DarkCyber for June 5, 2018: Amazon and Its LE and Intelligence Services

June 5, 2018

The DarkCyber for June 5, 2018, is now available at www.arnoldit.com/wordpress or on Vimeo at https://vimeo.com/273170550.

This week’s DarkCyber presents an extract from Stephen E Arnold’s lectures at the Prague Telestrategies ISS conference. The conference is designed for security, intelligence, and law enforcement professionals in Europe.

Stephen’s two lectures provided attendees with a snapshot of the services Amazon’s streaming data marketplace offer to customers, developers, and entrepreneurs.

Stephen said:

The Amazon platform is positioned to provide a robust, innovative way to anonymize digital currency transactions and perform the type of analyses needed to deal with bad actors and the activities.

The information was gleaned from Amazon conference lectures, Amazon’s Web logs and documentation, and open source documents.

For example, one public document stated:

“… A law enforcement agency may be a customer and may desire to receive global Bitcoin transactions, correlated by country, with USP data to determine source IP addresses and shipping addresses that correlate to Bitcoin addresses.”

Coupled with Amazon’s facial recognition service “Rekognition” and Amazon’s wide array of technical capabilities, Amazon is able to provide specialized content processing and data services.

Stephen stated:

Instead of learning how to use many different specialized systems, the Amazon approach offers a unified capability available with a Kindle-style interface. This is a potential game changer for LE, intel, and security service providers.

In this week’s DarkCyber video, Stephen provides an eight minute summary of his research, including the mechanisms by which new functions can be added to or integrated with the system.

A for fee lecture about what Stephen calls “Amazon’s intelligence services” is available on a for fee basis. For information, write darkcyber333 at yandex dot com.

Kenny Toth, June 5, 2018

DarkCyber, May 29, 2018, Now Available

May 29, 2018

Stephen E Arnold’s DarkCyber video news program for Tuesday, May 29, 2018, is now available.

This week’s story line up is:

  • The “personality” of a good Web hacker
  • Why lists are replacing free Dark Web search services
  • Where to find a directory of OSINT software
  • A new Dark Web index from a commercial vendor.

You can find this week’s program at either www.arnoldit.com/wordpress or on Vimeo at https://vimeo.com/272088088.

On June 5, 2018, Stephen will be giving two lectures at the Telestrategies ISS conference in Prague. The audiences will consist of intelligence, law enforcement, and security professionals from Europe. A handful of attendees from other countries will be among the attendees.

On Tuesday, June 5, 2018, Stephen will reveal one finding from our analysis of Amazon’s law enforcement, war fighting, and intelligence services initiative.

Because his books have been reused (in several cases without permission) by other analysts, the information about Amazon is available via online or in person presentations.

The DarkCyber team has prepared short video highlighting one research finding. He will include some of the DarkCyber research information in his Prague lectures.

The Amazon-centric video will be available on Tuesday, June 5, 2018. After viewing the video, if you want the details of his for fee lecture, write him at darkcyber333@yandex dot com. Please, put “Amazon” in the subject line.

Several on the DarkCyber team believe that most people will dismiss Stephen’s analysis of Amazon. The reason is that people buy T shirts, books, and videos from the company. However, the DarkCyber research team has identified facts which suggest a major new revenue play from the one time bookseller.

Just as Stephen’s analyses of Google in 2006 altered how some Wall Street professionals viewed Google, his work on Amazon is equally significant. Remember those rumors about Alexa recording what it “hears”? Now think of Amazon’s services/products as pieces in a mosaic.

The picture is fascinating and it has significant financial implications as well.

Enjoy today’s program at this link.

Kenny Toth, May 29, 2018

One View of the Amazon Game Plan

May 27, 2018

I read “Invisible Asymptotes.” Job One for me was trying to match the meaning of “asymptote” with the research my DarkCyber team has conducted into one slice of Amazon’s business roll outs in the last three years.

As you know, an “asymptote” is a mathy way of saying “you can’t get from here to there.” According to Wolfram Mathword:

An asymptote is a line or curve that approaches a given curve arbitrarily closely.

Here’s a diagram. No equations, I promise.

