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punk2176 writes "Hacker and security researcher Alejandro Caceres (developer of the PunkSPIDER project) and 3D UI developer Teal Rogers unveiled a new free and open source tool at DEF CON 21 that could change the way that users view the web and its vulnerabilities. The project is a visualization system that combines the principles of offensive security, 3D data visualization, and 'big data' to allow users to understand the complex interconnections between websites. Using a highly distributed HBase back-end and a Hadoop-based vulnerability scanner and web crawler the project is meant to improve the average user's understanding of the unseen and potentially vulnerable underbelly of web applications that they own or use. The makers are calling this new method of visualization web 3.0. A free demo can be found here, where users can play with and navigate an early version of the tool via a web interface. More details can be found here and interested users can opt-in to the mailing list and eventually the closed beta here."

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Programmer Steve Losh has written a lengthy explanation of what separates good documentation from bad, and how to go about planning and writing documentation that will actually help people. His overarching point is that documentation should be used to teach, not to dump excessive amounts of unstructured information onto a user. Losh takes many of the common documentation tropes — "read the source," "look at the tests," "read the docstrings" — and makes analogies with learning everyday skills to show how silly they can be. "This is your driving teacher, Ms. Smith. ... If you have any questions about a part of the car while you’re driving, you can ask her and she’ll tell you all about that piece. Here are the keys, good luck!" He has a similar opinion of API strings: "API documentation is like the user’s manual of a car. When something goes wrong and you need to replace a tire it’s a godsend. But if you’re learning to drive it’s not going to help you because people don’t learn by reading alphabetized lists of disconnected information." Losh's advice for wikis is simple and straightforward: "They are bad and terrible. Do not use them."

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Original author: 
Sean Gallagher


NSA Headquarters in Fort Meade, MD.

mjb

One organization's data centers hold the contents of much of the visible Internet—and much of it that isn't visible just by clicking your way around. It has satellite imagery of much of the world and ground-level photography of homes and businesses and government installations tied into a geospatial database that is cross-indexed to petabytes of information about individuals and organizations. And its analytics systems process the Web search requests, e-mail messages, and other electronic activities of hundreds of millions of people.

No one at this organization actually "knows" everything about what individuals are doing on the Web, though there is certainly the potential for abuse. By policy, all of the "knowing" happens in software, while the organization's analysts generally handle exceptions (like violations of the law) picked from the flotsam of the seas of data that their systems process.

I'm talking, of course, about Google. Most of us are okay with what Google does with its vast supply of "big data," because we largely benefit from it—though Google does manage to make a good deal of money off of us in the process. But if I were to backspace over Google's name and replace it with "National Security Agency," that would leave a bit of a different taste in many people's mouths.

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Original author: 
Jon Brodkin

The Linux Foundation has taken control of the open source Xen virtualization platform and enlisted a dozen industry giants in a quest to be the leading software for building cloud networks.

The 10-year-old Xen hypervisor was formerly a community project sponsored by Citrix, much as the Fedora operating system is a community project sponsored by Red Hat. Citrix was looking to place Xen into a vendor-neutral organization, however, and the Linux Foundation move was announced today. The list of companies that will "contribute to and guide the Xen Project" is impressive, including Amazon Web Services, AMD, Bromium, Calxeda, CA Technologies, Cisco, Citrix, Google, Intel, Oracle, Samsung, and Verizon.

Amazon is perhaps the most significant name on that list in regard to Xen. The Amazon Elastic Compute Cloud is likely the most widely used public infrastructure-as-a-service (IaaS) cloud, and it is built on Xen virtualization. Rackspace's public cloud also uses Xen. Linux Foundation Executive Director Jim Zemlin noted in his blog that Xen "is being deployed in public IaaS environments by some of the world's largest companies."

