FeaturedReed Elsevier Lexis Nexis Embraces Legal Analytics: No, Not an Oxymoron
Lawyers and legal search and content processing systems do words. The analytics part of life, based on my limited experience of watching attorneys do mathy stuff, is not these folks’ core competency. Words. Oh, and billing. I can’t overlook billing.
I read “Now It’s Official: Lexis Nexis Acquires Lex Machina.” This is good news for the stakeholders of Lex Machina. Reed Elsevier certainly expects Lex Machina’s business processes to deliver an avalanche of high margin revenue. One can only raise prices so far before the old chestnut from Economics 101 kicks in: Price elasticity. Once something is too expensive, the customers kick the habit, find an alternative, or innovate in remarkable ways.
According to the write up:
LexisNexis today announced the acquisition of Silicon Valley-based Lex Machina, creators of the award-winning Legal Analytics platform that helps law firms and companies excel in the business and practice of law.
So what does legal analytics do? Here’s the official explanation, which is in, gentle reader, words:
- A look into the near future. The integration of Lex Machina Legal Analytics with the deep collection of LexisNexis content and technology will unleash the creation of new, innovative solutions to help predict the results of legal strategies for all areas of the law.
- Industry narrative. The acquisition is a prominent and fresh example of how a major player in legal technology and publishing is investing in analytics capabilities.
I don’t exactly know what Lex Machina delivers. The company’s Web page states:
We mine litigation data, revealing insights never before available about judges, lawyers, parties, and patents, culled from millions of pages of IP litigation information. We call these insights Legal Analytics, because analytics involves the discovery and communication of meaningful patterns in data. Our customers use to win in the highly competitive business and practice of law. Corporate counsel use Lex Machina to select and manage outside counsel, increase IP value and income, protect company assets, and compare performance with competitors. Law firm attorneys and their staff use Lex Machina to pitch and land new clients, win IP lawsuits, close transactions, and prosecute new patents.
I think I understand. Lex Machina applies the systems and methods used for decades by companies like BAE Systems (Detica/ NetReveal) and similar firms to provide tools which identify important items. (BAE was one of Autonomy’s early customers back in the late 1990s.) Algorithms, not humans reading documents in banker boxes, find the good stuff. Costs go down because software is less expensive than real legal eagles. Partners can review outputs and even visualizations. Revolutionary.
InterviewsExclusive Interview: Danny Rogers, Terbium Labs
Editor’s note: The full text of the exclusive interview with Dr. Daniel J. Rogers, co-founder of Terbium Labs, is available on the Xenky Cyberwizards Speak Web service at www.xenky.com/terbium-labs. The interview was conducted on August 4, 2015.
Significant innovations in information access, despite the hyperbole of marketing and sales professionals, are relatively infrequent. In an exclusive interview, Danny Rogers, one of the founders of Terbium Labs, has developed a way to flip on the lights to make it easy to locate information hidden in the Dark Web.
Web search has been a one-trick pony since the days of Excite, HotBot, and Lycos. For most people, a mobile device takes cues from the user’s location and click streams and displays answers. Access to digital information requires more than parlor tricks and pay-to-play advertising. A handful of companies are moving beyond commoditized search, and they are opening important new markets such as secret and high value data theft. Terbium Labs can “illuminate the Dark Web.”
In an exclusive interview, Dr. Danny Rogers, one of the founders of Terbium Labs with Michael Moore, explained the company’s ability to change how data breaches are located. He said:
Typically, breaches are discovered by third parties such as journalists or law enforcement. In fact, according to Verizon’s 2014 Data Breach Investigations Report, that was the case in 85% of data breaches. Furthermore, discovery, because it is by accident, often takes months, or may not happen at all when limited personnel resources are already heavily taxed. Estimates put the average breach discovery time between 200 and 230 days, an exceedingly long time for an organization’s data to be out of their control. We hope to change that. By using Matchlight, we bring the breach discovery time down to between 30 seconds and 15 minutes from the time stolen data is posted to the web, alerting our clients immediately and automatically. By dramatically reducing the breach discovery time and bringing that discovery into the organization, we’re able to reduce damages and open up more effective remediation options.
