The Intersection of the Criminal, Law Enforcement and Technology Industries
February 26, 2016
A ZDNet article covers Arrests made over Bitcoin laundering scheme, Dark Web drug deals
Dutch police made several arrests related to laundering of criminal profits orchestrated through an unindexed section of the web called the Dark Web. The article says suspects allegedly laundered up to 20 million euros from online drug deals. With the information originating from Reuters, this article summarizes the arrests made by Dutch Fiscal Information and Investigation Service and public prosecution department:
“According to the publication, some of the men arrested are traders, while others are “Bitcoin cashers” — traders of Bitcoin online who cash these funds then withdraw money from ATMs. It is possible to find cashers online who run shadow services which exchange “dirty” coins for clean currency. Law enforcement in the United States, Australia, Lithuania and Morocco also participated in the raid.”
Just as criminal offenses are taking place increasingly online, so too must the law enforcement industry have turn to technology to aid its efforts. As the case unfolds, it will be interesting to uncover how these suspects were identified. Perhaps something innovative will be at the source.
Megan Feil, February 26, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Startup Semantic Machines Scores Funding
February 26, 2016
A semantic startup looks poised for success with experienced executives and a hefty investment, we learn from “Artificial Intelligence Startup Semantic Machines Raises $12.3 Million” at VentureBeat. Backed by investors from Bain Capital Ventures and General Catalyst Partners, the enterprise focuses on deep learning and improved speech recognition. The write-up reveals:
“Last year, Semantic Machines named Larry Gillick as its chief technology officer. Gillick was previously chief speech scientist for Siri at Apple. Now Semantic Machines is looking to go further than Siri and other personal digital assistants currently on the market. ‘Semantic Machines is developing technology that goes beyond understanding commands, to understanding conversations,’ the startup says on its website. ‘Our Conversational AI represents a powerful new paradigm, enabling computers to communicate, collaborate, understand our goals, and accomplish tasks.’ The startup is building tools that third-party developers will be able to use.”
Launched in 2014, Semantic Machines is based in Newton, Massachusetts, with offices in Berkeley and Boston. The startup is also seeking to hire a few researchers and engineers, in case anyone is interested.
Cynthia Murrell, February 26, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Google and Page Loading Speed
February 25, 2016
I read “Google Has Slowest Loading Home Page on Mobile Compared to Competitors.” I access the Internet from my desktop boat anchor computers. No cigarette racer for me.
The write up makes a startling claim about the speed and efficiency crazed Alphabet Google thing; to wit:
Google actually has the slowest loading home page on mobile devices compares to its major competitors.
The write up contains actual data to prove this bold assertion for the Googzilla. The top speed is 100, and Yahoo delivers a blistering 95.
Now in my own albeit uninformed experience, Yahoo loads slowly or not at all. Yahoo Mail is particularly snailish and unpredictable. The fix is to access dear old Yahoo via a Google search. I click on the Mail link in the Google results, and this often makes the recalcitrant purple people eater “work.”
Now the “test” was performed on mobile devices. I am not sure what devices, how many tests were run, and what mobile services were used to access the tested systems.
The write up seems a bit fluffy, but, heck, I read it. That’s the point. The information may be secondary to the click and the ads. One must not forget the ads.
Stephen E Arnold, February 25, 2016
DuckDuckGo: Challenging Google Is Not a Bad Idea
February 25, 2016
I read “The Founder of DuckDuckGo Explains Why Challenging Google Isn’t Insane.” I noted several statements in the write up; namely:
- DuckDuckGo delivers three billion searches a year, compared to Google’s trillion-plus search per year. The zeros can be confusing to an addled goose like me. Let me say that Google is delivering more search results that DuckDuckGo.com
- DuckDuckGo’s revenues are in 2015 were more than $1 million. Google’s revenues were about $75 billion. Yep, more zeros.
- It used to take Google six months to index pages on the Internet. (I thought that Google indexed from its early days based on a priority algorithm. Some sites were indexed in a snappy manner; others, like the National Railway Retirement Board, less snappily. I am probably dead wrong here, but it is a nifty point to underscore Google’s slow indexing. I just don’t think it was or is true.)
- DuckDuckGo was launched in 2008. The company is almost eight years old.
- Google’s incognito mode is a myth. What about those Google cookies? (I think the incognito mode nukes those long lived goodies.)
Here’s the passage I highlighted:
Adams (the interviewer): I thought the government could track me whether I use DuckDuckGo or not.
Weinberg (the founder of DuckDuckGo): No they can’t. They can get to your Google searches, but if you use DuckDuckGo it’s completely encrypted between you and us. We don’t store anything. So there’s no data to get. The government can’t subpoena us for records because we don’t have records.
