only the links to the files to be loaded, the MD5 checksum of the source file can remain unchanged even if the content of the linked files become completely different.  Therefore, the content of the linked items must be considered in the authenticity of the Web page. X1 Social Discovery addresses these challenges by first generating an MD5 checksum log representing each item that constitutes the Web page, including the main Web page’s source. Then an MD5 representing the content of all the items contained within the web page is generated and preserved.

To further complicate Web collections, entire sections of a Web page are often not visible to the viewer. These hidden areas serve various purposes, including metatagging for Internet search engine optimization. The servers that host Websites can either store static Web pages or dynamically created pages that usually change each time a user visits the Website, even though the actual content may appear unchanged.

In order to address this additional challenge, X1 Social Discovery utilizes two different MD5 fields for each item that makes a Web page.  The first is the acquisition hash that is from the actual collected information.  The second is the content hash.  The content hash is based on the actual “BODY” of a Web page and ignores the hidden metadata.  By taking this approach, the content hash will show if the user viewable content has actually changed, not just a hidden metadata tag provided by the server. To illustrate, below is a screenshot from the metadata view of X1 Social Discovery for website capture evidence, reflecting the generation of MD5 checksums for individual objects on a single webpage:

The time stamp of the capture and url of the web page is also documented in the case. By generating hash values of all individual objects within the web page, the examiner is better able to pinpoint any changes that may have occurred in subsequent captures. Additionally, if there is specific item appearing on the web page, such as an incriminating image, then is it is important to have an individual MD5 checksum of that key piece of evidence. Finally, any document file found on a captured web page, such as a pdf, Powerpoint, or Word document, will also be individually collected by X1 Social Discovery with corresponding acquisition and content hash values generated.

We believe this approach to authentication of website evidence is unique in its detail and presents a new standard. This authentication process supports the equally innovative automated and integrated web collection capabilities of X1 Social Discovery, which is the only solution of its kind to collect website evidence both through a one-off capture or full crawling, including on a scheduled basis, and have that information instantly reviewable in native file format through a federated search that includes multiple pieces of social media and website evidence in a single case. In all, X1 Social Discovery is a powerful solution to effectively collect from social media and general websites across the web for both relevant content and all available “circumstantial indicia.”

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Filed under Authentication, Best Practices, Preservation & Collection

Defining Truly Cloud-Capable eDiscovery Software

Last week we discussed the challenges of searching and collecting data in Infrastructure as a Service (IaaS) cloud deployments (such as the Amazon cloud or Rackspace) for eDiscovery purposes.  Today we discuss what is needed for eDiscovery and enterprise search vendors to provide a truly cloud-capable solution and provide a decoder ring of sorts to cut through the hype.  For there is a lot of hype with the cloud becoming the latest eDiscovery hot button, with vendor marketing claims far surpassing actual capabilities.

In fact, many eDiscovery and enterprise software vendors claim to support the cloud, but are simply re-branding their long-existing SaaS offerings, which really has nothing to do with supporting IaaS. Barry Murphy of the eDiscovery Journal aptly identified this marketing practice as “cloud washing.” Data hosting, especially where the vendor’s manual labor is routinely required to upload and process data, does not meet defined cloud standards. Neither does a process that primarily exports data through APIs or other means out of its resident cloud environment to slowly migrate the cloud data to the vendor tools, instead of deploying the tools (and their processing power) to the data where it resides in the cloud. In order to truly support IaaS cloud deployments, eDiscovery and enterprise search software must meet the following three core requirements:

1.         Automated installation and virtualization:  The eDiscovery and search solution must immediately and rapidly install, execute and efficiently operate in a virtualized environment without rigid hardware requirements or on-site physical access. This is impossible if the solution is fused to hardware appliances or otherwise requires a complex on-site installation process. As hardware appliance solutions by definition are not cloud deployable and with enterprise search installations often requiring many months of man hours to install and configure, whether many of these vendors will be able to support robust IaaS cloud deployments in the reasonably foreseeable future is a significant question.

2.         On-demand self-service: In its definition of cloud computing, The National Institute of Standards and Technology (NIST) identifies on- demand self-service as an essential characteristic of the cloud where a “consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with each service provider.”

Many hosted eDiscovery services require shipping of data to the provider or extensive behind the scenes manual labor to load and configure the systems for data ingestion. Conversely, solutions that truly support cloud IaaS will spin up, ingest data and fully operate in an automated fashion without the need for manual on-premise labor for configuration or data import.

3.         Rapid elasticity: NIST describes this characteristic as capabilities that “scale rapidly outward and inward commensurate with demand. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be appropriated in any quantity at any time.” This important benefit of cloud computing is accomplished by a parallelized software architecture designed to dynamically scale out over potentially several dozen virtualized servers to enable rapid ingestion, processing and analysis of data sets in that cloud environment. This capability would allow several terabytes of data to be indexed and processed within 2 to 4 hours on a highly automated basis at far less cost than non-cloud eDiscovery efforts.

However, many characteristics of leading eDiscovery solutions fundamentality prevent their ability to support this core cloud requirement. Most eDiscovery early case assessment solutions are developed and configured toward a monolithic processing schema designed to operate on a single expensive hardware apparatus. While recently spawning some bold marketing claims of high speeds and feeds, such architecture is very ill-suited to the cloud, which is powered by highly distributed processing across multitudes of servers. Additionally, many of the leading eDiscovery and enterprise search solutions are tightly integrated with third party databases and other OEM technology that cannot be easily decoupled (and also present possible licensing constraints) making such elasticity physically and even legally impossible.