Image result for asymptote

This diagram suggests a business angle to the “asymptote” reference: No matter what you do, it requires effort and a commitment to “quality”. The good news is that although one can quantify time, one cannot quantify “quality” or “perfection.” Okay, gerbil, run in that Ferris wheel gizmo in your cage.

The write up points out:

We focus so much on product-market fit, but once companies have achieved some semblance of it, most should spend much more time on the problem of product-market unfit.

I am not exactly sure what “unfit” means. The author provides a hint:

For me, in strategic planning, the question in building my forecast was to flush out what I call the invisible asymptote: a ceiling that our growth curve would bump its head against if we continued down our current path.

Okay, the idea seems to be that if Amazon enters a new market, the “invisible asymptote” is what slows growth or stops it completely. (Is this the Amazon phone’s and the slowing sales of Alexa in the face of competition from the Google Home device?)

The reason Amazon cannot grow ever larger is because of an “invisible asymptote”; that is, a factor which prevents Amazon from becoming a company that Vanderbilt, JP Morgan, and John D. Rockefeller would have wished they had.

The write up does not discuss Amazon’s semi-new entrance into the law enforcement and intelligence market. That’s a push I am exploring in my lecture at the Telestrategies ISS conference in early June.

The focus shifts to a more mundane and increasingly problematic aspect of Amazon’s business: Shipping fees. Fiat, law, and the costs of fuel are just a few of the challenges Amazon faces. I am not sure these are “invisible”, but let’s trudge forward.

Twitter becomes that foundation for social media. I noted this passage:

No company owes it to others to allow people to build direct competitors to their own product.

If Amazon wants to make law enforcement and intelligence services into a major revenue stream, I think the first evidence of this intent will be cutting off the vendors using Amazon’s infrastructure to serve their clients now. (Keep in mind that most of the specialist vendors in the LE and intel space use Amazon as plumbing. To cite one example, Marinus, the anti human trafficking group, follows this approach.

The author brings up Snapchat and other social media companies. I find this example important. Amazon’s facial recognition capabilities hit out radar when my team was assembling “CyberOSINT: Next Generation Information Access”, written in 2014 and published in 2015.

We did not include Amazon in my review of LE and intel tools because I had only references in some Amazon conference videos, a few patent applications which were particularly vague about applications in the Background and Claims sections of the documents, and chatter at meetings I attended.

The American Civil Liberties Union has made a bit of noise about Amazon’s facial recognition system. Recognition is spelled “rekognition”, presumably to make it easy to locate in the wonky world of Bing and Google search. The reason is that Amazon’s facial recognition system can identify individuals and cross tabulate that piece of information with other data available to the Amazon system.

Instant bubblegum card.

The write up “Invisible Asymptote” talks about social content and social rich media without offering any comment about the importance of these types of data to Amazon’s intelligence services or its marketplace.

The conclusion of the 10,000 word essay is more “invisible asymptote”. Is this Amazon’s the secret sauce:

Lastly, though I hesitate to share this, it is possible to avoid invisible asymptotes through sheer genius of product intuition.

Here’s a diagram from the essay which looks quite a bit like the self help diagram I included at the top of this Beyond Search post:

stratechery-disruption-diagram-1.png

Several observations:

  1. The write up makes clear that if anyone thinks Amazon’s platform is neutral, think again.
  2. Strategists at Amazon are not able to “see” and “explain” the nuts and bolts of the “we may be a monopoly but” approach of the Big Dog of the Amazon
  3. The long, long essay does not stray very far from selling stuff to consumers who love free shipping.

Taken as a group of three perceptions, what does this say about Amazon?

For me, I think companies using Amazon’s plumbing will want to do a bit of strategizing using “What if” questions to spark discussion.

For companies behind or beneath the curve, there will be a ceiling, and it will not be easy to break through.

Amazon, on the other hand, may have break through and then replace the old ceiling with a nifty new one made of sterner stuff.

For information about our lectures about Amazon’s Next Big Thing: Intelligence Services, write me at benkent2020@yahoo.com. Put Amazon Streaming Marketplace in the subject line, please.

We now offer for fee webinars and on site consulting sessions. On June 5, 2015, coincident with my two lectures in Prague before an audience of LE and intel professionals, I will release a nine minute DarkCyber video exploring some of the inventions Amazon disclosed in an April document not widely reported in the media. Watch this blog for a link.