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theodp writes "'Someday, and that day may never come,' Don Corleone says famously in The Godfather, 'I'll call upon you to do a service for me.' Back in 2010, filmmaker Lesley Chilcott produced Waiting for 'Superman', a controversial documentary that analyzed the failures of the American public education system, and presented charter schools as a glimmer of hope, including the Bill & Melinda Gates Foundation-backed KIPP Los Angeles Prep. Gates himself was a 'Superman' cast member, lamenting how U.S. public schools are producing 'American Idiots' of no use to high tech firms like Microsoft, forcing them to 'go half-way around the world to recruit the engineers and programmers they needed.' So some found it strange that when Chilcott teamed up with Gates again three years later to make Code.org's documentary short What Most Schools Don't Teach, kids from KIPP Empower Academy were called upon to demonstrate that U.S. schoolchildren are still clueless about what computer programmers do. In a nice coincidence, the film went viral just as leaders of Google, Microsoft, and Facebook pressed President Obama and Congress on immigration reform, citing a dearth of U.S. programming talent. And speaking of coincidences, the lone teacher in the Code.org film (James, Teacher@Mount View Elementary), whose classroom was tapped by Code.org as a model for the nation's schools, is Seattle teacher Jamie Ewing, who took top honors in Microsoft's Partners in Learning (PiL) U.S. Forum last summer, earning him a spot on PiL's 'Team USA' and the chance to showcase his project at the Microsoft PiL Global Forum in Prague in November (82-page Conference Guide). Ironically, had Ewing stuck to teaching the kids Scratch programming, as he's shown doing in the Code.org documentary, Microsoft wouldn't have seen fit to send him to its blowout at 'absolutely amazingly beautiful' Prague Castle. Innovative teaching, at least according to Microsoft's rules, 'must include the use of one or more Microsoft technologies.' Fortunately, Ewing's project — described in his MSDN guest blog post — called for using PowerPoint and Skype. For the curious, here's Microsoft PiL's vision of what a classroom should be."

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Aurich Lawson

Some say we're living in a "post-PC" world, but malware on PCs is still a major problem for home computer users and businesses.

The examples are everywhere: In November, we reported that malware was used to steal information about one of Japan's newest rockets and upload it to computers controlled by hackers. Critical systems at two US power plants were recently found infected with malware spread by USB drives. Malware known as "Dexter" stole credit card data from point-of-sale terminals at businesses. And espionage-motivated computer threats are getting more sophisticated and versatile all the time.

In this second installment in the Ars Guide to Online Security, we'll cover the basics for those who may not be familiar with the different types of malware that can affect computers. Malware comes in a variety of types, including viruses, worms, and Trojans.

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Board Room EmptyMost people and corporations are terrible at planning for the future, according to prominent futurist Dr. Peter Bishop of the University of Houston.

"The way the public — and particularly the way policy and decision makers talk about the future, is with way more certainty than they should have," Bishop explained in a phone conversation with Business Insider.

"To tell you what's going to happen is asking the wrong question," he said. "It's not what the future will be, but what it could be or what it might be. And the problem is that in the halls of decision, in the boardroom or the pentagon or something like that, That degree of uncertainty is not welcome."

Bishop says there are subtleties to future planning that can only be grasped by a futurist.

Several major corporations feel the same way, which is why Google just hired futurist Ray Kurzweil as director of engineering and Cisco employs furturist Dave Evans. Bishop himself has worked with IBM, NASA, Nestle, and more.

Says Bishop: "We're encouraging companies to spend a little bit of time thinking about the future, single digit percents. They don't do it because they don't know how to do it so they think it's a waste of time, and the reason that they don't know how is because nobody in their schools has ever taught them how to do it."

So what are the keys to thinking like a futurist?

Futurists think in terms of "multiple futures" rather than one. Not only does this increase the chances that one will have a plan for the actual future, but it also "intellectually conditions" one to adapt to change.

Futurists also see value in challenging basic assumptions.

 "What we do now is basically assume," says. Bishop. "Then we go on and make plans, and those assumptions are fine. The problem is we don't challenge those assumptions, and what we've been taught in physics class is to state your assumptions. We were never taught to say, 'and what if those assumptions are wrong? What's different about it?'"

Just look at what happened in New Orleans in 2005:

"One of the classic cases of this was the plan for responding in New Orleans to a hurricane, like Katrina in 2005. On the very first page of that plan, published by LSU under a grant from the Department of  Interior, and the very first assumption was, the levees will hold. They should say that, and they should make that assumption. The problem is that they should also have said, and what if they don't? Now that may have sent them off to go look at them, number one, that would have been a nice thing to do. And secondly ... what is the plan if the levees do not hold, because then water comes in pouring in from the lake and the river and stuff, and they had nothing about that."

Bishop says big changes are coming in our lifetime:

"There will be significant change within our tenure within any position within our lifetime for sure, that we will have to learn to live in a new world — to some extent. It's not completely new the way some futurists will say. But it will be new enough that we will be uncomfortable, we will be unprepared, and that we will have to learn new skills and new techniques in order to be successful in that future compared to how we are being successful today, or indeed how we were prepared to be successful when we were in school or training."

Now see futurist Ray Kurzweil's vision of the next 20 years >

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hal380The advent of Salesforce Marketing Cloud and Adobe Marketing Cloud demonstrates the need for enterprises to develop new ways of harnessing the vast potential of big data. Yet these marketing clouds beg the question of who will help marketers, the frontline of businesses, maximize marketing spending and ROI and help their brands win in the end. Simply moving software from onsite to hosted servers does not change the capabilities marketers require — real competitive advantage stems from intelligent use of big data.

