Experian Hitwise today announced that Google accounted for 72.17 percent of all U.S. searches conducted in the four weeks ending May 29, 2010. Yahoo! Search, Bing and Ask received 14.43 percent, 9.23 percent and 2.14 percent, respectively.
Google always has a lot going on but one of the things that set the net abuzz was the launch of the new Google TV service. Instead of having a TV screen and separate computer screen users will now finally be able to combine the two with the power of Google’s ultra fast search-indexing.
As long as advertisers pay for clicks, there will be click fraud. And the more people combat it, the more sophisticated the attacks become to get around the defenses that advertisers, search engines, and others put in place. But a recent click fraud ring discovered by click-fraud monitoring service Anchor Intelligence suggests that the practice is evolving to a scale never seen before.
Anchor Intelligence identified a click fraud ring being run out of China which involved 200,000 different IP addresses and racked up more than $3 million worth of fraudulent clicks across 2,000 advertisers in a two-week period. That money was never paid out and the ring has now dissipated (or moved onto another scam), but who knows how long the ring was in operation before Anchor noticed. The operation was called DormRing1 because it was centered in dorms at technical universities in China such as the Shanghai Technology Institute.
“We have seen 200 fraud rings,” says Anchor VP Richard Sim, “and this one by far trumps them all. I think it is indicative of how sophisticated the click fraud is getting. We are seeing the sheer scale and size of these rings growing.”
Click fraud occurs when someone sets up a website, signs up with an ad network, and then clicks on the ads to generate ad revenues with false clicks. DormRing1 operated the same way, except it easily involved more than 1,000 people who set up more than 10,000 Websites to spread out the fraud. The image above depicts a portion of the ring, with each red dot representing a source of fraudulent clicks with similar digital signatures. (Anchor monitors such activity on behalf of advertising clients).
Spreading the click fraud out across thousands of sites makes it harder to detect, but it also requires a lot more people to perpetrate it. DormRing1 recruited student click fraud workers on Chinese social networks where and forums participants would post images of checks they were getting for their activities. One drummed up interest by talking about his plans to buy a car with the proceeds. Just like with any criminal organization, people at the lower rungs had to do a lot of grunt work to move up the ladder of trust and money. A briefing paper provided by Anchor describes the operation:
These social networks involve a complex set of user access levels. The baseline entrance level is only available by invitation; access to sensitive information is restricted solely to those users who have attained the highest levels. Users with the uppermost levels of access are able to purchase root kits to engage in fraudulent activity and contract out phases of their fraud operations to a large network of willing participants. Users reach higher levels of access in one of two ways: either through a vouching system or by proving themselves as valuable contributors to the network through the provision of some ground level of services (e.g. contracting to create hundreds of accounts on various websites).
DormRing1 was able to use these exclusive social networks to create a division of labor in which all participants at the highest levels shared in a percentage of profits from an operation. The students involved in the ring each set up dozens of bare-bones websites, and successfully registered them with multiple ad networks. The students then hired the services of several botnet controllers to systematically click on ad links that were displayed on these sites. For each ad click, the publisher made a percentage of what the advertiser paid for that click. Through this network, the perpetrators were able to contract money mules (i.e. people with US addresses to which checks can be sent), traffic generators / botnet herders, website template developers, and a host of other service providers. After monetizing these fake websites via fraudulent ad clicks, the perpetrators then wired money to their various contractors.
Remember, we only know these details because DormRing1 was stopped. But nobody was arrested. The advertisers just stopped making payments to the fraudulent Websites. You can be pretty sure that DormRing2 is already up and running.
Beginning tomorrow (September 30), Google will send out 100,000 invites to Google Wave. The product has received a lot of buzz, both for being innovative and not quite ready. Actually, Google admits it’s not ready for prime time, which is one of the reasons why the invites are limited.
If you’re not familiar, Google Wave is a collaborative tool that features real-time features. They’re still working on features, including group definitions, draft mode and permissions.
Those who can expect an invite are developers who participated in an earlier preview, the first people to sign up for invites and select Google Apps customers.
There’s no question about it: Google is great at search, and its huge lead over competitors is well deserved. But the site’s spartan design can sometimes leave something to be desired — sure, the company gradually makes tweaks to it, but we haven’t seen many radical changes in a very long time. Now WebMynd, a Y Combinator startup that launched back in early 2008, is looking to help spur the search giant to make itself a little better, or at least give it a few ideas to help. Tonight, WebMynd is launching a contest appropriately called RedesignGoogle.com that invites designers from around the world to give Google a makeover.
WebMynd has posted all the details details on its blog, but here’s the gist of it: designers are invited to revamp Google using any CSS modifications they’d like. The contest starts accepting submissions today, and will run through November 1. Then, a number of judges (which include Y Combinator’s Paul Graham, the WebMynd team and — full disclosure — myself) will pick the best designs. The winners will take home a brand new MacBook Air.