Stephen E Arnold, May 27, 2018

You Know You Are in Deep Doo Doo When…

May 7, 2018

I flipped through the Overflight news feeds and noted several stories. Remember when you were a wee thing, and you did something wrong. Your friends knew. Your friends’ mom knew. Your mom knew. Then your father or significant parental other (SPO) knew. That may be the feeling of some of the Cambridge Analytica wunderkind.

An example is warranted:

That excellent hire Christopher Wylie has allegedly shared more information about turning clicks into votes. The good hearted wizard told the Guardian about data, target variables, and profiling. There’s even a reference to a patent (absent the patent number, the assignee, and other data which allows one to locate the referenced patent). The kimono is open and the sight does not strike me as one I would describe as attractive.

Will declaring bankruptcy allow the Cambridge Analytica “owner” to avoid further scrutiny? That seems unlikely.

Will an expert step forward and suggest that Cambridge Analytica may have precipitated the Brexit anguish? That seems unlikely.

Nevertheless, I would hypothesize that moms.

PS. Include patent identifiers when you quote patents, dear Guardian editors, please. Perhaps you too are engaging in some data shaping just on a tiny scale?

Stephen E Arnold, May 7,l 2018

Metadata Collection Spike: Is There a Reason?

May 6, 2018

I read “NSA Triples Metadata Collection Numbers Sucking Up over 500 Million Call Records in 2017.” Interesting report, but it raised several questions here in Harrod’s Creek. But first, let’s look at the “angle” of the story.

I noted this statement:

The National Security Agency revealed a huge increase in the amount of call metadata collected, from about 151 million call records in 2016 to more than 530 million last year — despite having fewer targets.

The write up pointed out that penetration testing and trace and tap orders declined. That’s interesting as well.

The write up focused on what’s called “call detail records.” These, the write up explained, are:

things like which numbers were called and when, the duration of the call, and so on…

The write up then reminds the reader that “one target can yield hundreds or thousands of sub-targets.”

The article ends without any information about why. My impression of the write up is that the government agency is doing something that’s not quite square.

My initial reaction to the data in the write up was, “That does not seem like such a big number.” A crawl of the Dark Web, which is a pretty tiny digital space, often generates quite a bit of metadata. Stuffing the tiny bit of Dark Web data into a robust system operated by companies from Australia to the United States can produce terabytes of data. In fact, one Israeli company uploads new data in zipped block to its customers multiple times a day. The firm of which I am thinking performs this work for outfits engaged in marketing consumer products. In comparison, the NSA effort strikes me as modest.

My first question, “Why so little data?” Message, call, image, and video data are going up. The corresponding volume of metadata is going up. Toss in link analysis pointers, and that’s a lot of data. In short, the increase reported seems modest.

The second question is, “What factors contributed to the increase?” Based on our research, we think that some of the analytic systems are bogged down due to the wider use of message encryption technology. I will be describing one of these systems in my June 2018 Telestrategies ISS lecture related to encrypted chat. I wonder if the change in the volume reported in the write up is related to encryption.

My third question is, “Is government analysis of message content new or different?” Based on the information I have stumbled upon here in rural Kentucky, my thought is that message traffic analysis has been chugging along for decades. I heard an anecdote when I worked at a blue chip consulting firm. It went something like this:

In the days of telegrams, the telegraph companies put paper records in a bag, took them to the train station in Manhattan, and sent them to Washington, DC.

Is the anecdote true or false? My hunch is that it is mostly true.

My final question triggered by this article is, “Why does the government collect date?” I suppose the reasons are nosiness, but my perception is that the data are analyzed in order to get a sense of who is doing what which might harm the US financial system or the country itself.

My point is that numbers without context are often not helpful. In this case, the 2010 Pew Data reported that the average adult with a mobile makes five calls per day. Text message volume is higher. With 300 million people in the US in 2010 and assuming 30 percent mobile phone penetration, the number of calls eight years ago works out to about 1.5 billion calls. Flash forward to the present. The “number” cited in the article seems low.