Marc Benioff, who is famous for declaring that “Software Is Dead,” may face a similar fate with his recent bets on Buddy Media and Radian6. These applications provide data to people who must then analyze, prioritize and act — often at a pace much slower than the digital world. Data, content and platform insights are too massive for mere mortals to handle without costing a fortune. Solutions that leverage big data are poised to win — freeing up people to do the strategy and content creation that is best done by humans, not machines.

Big data is too big for humans to work with, at least in the all-important analytical construct of responding to opportunities in real time — formulating efficient and timely responses to opportunities generated from your marketing cloud, or pursuing the never-ending quest for perfecting search engine optimization (SEO) and search engine marketing (SEM). The volume, velocity and veracity of raw, unstructured data is overwhelming. Big data pioneers such as Facebook and eBay have moved to massive Hadoop clusters to process their petabytes of information.

In recent years, we’ve gone from analyzing megabytes of data to working with gigabytes, and then terabytes, and then petabytes and exabytes, and beyond. Two years ago, James Rogers, writing in The Street, wrote: “It’s estimated that 1 Petabyte is equal to 20 million four-door filing cabinets full of text.” We’ve become jaded to seeing such figures. But 20 million filing cabinets? If those filing cabinets were a standard 15 inches wide, you could line them up, side by side, all the way from Seattle to New York — and back again. One would need a lot of coffee to peruse so much information, one cabinet at a time. And, a lot of marketing staff.

Of course, we have computers that do the perusing for us, but as big data gets bigger, and as analysts, marketers and others seek to do more with the massive intelligence that can be pulled from big data, we risk running into a human bottleneck. Just how much can one person — or a cubicle farm of persons — accomplish in a timely manner from the dashboard of their marketing cloud? While marketing clouds do a fine job of gathering data, it still comes down to expecting analysts and marketers to interpret and act on it — often with data that has gone out of date by the time they work with it.

Hence, big data solutions leveraging machine learning, language models and prediction, in the form of self-learning solutions that go from using algorithms for harvesting information from big data, to using algorithms to initiate actions based on the data.

Yes, this may sound a bit frightful: Removing the human from the loop. Marketers indeed need to automate some decision-making. But the human touch will still be there, doing what only people can do — creating great content that evokes emotions from consumers — and then monitoring and fine-tuning the overall performance of a system designed to take actions on the basis of big data.

This isn’t a radical idea. Programmed trading algorithms already drive significant activity across stock markets. And, of course, Amazon, eBay and Facebook have become generators of — and consummate users of — big data. Others are jumping on the bandwagon as well. RocketFuel uses big data about consumers, sites, ads and prior ad performance to optimize display advertising. Turn.com uses big data from consumer Web behavior, on-site behaviors and publisher content to create, optimize and buy advertising across the Web for display advertisers.

The big data revolution is just beginning as it moves beyond analytics. If we were building CRM again, we wouldn’t just track sales-force productivity; we’d recommend how you’re doing versus your competitors based on data across the industry. If we were building marketing automation software, we wouldn’t just capture and nurture leads generated by our clients, we’d find and attract more leads for them from across the Web. If we were building a financial application, it wouldn’t just track the financials of your company, it would compare them to public filings in your category so you could benchmark yourself and act on best practices.

Benioff is correct that there’s an undeniable trend that most marketing budgets today are betting more on social and mobile. The ability to manage social, mobile and Web analysis for better marketing has quickly become a real focus — and a big data marketing cloud is needed to do it. However, the real value and ROI comes from the ability to turn big data analysis into action, automatically. There’s clearly big value in big data, but it’s not cost-effective for any company to interpret and act on it before the trend changes or is over. Some reports find that 70 percent of marketers are concerned with making sense of the data and more than 91 percent are concerned with extracting marketing ROI from it. Incorporating big data technologies that create action means that your organization’s marketing can get smarter even while you sleep.

Raj De Datta founded BloomReach with 10 years of enterprise and entrepreneurial experience behind him. Most recently, he was an Entrepreneur-In-Residence at Mohr-Davidow Ventures. Previously, he was a Director of Product Marketing at Cisco. Raj also worked in technology investment banking at Lazard Freres. He holds a BSE in Electrical Engineering from Princeton and an MBA from Harvard Business School.

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BYTE spoke to IT manager Brent Shinn at Double Fine Productions to see how he operates the lean IT department, what he thinks about Windows, and his feelings on BYOD in the workplace. While producing a video game traditionally costs millions of dollars and takes years to make, companies such as Double Fine are using consumer tools like Kickstarter to raise money and to speed up production.

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