The nice thing about the contest is that it isn’t purely theoretical — you’ll actually be able to start using the new design in your browser, using a stripped down version of WebMynd’s browser plugin. The Plugin, which launched back in March, gives users the ability to customize their search experience and includes a number of other features, like a comprehensive browsing history (advanced features won’t be enabled by default on the streamlined contest plugin, but users will be able to turn them on).
Here is an early submission to the contest. You can see a full gallery here.
Google has acquired reCAPTCHA, an open source technology that provides CAPTCHAs to prevent spam and fraud. Captchas are those security questions you find on Web sites that require you to decipher and type words or numbers and detects whether the user is a human.
Here’s what Google wrote in a blog post about the announcement:
CAPTCHAs are designed to allow humans in but prevent malicious programs from scalping tickets or obtain millions of email accounts for spamming. But there’s a twist — the words in many of the CAPTCHAs provided by reCAPTCHA come from scanned archival newspapers and old books. Computers find it hard to recognize these words because the ink and paper have degraded over time, but by typing them in as a CAPTCHA, crowds teach computers to read the scanned text.
Google says that reCAPTCHA’s technology improves the process that converts scanned images into plain text, known as Optical Character Recognition (OCR). It sounds like Google will be using the technology to power massive scanning projects for Google Books and Google News Archive Search as well as for fraud and spam prevention.
In May, the New York Times reported that Google was developing their own type of captcha and also took notice of the potential of reCAPTCHA’s technology. Sounds like Google found it more effective to acquire reCAPTCHA’s technology instead of reinventing the wheel.
Over at the official Bing blog, Principal Group Program Manager Rajesh Srivastava is offering up some tips on how to conduct search engine optimization (SEO) for their engine.
Much of Srivastava’s advice is your basic SEO tips that you would apply for Google or Yahoo! But for you beginners out there, drill these SEO principles into your head:
Bing has a Webmaster Center, similar to Google’s Webmaster Central. Use it to help Bing index your site and improve your results even further. Here are tips for using Bing’s Webmaster Center:
Here’s a great tip via Google Blogoscoped (even though this tip has to do with Bing). Want to find out if any other domains are associated with your domain’s IP address? Bing allows you to find out.
Use a site that looks up the IP address of a domain such as IP-Address.com. Then plug the IP address into Bing, preceded with “ip:”.
To try it out, I used a local tv site, WRAL.com. Their IP is 216.27.85.170. You can see other sites share the same IP. (The sites are associated with sites that the parent company of WRAL.com owns.)
Google has added a Creative Commons filter to Image Search. In order to use the filter, you’ll need to use the Advanced Search option in Google Image Search.
Once on the Advanced Search page, look for the “Usage Rights” option, which is the second from the bottom. You won’t see “Creative Commons” listed as an option. Instead, you’ll see options for:
Google’s not the first to do this. Of course, Flickr has had Creative Commons search for a long time. Yahoo! added a Creative Commons filter to its Image Search last May.
For its part, Google added Creative Commons filtering options to Custom Search plus YouTube began offering Creative Commons licensing this past February. However, YouTube doesn’t yet offer Creative Commons search in its Advanced Search yet.
Firefox is nearly at 50% market share!