DuckDuckGo beats the privacy drum. That’s okay, but the privacy of Tor and I2P can be called into question. Is it possible that there are systems and methods to track user queries with or without the assistance of the search engine system? My hunch is that there are some interesting avenues to explore from companies providing tools to various government agencies. What about RACs, malware, metadata analyses, etc.? Probably I am wrong again. RATs. I have no immunity from my flawed information. I may have to grab my swim fins and go fin-fishing. I could also join a hacking team and vupen it up.
Stephen E Arnold, February 25, 2016
Data Insight: Common Sense Makes Sense
February 25, 2016
I am skeptical about lists of problems which hot buzzwords leave in their wake. I read “Why Data Insight Remains Elusive,” which I though was another content marketing pitch to buy, buy, buy. Not so. The write up contains some clearly expressed, common sense reminds for those who want to crunch big data and point and click their way through canned reports. Those who actually took the second semester of Statistics 101 know that ignoring the data quality and the nitty gritty of the textbook procedures can lead to bone head outputs.
The write up identifies some points to keep in mind, regardless of which analytics vendor system a person is using to make more informed or “augmented” decisions.
Here’s the pick of the litter:
- Manage the data. Yep, time consuming, annoying, and essential. Skip this step at your decision making peril.
- Manage the indexing. The buzzword is metadata, but assigning keywords and other indexing items makes the difference when trying to figure out who, what, why, when, and where. Time? Yep, metadata which not even the Alphabet Google thing does particularly well.
- Create data models. Do the textbook stuff. Get the model wrong, and what happens? Failure on a scale equivalent to fumbling the data management processes.
- Visualization is not analytics. Visualization makes outputs of numerical recipes appear in graphical form. Do not confuse Hollywood outputs with relevance, accuracy, or math on point to the problem one is trying to resolve.
- Knee jerking one’s way through analytics. Sorry, reflexes are okay but useless without context. Yep, have a problem, get the data, get the model, test, and examine the outputs.
Common sense. Most basic stuff was in the textbooks for one’s college courses. Too bad more folks did not internalize those floorboards and now seek contractors to do a retrofit. Quite an insight when the bill arrives.
Stephen E Arnold, February 25, 2016
More Hacked US Voter Data Appears on the Dark Web
February 25, 2016
From HackRead comes a piece called More US Voters Data Circulating on the Dark Net, which points to the lack of protection surrounding data on US voters. This data was leaked on the site The Hell on Dark Web. No reports yet suggest how this data was hacked. While no social security numbers or highly sensitive information was released, records include name, date of birth, voter registration dates, voting records, political affiliation and address. Continuing the explanation of implications, the article’s author writes,
“However, it provides any professional hacker substantial information to initiate and plan a phishing attack in the next election which takes place in the US. Recent discoveries, news and speculations have exposed the role of nation-state actors and cyber criminals in planning, instigating and initiating hacking attacks aimed at maligning the upcoming US elections. While social media has emerged as one of the leading platforms adopted by politicians when they wish to spread a certain message or image, cyber criminals and non-state actors are also utilizing the online platform to plan and initiate their hacking attacks on the US election.”
As the article reminds us, this is the not first instance of voter records leaking. Such leaks call into question how this keeps happening and makes us wonder about any preventative measures. The last thing needed surrounding public perception of voting is that it puts one at risk for cyber attacks. Aren’t there already enough barriers in place to keep individuals from voting?
Megan Feil, February 25, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
monograph
Brown Dog Fetches Buried Data
February 25, 2016
Outdated file formats, particularly those with no metadata, are especially difficult to search and utilize. The National Science Foundation (NSF) reports on a new search engine designed to plumb the unstructured Web in, “Brown Dog: A Search Engine for the Other 99 Percent (ofData).” With the help of a $10 million award from the NSF, a team at the University of Illinois-based National Center for Supercomputing Application (NCSA) has developed two complementary services. Writer Aaron Dubrow explains:
“The first service, the Data Access Proxy (DAP), transforms unreadable files into readable ones by linking together a series of computing and translational operations behind the scenes. Similar to an Internet gateway, the configuration of the Data Access Proxy would be entered into a user’s machine settings and then forgotten. From then on, data requests over HTTP would first be examined by the proxy to determine if the native file format is readable on the client device. If not, the DAP would be called in the background to convert the file into the best possible format….
“The second tool, the Data Tilling Service (DTS), lets individuals search collections of data, possibly using an existing file to discover other similar files in the data. Once the machine and browser settings are configured, a search field will be appended to the browser where example files can be dropped in by the user. Doing so triggers the DTS to search the contents of all the files on a given site that are similar to the one provided by the use…. If the DTS encounters a file format it is unable to parse, it will use the Data Access Proxy to make the file accessible.”
See the article for more on these services, which NCSA’s Kenton McHenry likens to a DNS for data. Brown Dog conforms to NSF’s Data Infrastructure Building Blocks program, which supports development work that advances the field of data science.