So is there eDiscovery software that will truly support the IaaS cloud based upon these requirements, and address up to terabytes of data?  Stay tuned….

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Filed under Cloud Data, Enterprise eDiscovery, IaaS

eDiscovery Search and Collection in the Cloud

After several dozen posts on social media eDiscovery, we are going to focus the next few weeks on the related issue of eDiscovery in the cloud. As we see it, despite the enormous cost benefits of the cloud, concerns about the feasibility of eDiscovery and general search across an organization’s critical cloud-resident data has to some degree prevented broader adoption.

The cloud means many things to many people, but I believe the real eDiscovery action (and pain point) is in Infrastructure as a Service (IaaS) cloud deployments (such as the Amazon cloud, Rackspace, or pure enterprise cloud providers such as Fujitsu). According to a recent PwC report, Cloud IaaS will account for 30% of IT expenditures by 2014.  IaaS currently provides the means for organizations to aggressively store and virtualize their enterprise data and software, thus potentially spawning the same large data volumes and requiring the same critical search and eDiscovery requirements as traditional enterprise environments.  Amazon Web Services, the leading IaaS cloud provider, reports in our discussions with them extensive customer eDiscovery requirements that are currently addressed by inefficient and manual means.  So for purposes of this discussion, IaaS, which is essentially cloud for the enterprise and where there is a current significant eDiscovery challenge, is what we will focus on.

So if an organization maintains two terabytes of documents in the Amazon or Rackspace cloud, how do they quickly access, search, triage and collect that data in its existing cloud environment if a critical eDiscovery or compliance search requirement suddenly arises? This scenario is a current significant pain point for IaaS cloud.  In such situations, the organization is typically resorting to one of two agonizingly inefficient processes. The first option involves shipping the provider hard drives for their IT staff to copy the data in bulk for download and having that data shipped back. Rackspace’s guidelines provide that a transfer of 2 terabytes of bulk files would cost over $10,000 in fees and require about four to six weeks. And then all the company gets is a full 2 terabyte duplicate of its data that still must be searched, processed and reviewed.

The other alternative is to slowly download the data through a secure file transfer protocol connection. However, even with a robust T2 line, it would take three to six weeks to transfer the two TBs, depending on how much dedicated bandwidth IT would be willing to dedicate to the exercise.

So what is needed is robust eDiscovery software that can truly support the IaaS cloud where the data resides without first requiring mass data export. We will discuss what that entails and the requirements of truly cloud capable eDiscovery software in our next post, so please stay tuned!

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Filed under Cloud Data, IaaS

Can Lawyers Be Disqualified by Merely Viewing a Linkedin Profile? The Implications of Indirect Social Media Communications and Legal Ethics Rules

With attorneys and their hired consultants routinely collecting social media evidence for investigation and eDiscovery purposes, it is important to be aware that such activity can generate various direct and indirect communications to the subject account owners.  Sending a Facebook “friend” or a LinkedIn “connect” request are obvious examples, but there are also less overt means of social media communications. For instance, if a hypothetical law firm named Smith & Wesson were to merely follow a witness on Twitter, the service will automatically email the witness with a notification that Smith & Wesson is now following her. Additionally, it is all too easy when viewing a Facebook page to inadvertently “like” an item or accidentally send a friend request through a single mouse click.  And if you simply view another’s Linkedin profile while logged into your own account, that person will often be notified that you viewed his or her profile page.  Ethical Implication

For lawyers and their hired consultants and investigators, all this can be very problematic considering legal ethics rules that strictly regulate communications with represented parties and even jurors connected to a case. Several local and state bar associations have issued legal ethics opinions discussing this issue specific to collecting social media evidence. On December 6, X1 Discovery hosted a live webinar to delve deeper into this topic with the esteemed Ralph Losey of Jackson Lewis as the featured speaker. Ralph is the lead eDiscovery partner at Jackson Lewis and the author of “The eDiscovery Team,” considered by many to be the best legal eDiscovery blog on the planet. You can register for the recorded version of this webinar at this link here. (One hour of ethics CLE credit will be available to California attorneys).

From our perspective, this critical concern involving indirect social media communications and legal ethics underscores the importance of employing best practices technology to search and collect social media evidence for investigative and eDiscovery purposes.  Collecting evidence in a manner that prevents, or at minimum, does not require that attorneys and their proxies directly or indirectly communicate with the subjects from whom they are collecting social media evidence is a core requirement for solutions that truly address investigative and eDiscovery requirements for social media. If user credentials to the social media account have been properly obtained, that is obviously ideal. However, in many instances lawyers must resort to searching and collecting publicly available information. In such situations, it is crucial that the law firm and/or its hired experts conduct such collections in the proper manner.

For instance, X1 Social Discovery software features public Facebook capture that can search and collect publicly available Facebook pages without directly or indirectly notifying the account holder. This is critical functionality for eDiscovery preservation. Additionally, X1 Social Discovery accesses and displays Facebook pages in read-only mode, preventing metadata alternation, inadvertent friend requests or “like” tagging through a simple slip of the mouse. X1 Social Discovery includes other features concerning Twitter and Linkedin that also prevent indirect communications while effectively collecting data from those sites. We will be highlighting those features in the next few weeks, but in the meantime, we hope you enjoy our webinar.

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Filed under Best Practices, Legal Ethics & Social Media