| 2009 | IE7 | IE6 | IE8 | Firefox | Chrome | Safari | Opera |
|---|---|---|---|---|---|---|---|
| June | 18.7% | 14.9% | 7.1% | 47.3% | 6.0% | 3.1% | 2.1% |
| May | 21.3% | 14.5% | 5.2% | 47.7% | 5.5% | 3.0% | 2.2% |
| April | 23.2% | 15.4% | 3.5% | 47.1% | 4.9% | 3.0% | 2.2% |
| March | 24.9% | 17.0% | 1.4% | 46.5% | 4.2% | 3.1% | 2.3% |
| February | 25.4% | 17.4% | 0.8% | 46.4% | 4.0% | 3.0% | 2.2% |
| January | 25.7% | 18.5% | 0.6% | 45.5% | 3.9% | 3.0% | 2.3% |
| 2008 | IE7 | IE6 | IE5 | Firefox | Chrome | Safari | Opera |
| December | 26.1% | 19.6% | 44.4% | 3.6% | 2.7% | 2.4% | |
| November | 26.6% | 20.0% | 44.2% | 3.1% | 2.7% | 2.3% | |
| October | 26.9% | 20.2% | 44.0% | 3.0% | 2.8% | 2.2% | |
| September | 26.3% | 22.3% | 42.6% | 3.1% | 2.7% | 2.0% | |
| August | 26.0% | 24.5% | 43.7% | 2.6% | 2.1% | ||
| July | 26.4% | 25.3% | 42.6% | 2.5% | 1.9% | ||
| June | 27.0% | 26.5% | 0.5% | 41.0% | 2.6% | 1.7% | |
| May | 26.5% | 27.3% | 0.7% | 39.8% | 2.4% | 1.5% | |
| April | 24.9% | 28.9% | 1.0% | 39.1% | 2.2% | 1.4% | |
| March | 23.3% | 29.5% | 1.1% | 37.0% | 2.1% | 1.4% | |
| February | 22.7% | 30.7% | 1.3% | 36.5% | 2.0% | 1.4% | |
| January | 21.2% | 32.0% | 1.5% | 36.4% | 1.9% | 1.4% | |
| 2007 | IE7 | IE6 | IE5 | Firefox | Mozilla | Safari | Opera |
| November | 20.8% | 33.6% | 1.6% | 36.3% | 1.2% | 1.8% | 1.6% |
| September | 20.8% | 34.9% | 1.5% | 35.4% | 1.2% | 1.6% | 1.5% |
| July | 20.1% | 36.9% | 1.5% | 34.5% | 1.4% | 1.5% | 1.9% |
| May | 19.2% | 38.1% | 1.6% | 33.7% | 1.3% | 1.5% | 1.7% |
| March | 18.0% | 38.7% | 2.0% | 31.8% | 1.3% | 1.6% | 1.6% |
| January | 13.3% | 42.3% | 3.0% | 31.0% | 1.5% | 1.7% | 1.5% |
| 2006 | IE7 | IE6 | IE5 | Firefox | Mozilla | N7/8 | Opera |
| November | 7.1% | 49.9% | 3.6% | 29.9% | 2.5% | 0.2% | 1.5% |
| September | 2.5% | 55.6% | 4.0% | 27.3% | 2.3% | 0.4% | 1.6% |
| July | 1.9% | 56.3% | 4.2% | 25.5% | 2.3% | 0.4% | 1.4% |
| May | 1.1% | 57.4% | 4.5% | 25.7% | 2.3% | 0.3% | 1.5% |
| March | 0.6% | 58.8% | 5.3% | 24.5% | 2.4% | 0.5% | 1.5% |
| January | 0.2% | 60.3% | 5.5% | 25.0% | 3.1% | 0.5% | 1.6% |
| 2005 | IE6 | IE5 | Firefox | Mozilla | N7 | O8 | O7 |
| November | 62.7% | 6.2% | 23.6% | 2.8% | 0.4% | 1.3% | 0.2% |
| September | 69.8% | 5.7% | 18.0% | 2.5% | 0.4% | 1.0% | 0.2% |
| July | 67.9% | 5.9% | 19.8% | 2.6% | 0.5% | 0.8% | 0.4% |
| May | 64.8% | 6.8% | 21.0% | 3.1% | 0.7% | 0.7% | 0.6% |
| March | 63.6% | 8.9% | 18.9% | 3.3% | 1.0% | 0.3% | 1.6% |
| January | 64.8% | 9.7% | 16.6% | 3.4% | 1.1% | 1.9% | |
| 2004 | IE6 | IE5 | Mozilla | N3 | N7 | N4 | O7 |
| November | 66.0% | 10.2% | 16.5% | 0.2% | 1.2% | 0.3% | 1.6% |
| September | 67.8% | 11.2% | 13.7% | 0.3% | 1.4% | 0.3% | 1.7% |
| July | 67.2% | 13.2% | 12.6% | 0.4% | 1.4% | 0.4% | 1.6% |
| May | 68.1% | 13.8% | 9.5% | 0.6% | 1.4% | 0.4% | 1.6% |
| March | 68.2% | 14.6% | 7.9% | 0.8% | 1.4% | 0.6% | 1.4% |
| January | 68.9% | 15.8% | 5.5% | 0.4% | 1.5% | 0.5% | 1.5% |
| 2003 | IE6 | IE5 | Mozilla | N3 | N7 | N4 | O7 |
| November | 71.2% | 13.7% | 7.2% | 0.5% | 1.6% | 0.5% | 1.9% |
| September | 69.7% | 16.9% | 6.2% | 0.6% | 1.5% | 0.6% | 1.8% |
| July | 66.9% | 20.3% | 5.7% | 0.6% | 1.5% | 0.6% | 1.7% |
| May | 65.0% | 22.7% | 4.6% | 1.0% | 1.4% | 0.9% | 1.4% |
| March | 63.4% | 24.6% | 4.2% | 0.9% | 1.4% | 1.1% | 1.2% |
| January | 55.3% | 29.3% | 4.0% | 1.2% | 1.1% | 1.7% | |
| 2002 | IE6 | IE5 | AOL | N3 | N5 | N4 | IE4 |
| November | 53.5% | 29.9% | 5.2% | 1.1% | 4.9% | 2.0% | |
| September | 49.1% | 34.4% | 4.5% | 1.3% | 4.5% | 2.2% | |
| July | 44.4% | 40.1% | 3.5% | 1.2% | 3.5% | 2.6% | 0.5% |
| May | 40.7% | 46.0% | 2.8% | 1.2% | 2.7% | 3.4% | 0.7% |
| March | 36.7% | 49.4% | 3.0% | 1.2% | 2.4% | 4.1% | 0.7% |
| January | 30.1% | 55.7% | 2.8% | 1.3% | 2.2% | 4.4% | 1.0% |
Thank you w3schools for the stats
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