Perhaps the author of the article could provide more context, do a bit of digging to figure out why the number is what it is, and explain why these data are needed in the first place.

One can criticize the US government. But I want to know a bit more.

Net net: It seems that the NSA is showing quite a bit of focus or restraint in its collection activities. In the May 16, DarkCyber, I report the names of some of the companies manufacturing cell site simulators. These gizmos are an interesting approach to data collection. Some of the devices seem robust. To me, capturing 500 million calls seems well within the specifications of these devices.

But what do I know? I can see the vapor from a mine drainage ditch from my back window. Ah, Kentucky.

Stephen E Arnold, May 6, 2018

Cambridge Analytica: Those Greek Tragedians Understood Bad Decisions

May 2, 2018

Here in Harrod’s Creek, the echoes of the khoros are sometimes audible. For example, we heard that Cambridge Analytica, the zippy data outfit has folded its tents. The firm’s offices in the US and elsewhere are shuttered or in the process of turning out the lights and unplugging from the interwebs.

We noted this statement in Gizmodo:

The news was announced during a conference call led by Julian Wheatland, the current chairman of the SCL Group who was reportedly tapped to take over as Cambridge Analytica’s next CEO. Both companies will now close their doors. During the call, Wheatland said that the board determined that rebranding the company’s current offerings in the current environment is “futile.”

In the online information the Beyond Search team has been reviewing, there was no reference to this statement, allegedly crafted by Sophocles:

I would prefer even to fail with honor than win by cheating.

CNBC reported:

The firm is shuttering in part due to mounting legal fees associated with its investigation into whether there had been any wrongdoing with regard to Facebook data, according to the Wall Street Journal who first reported the shuttering.

That “real” news report did not include this statement, allegedly penned by Euripides:

Cleverness is not wisdom.

Will other clever individuals bump into Greek truisms?

The odds in Harrod’s Creek that trouble will be coming to some social media outfits are the same as those on Justified, the favorite in the Kentucky Derby.

Race tracks do need workers to clean their Augean stables. The work is less sporty than crunching data of mysterious origins, but it pays because horses are often more reliable than some humans. Plus there is a party for workers after the race on Saturday.

Stephen E Arnold, May 2, 2018

Geotargeting: Getting Popular

May 1, 2018

Businesses, governments, and organizations are asking, “How can AI be used?” The better question to ask is, “What can AI not do?” Along with spying on the Chinese’s good behavior and people’s personal information on social media, the Smart Data Collective posted that “Malicious AI? Report Shines Dark Light On Geotargeting.”

What is geotargeting? Geotargeting is using locations specific data to keep a close eye on selected targets. Social media data plays a part too. It is astonishing and creepy how much AI can pull from information placed on the Internet. Ever since Russia intervened in the 2016 election, policymakers are cracking down on data-based marketing. What is even worse is that hackers are already using AI against the innocent.

New policies are being put into place and Mark Zuckerberg is even being held (hopefully) accountable for how Facebook has taken advantage of data.

“People are growing more and more suspicious of AI. The new malicious AI report, which was written by 26 experts from academia, industry, and 12 other fields, identifies AI as a potential culprit in the threat to “political security.” The report says that AI “can automate tasks involved in surveillance” by analyzing “mass-collected data,” which it can use to create propaganda and deceptive content, such as misleading videos and fake news. The more trolls and hackers use AI to threaten the political security of democracies, the more likely democracies and companies are to regulate the use of big data.”

One scary AI trick is geotargeting, where companies can push advertising directly to customers’ and law enforcement can track people of interested all based on a persons’ cell phone data. Bad actors can use geotargeting for personal drone attacks. Scary! There are not any amendments currently protecting AI, so the legal ramifications are still up in the air.

Remember, however, that AI is a neutral tool. Humans are creatures of habit. Plotting geo-behaviors can be a useful, insightful exercise.

Whitney Grace, May 1, 2018

Access Free and Lower Cost DNA Data Analytics

April 28, 2018

Short honk: Do you want to do some DNA matching? There is a free source of some DNA data. Navigate to https://www.gedmatch.com. You will need to register and provide your own DNA sample. Once you are registered there are some free data available plus for-fee services. For a good run down of some DNA analytic options, Ahmed El-Kalliny provides a useful run down plus links at this Quora location. Many of the listings are 23 and Me centric, but some of the services can provide helpful for-fee analytics. If you want to spoof, GEDmatch, you will need to find an individual will to provide the bio sample. Verification strikes Beyond Search as somewhat relaxed.