Terbium’s approach, it turns out, can be applied to traditional research into content domains to which most systems are effectively blind. At this time, a very small number of companies are able to index content that is not available to traditional content processing systems. Terbium acquires content from Web sites which require specialized software to access. Terbium’s system then processes the content, converting it into the equivalent of an old-fashioned fingerprint. Real-time pattern matching makes it possible for the company’s system to locate a client’s content, either in textual form, software binaries, or other digital representations.
One of the most significant information access innovations uses systems and methods developed by physicists to deal with the flood of data resulting from research into the behaviors of difficult-to-differentiate sub atomic particles.
One part of the process is for Terbium to acquire (crawl) content and convert it into encrypted 14 byte strings of zeros and ones. A client such as a bank then uses the Terbium content encryption and conversion process to produce representations of the confidential data, computer code, or other data. Terbium’s system, in effect, looks for matching digital fingerprints. The task of locating confidential or proprietary data via traditional means is expensive and often a hit and miss affair.
Terbium Labs changes the rules of the game and in the process has created a way to provide its licensees with anti-fraud and anti-theft measures which are unique. In addition, Terbium’s digital fingerprints make it possible to find, analyze, and make sense of digital information not previously available. The system has applications for the Clear Web, which millions of people access every minute, to the hidden content residing on the so called Dark Web.
Terbium Labs, a start up located in Baltimore, Maryland, has developed technology that makes use of advanced mathematics—what I call numerical recipes—to perform analyses for the purpose of finding connections. The firm’s approach is one that deals with strings of zeros and ones, not the actual words and numbers in a stream of information. By matching these numerical tokens with content such as a data file of classified documents or a record of bank account numbers, Terbium does what strikes many, including myself, as a remarkable achievement.
Terbium’s technology can identify highly probable instances of improper use of classified or confidential information. Terbium can pinpoint where the compromised data reside on either the Clear Web, another network, or on the Dark Web. Terbium then alerts the organization about the compromised data and work with the victim of Internet fraud to resolve the matter in a satisfactory manner.
Terbium’s breakthrough has attracted considerable attention in the cyber security sector, and applications of the firm’s approach are beginning to surface for disciplines from competitive intelligence to health care.
We spent a significant amount of time working on both the private data fingerprinting protocol and the infrastructure required to privately index the dark web. We pull in billions of hashes daily, and the systems and technology required to do that in a stable and efficient way are extremely difficult to build. Right now we have over a quarter trillion data fingerprints in our index, and that number is growing by the billions every day.
The idea for the company emerged from a conversation with a colleague who wanted to find out immediately if a high profile client list was ever leaded to the Internet. But, said Rogers, “This individual could not reveal to Terbium the list itself.”
How can an organization locate secret information if that information cannot be provided to a system able to search for the confidential information?
The solution Terbium’s founders developed relies on novel use of encryption techniques, tokenization, Clear and Dark Web content acquisition and processing, and real time pattern matching methods. The interlocking innovations have been patented (US8,997,256), and Terbium is one of the few, perhaps the only company in the world, able to crack open Dark Web content within regulatory and national security constraints.
I think I have to say that the adversaries are winning right now. Despite billions being spent on information security, breaches are happening every single day. Currently, the best the industry can do is be reactive. The adversaries have the perpetual advantage of surprise and are constantly coming up with new ways to gain access to sensitive data. Additionally, the legal system has a long way to go to catch up with technology. It really is a free-for-all out there, which limits the ability of governments to respond. So right now, the attackers seem to be winning, though we see Terbium and Matchlight as part of the response that turns that tide.
Terbium’s product is Matchlight. According to Rogers:
Matchlight is the world’s first truly private, truly automated data intelligence system. It uses our data fingerprinting technology to build and maintain a private index of the dark web and other sites where stolen information is most often leaked or traded. While the space on the internet that traffics in that sort of activity isn’t intractably large, it’s certainly larger than any human analyst can keep up with. We use large-scale automation and big data technologies to provide early indicators of breach in order to make those analysts’ jobs more efficient. We also employ a unique data fingerprinting technology that allows us to monitor our clients’ information without ever having to see or store their originating data, meaning we don’t increase their attack surface and they don’t have to trust us with their information.
Stephen E Arnold, August 11, 2015
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