Are Big Data Vendors Forgetting History?: Page 2

Companies adopting Big Data strategies would be well served by taking a look back at previous emerging technologies.


You Can't Detect What You Can't See: Illuminating the Entire Kill Chain

Posted November 25, 2013

Jeff Vance

(Page 2 of 2)

Ryan Betts, CTO of VoltDB, a NewSQL database vendor, does care, but even he, as deeply engrossed in the minute details as anyone, recognizes that the real point of Big Data is far less granular: “Data is only valuable when you can interact with it. Data you can’t interact with? That’s just overhead. Access and interactivity need to come first.”

4. But sometimes the techy details do matter.

For every rule, there’s the exception that proves the rule, and here’s one: SQL vs. NoSQL is a fight that will have real-world ramifications. NoSQL startups have been getting a lot of attention lately, with the likes of Cloudera, 10Gen and Datameer raising significant VC funding.

However, tech giants seem to be betting against NoSQL. “As SQL relational systems first came to market, many years ago, they competed with navigation and document oriented solutions. SQL won,” Betts pointed out. “The expressiveness and the flexibility to interact with data is why SQL matters. SQL is fast. SQL scales (witness Impala, BigQuery and Facebook’s announcement today). SQL matters to the marketplace – ask any ODBC-compliant BI vendor. To date first Google, then Apache Impala, and now Facebook have announced SQL interfaces to their large volume data stores. It’s nice to see ‘NoSQL’ learning the lessons of 30 years.”

Of course, the NoSQL camp has its own arguments for why their approach is better, but the smart money looks like it’s heading in the opposite direction – for now.

5. Being a skeptic is easy, but Big Data matters.

I recently attended a panel on Big Data where one of the panelists made some sarcastic comments about Big Data not being real, since it’s typically either capitalized or in quotes – or both.

I get the joke (although it’s not a terribly funny one), but many people take these jokes seriously.

Not too long ago, there was plenty of cloud skepticism, even from people who should have known better (such as Larry Ellison, until he saw the light and hastily directed Oracle to play cloud catch-up). Now, I hear plenty of Big Data skepticism, most of which is either stems from ignorance or an urge to protect the status quo.

Granted, some of the skepticism is well-earned, since vendors in hot spaces tend to hype the crap out of even something as trivial as a UI upgrade, but Big Data is here to stay, and it’s making an impact already.

Recently, Cryptolocker, which is arguably the most effective and sophisticated piece of ransomware released to date, was kept in check through Big Data analytics.

Cryptolocker's creators built a Domain Generation Algorithm that produces thousands of different rendezvous domains for the malware to try until it finally finds a command-and-control server. This tactic helps the malware evade static blacklists and reputation systems. Upon infecting a device, Cryptolocker must establish a connection with a command and control server to obtain an infection-specific encryption key, which is used to help the attacker receive the ransom payment later.

Using traditional detection and prevention methods, “it took about 30 days for security vendors to capture malware samples and reverse engineer them to come up with a way to contain it,” said Dan Hubbard, CTO of cyber-security service provider OpenDNS.

OpenDNS took a different approach to fend off Cryptolocker. Using Big Data analytics and predictive algorithms, OpenDNS’ Umbrella security service was able to block Cryptolocker from day one of the outbreak. The services identifies the patterns used by Cryptolocker's Domain Generation Algorithm and predicts the malicious sites it tries to connect with. Since the OpenDNS Umbrella service monitors inbound and outbound Internet traffic, it can block outbound Cryptolocker traffic and prevent machines that are infected from having their data encrypted.

“With Big Data-powered predictive security we are able to cut off the head of Cryptolocker and then pinpoint infected machines for disinfection,” Hubbard said.

That’s one security lesson that will, hopefully, not be lost to history.

Jeff Vance is a regular contributor to many high-tech and business-focused publications, including Forbes.com, Wired, Network World, CIO, Datamation and many others. Connect with him on LinkedIn (jeffvanceatsandstorm), follow him on Twitter @JWVance, or add him to your circles on Google Plus (+jeffvance).

Photo courtesy of Shutterstock.

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Tags: cloud computing, IT management, big data, enterprise technology

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