Cynthia Murrell, February 25, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Legal Eagles and Technology: The Uber Search Dictum
February 24, 2016
I love legal eagles. When there is a new gadget, the legal eagles are among the first to squawk, “Class action suit” when there is a glitch. Legal eagles are also producing entertaining television commercials to complement the Adwords for various high dollar health related problems. Great stuff.
I know that some fledgling legal eagles are not happy with their law schools. Some of these folks whose parents are not partners in a big money law firm or related to certain public office holders are driving Uber cars.
I read “Judge Tells Uber to Do the Impossible: Control Its Google Results.” The article is very entertaining. The main point is that a federal judge ordered Uber to ensure that certain information appeared in a free Web search results list.
But wait. The write up contained a quote which is a keeper:
To slightly tweak a metaphor offered by this Court during the hearing, a preliminary injunction should not serve as a bazooka in the hands of a squirrel, used to extract from a more fear-some animal a bounty which the squirrel would never be able to gather by his own labors — at least not when the larger animal is mostly without sin.
A squirrel with a bazooka. I would have substituted a drone operator in a tree with a laptop and a Predator under control.
Squirrel in Kentucky watching for legal eagles.
There you go, Google. Help out Uber. Adjust the results list to display exactly what the judge orders; for example:
A result containing [Uber’s] 352-area-code number
Words clearly indicating that the result is associated with [Uber].
What happens if Uber cannot figure out how to conform to the “command” using Adwords, white hat SEO, black hat SEO, or something more innovative?
What happens if Google helps out Uber?
I love this stuff. Come to think of it. Squirrels may be more technically savvy than some legal eagles. I think I hear from the tree, “Gray squirrel, gray squirrel, call in a strike on my command.”
“On your command,” replies the gray squirrel.
Stephen E Arnold, February 24, 2016
The Facebook Google Hundred Years War
February 24, 2016
Okay, the 100 years is in Internet time. But the idea is one that is not a surprise to me and the goslings here in Harrod’s Creek. We are far from the field of battle. What sparked my thoughts about the squabbles among the Plantagenets and the good folks over at the House of Valois. What happened to chivalry?
I read “Facebook and Google at War: Is It Time to Pick Sides” and my addled goose brain thought of the 14th and 15th century dust up. Chivalry and deception went hand in hand with the routine stuff of fights over sovereignty.
In the world of search, the Alphabet Google thing faces a couple of challenges. The 15 year old GoTo.com/Overture/Yahoo revenue model is still chugging along. The users’ behavior is changing, and that put a bit of pressure on the Googlers to diversify their revenue streams. Yikes. What business model can the science and math club use as inspiration? Wild and crazy X Labs’ activities? The social thrust has not exactly worked out. Google no longer requires mandatory Google social log ins for games. Games are big, right?
In the world of social, Facebook is the go to way to keep track of pals. Unlike Twitter, which is a coterie service, Facebook is big, popular with some folks, and has revenue streams from its services. Facebook addiction, anyone? Facebook is also holding its own against upstarts, and the company is semi-famous for its hefty flow of useful information about people, individuals, heck, anyone who signs up and remains logged in. Good stuff.
The write up points out:
Businesses can create a ‘Canvas’ by bringing together their own videos and images, which they combine with interactive buttons to create a truly engaging social experience. The functionality is top notch: “In Canvas, people can swipe through a carousel of images, tilt to view panoramic images and zoom in to view images in detail.” Businesses can easily build their Canvas using a combination of videos, still images and call-to-action buttons.
I would mention that Facebook wants folks with content to use Facebook as a publishing platform. There you go. More useful content to analyze via assorted graph analytics methods.
What’s Google doing? The write up does not focus too much on the Alphabet Google thing.
Now back to that 100 year war. Were not the winners the innovators who created the weapons and, of course, the plague?
Stephen E Arnold, February 24, 2016
Analytics Reality: Do You Excel?
February 24, 2016
I read “What Is the Most used Feature in Any business Intelligence Solution? It’s the Export to Excel Button.” The write up asserts:
I was recently forwarded an article on the continued popularity of Excel in the BI community consisting of quotes from 27 experts saying how great and how relevant Excel remains. We do categorize BI as static and historical as opposed to forward looking predictive analytics but I bet it’s still true that Excel is a very widely used tool even by folks that categorize themselves as data scientists.
Let’s assume this is accurate. What does this suggest for complex analytics like my old pals SAS or IBM SPSS? What about high flying outfits like Palantir, and Centrifuge Systems?
I have some answers, but I think the questions are suggestive of a hurdle which high horsepower analytic systems must power around. There is a reason so few folks are adept at statistics whether the industrial strength variety or the weird approach taken in social science and economics classes.
Excel seems to be tough to master but compared to more supercharged methods, Excel sure looks like a push peddle tricycle. You can’t go too far or too fast. If you crash into something, there is F1 and semi automated procedures to kiss the boo boo and make it better.
Stephen E Arnold, February 24, 2016
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