Stephen E Arnold, April 27, 2018

Picking and Poking Palantir Technologies: A New Blood Sport?

April 25, 2018

My reaction to “Palantir Has Figured Out How to Make Money by Using Algorithms to Ascribe Guilt to People, Now They’re Looking for New Customers” is a a sign and a groan.

I don’t work for Palantir Technologies, although I have been a consultant to one of its major competitors. I do lecture about next generation information systems at law enforcement and intelligence centric conferences in the US and elsewhere. I also wrote a book called “CyberOSINT: Next Generation Information Access.” That study has spawned a number of “experts” who are recycling some of my views and research. A couple of government agencies have shortened by word “cyberosint” into the “cyint.” In a manner of speaking, I have an information base which can be used to put the actions of companies which offer services similar to those available from Palantir in perspective.

The article in Boing Boing falls into the category of “yikes” analysis. Suddenly, it seems, the idea that cook book mathematical procedures can be used to make sense of a wide range of data. Let me assure you that this is not a new development, and Palantir is definitely not the first of the companies developing applications for law enforcement and intelligence professionals to land customers in financial and law firms.

baseball card part 5

A Palantir bubble gum card shows details about a person of interest and links to underlying data from which the key facts have been selected. Note that this is from an older version of Palantir Gotham. Source: Google Images, 2015

Decades ago, a friend of mine (Ev Brenner, now deceased) was one of the pioneers using technology and cook book math to make sense of oil and gas exploration data. How long ago? Think 50 years.

The focus of “Palantir Has Figured Out…” is that:

Palantir seems to be the kind of company that is always willing to sell magic beans to anyone who puts out an RFP for them. They have promised that with enough surveillance and enough secret, unaccountable parsing of surveillance data, they can find “bad guys” and stop them before they even commit a bad action.

Okay, that sounds good in the context of the article, but Palantir is just one vendor responding to the need for next generation information access tools from many commercial sectors.

Read more

French Report: Demographics of Bad Actors

April 20, 2018

If this report is to be believed, a demographic segment may come under increased scrutiny, online and offline. The Local lays out the results of a recent study from the director of publications at the French Institute of International Relations, Marc Hecker, in the write-up, “Aged 26, Poor, and Already a Criminal: Who Is the Typical French Jihadist?” The sample size was not large—137 people who had been convicted of Islamist- or jihad-related terror offences in France, most of whom were French nationals. The write-up shares a number of specific findings, including this bit of interest to IT folks: Though jihadists do use the internet extensively for networking and coordination, most become radicalized through extensive in-person contact; they have not been enticed simply by material found online. The article also reports:

“Out of the 137 cases, 131 were men and six were women. The average age of those at the time they were charged was 26, with 90 percent of them coming from large broken families and 40 percent coming from poor backgrounds. Of the 137 jihadists looked at by the study, some 74 percent were born Muslim while the remaining 26 percent converted during their lifetime. Although in general the study found there was a low level of religious knowledge among the individuals. Some 47 percent of the 68 French jihadists whose education records were available left school with no qualifications while 26 percent passed their baccalaureate and 11 percent graduated from university. Some 36 percent were unemployed at the time of arrest while another 22 percent were in low-paid unstable jobs (emploi précaire). More than half of those charged with Islamist terror offences were in a couple (57 percent). IFRI says the study shows “that these individuals are distinguished by a lower level of education and professional integration, a higher degree of poverty, a greater involvement in crime and a closer relationship to North and sub-Saharan Africa than the average population of France.”

One more key statistic—about 40 percent of respondents had already been convicted of at least one crime, while another 8 had been reported to police with no conviction. So, those already inclined toward criminality may be more likely to see violence as a viable tool for change; imagine that. The study also found that the process of radicalization takes months or, in 30 percent of cases, several years. A preview of Hecker’s study can be found here.

Cynthia Murrell, April 20, 2018

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