In Connected World, Users Are Getting Reared as Slaughter Animals
November 22, 2016
Yahoo, Facebook, Google, WhatsApp, Instagram and Microsoft all have one thing in common; for any service that they provide for free, they are harnessing your private data to be sold to advertisers.
Mirror UK recently published an Op-Ed titled Who Is Spying on You? What Yahoo Hack Taught Us About Facebook, Google, and WhatsApp in which the author says:
Think about this for a second. All those emails you’ve written and received with discussions about politics and people that were assumed to be private and meant as inside jokes for you and your friends were being filtered through CIA headquarters. Kind of makes you wonder what you’ve written in the past few years, doesn’t it?
The services be it free email or free instant messaging have been designed and developed in such a way that the companies that own them end up with a humongous amount of information about its users. This data is sugarcoated and called as Big Data. It is then sold to advertisers and marketers who in the garb of providing immersive and customized user experience follow every click of yours online. This is akin to rearing animals for slaughtering them later.
The data is not just for sale to the corporates; law enforcement agencies can snoop on you without any warrants. As pointed out in the article:
While hypocritical in many ways, these tech giants are smart enough to know who butters their bread and that the perception of trust outweighs the reality of it. But isn’t it the government who ultimately ends up with the data if a company is intentionally spying on us and building a huge record about each of us?
None of the tech giants accept this fact, but most are selling your data to the government, including companies like Samsung that are into the hardware business.
Is there are a way that can help you evade this online snooping? Probably no if you consider mainstream services and social media platforms. Till then, if you want to stay below the radar, delete your accounts and data on all mainstream email service providers, instant messaging apps, service providing websites and social media platform.
Vishal Ingole, November 22, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Big Data: Stunners from Researchers
November 18, 2016
I read “Big Data Shows People’s Collective Behavior Follows Strong Periodic Patterns.” May I suggest you sit down, take a deep breath, and contemplate a field of spring flowers before you read these findings. I am not kidding. Hot stuff, gentle reader.
According to the write up,
New research has revealed that by using big data to analyze massive data sets of modern and historical news, social media and Wikipedia page views, periodic patterns in the collective behavior of the population can be observed that could otherwise go unnoticed.
Here are the findings. I take no responsibility for the impact of these Big Data verified outputs. You are on your own. You now have your trigger warning about the findings from online news, newspapers, tweets, and Wikipedia usage. The findings are:
- “People’s leisure and work were regulated by the weather with words like picnic or excursion consistently peaking every summer in the UK and the US.”
- Diet, fruits, foods, and flowers were influenced by the seasons.
- Measles surface in the spring
- Gooseberries appear in June. (Well, maybe not in Harrod’s Creek.)
- Football and Oktoberfest become popular in the fall. (Yep, October for Oktoberfest, right?)
- People get depressed in the winter.
Now you have it. Big Data delivers.
Stephen E Arnold, November 18, 2016
Big Data Teaches Us We Are Big Paranoid
November 18, 2016
I love election years! Actually, that is sarcasm. Election years bring out the worst in Americans. The media runs rampant with predictions that each nominee is the equivalent of the anti-Christ and will “doom America,” “ruin the nation,” or “destroy humanity.” The sane voter knows that whoever the next president is will probably not destroy the nation or everyday life…much. Fear, hysteria, and paranoia sells more than puff pieces and big data supports that theory. Popular news site Newsweek shares that, “Our Trust In Big Data Shows We Don’t Trust Ourselves.”
The article starts with a new acronym: DATA. It is not that new, but Newsweek takes a new spin on it. D means dimensions or different datasets, the ability to combine multiple data streams for new insights. A is for automatic, which is self-explanatory. T stands for time and how data is processed in real time. The second A is for artificial intelligence that discovers all the patterns in the data.
Artificial intelligence is where the problems start to emerge. Big data algorithms can be unintentionally programmed with bias. In order to interpret data, artificial intelligence must learn from prior datasets. These older datasets can show human bias, such as racism, sexism, and socioeconomic prejudices.
Our machines are not as objectives as we believe:
But our readiness to hand over difficult choices to machines tells us more about how we see ourselves.
Instead of seeing a job applicant as a person facing their own choices, capable of overcoming their disadvantages, they become a data point in a mathematical model. Instead of seeing an employer as a person of judgment, bringing wisdom and experience to hard decisions, they become a vector for unconscious bias and inconsistent behavior. Why do we trust the machines, biased and unaccountable as they are? Because we no longer trust ourselves.”
Newsweek really knows how to be dramatic. We no longer trust ourselves? No, we trust ourselves more than ever, because we rely on machines to make our simple decisions so we can concentrate on more important topics. However, what we deem important is biased. Taking the Newsweek example, what a job applicant considers an important submission, a HR representative will see as the 500th submission that week. Big data should provide us with better, more diverse perspectives.
Whitney Grace, November 18, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Dark Web Marketplaces Are Getting Customer Savvy
November 17, 2016
Offering on Dark Web marketplaces are getting weirder by the day. Apart from guns, ammo, porn, fake identities, products like forged train tickets are now available for sale.
The Guardian in an investigative article titled Dark Web Departure: Fake Train Tickets Go on Sale Alongside AK-47s reveals that:
At least that’s the impression left by an investigation into the sale of forged train tickets on hidden parts of the internet. BBC South East bought several sophisticated fakes, including a first-class Hastings fare, for as little as a third of their face value. The tickets cannot fool machines but barrier staff accepted them on 12 occasions.
According to the group selling these tickets, the counterfeiting was done to inflict financial losses on the operators who are providing deficient services. Of course, it is also possible that the fake tickets are used by people (without criminalistics inclinations) who do not want to pay for the full fares.
One school of thought also says that like online marketplaces on Open Web, Dark Web marketplaces are also getting customer-savvy and are providing products and services that the customers need or want. This becomes apparent in this portion of the article:
The academics say the sites, once accessed by invitation or via dark-web search engines (there’ll be no hyperlinks here) resemble typical marketplaces such as Amazon or eBay, and that customer service is improving. “Agora was invitation-only but many of these marketplaces are easily accessible if you know how to search,” Dr Lee adds. “I think any secondary school student who knows how to use Google could get access – and that’s the danger of it.
One of the most active consumer group on Dark Web happens to be students, who are purchasing anything from fake certificates to hacker services to improve their grades and attendance records. Educational institutions, as well as law enforcement officials, are worried about this trend. And as more people get savvy with Dark Web, this trend is going to strengthen creating a parallel e-commerce, albeit a dark one.
Vishal Ingole, November 17, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
AI to Profile Gang Members on Twitter
November 16, 2016
Researchers from Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) are claiming that an algorithm developed by them is capable of identifying gang members on Twitter.
Vice.com recently published an article titled Researchers Claim AI Can Identify Gang Members on Twitter, which claims that:
A deep learning AI algorithm that can identify street gang members based solely on their Twitter posts, and with 77 percent accuracy.
The article then points out the shortcomings of the algorithm or AI by saying this:
According to one expert contacted by Motherboard, this technology has serious shortcomings that might end up doing more harm than good, especially if a computer pegs someone as a gang member just because they use certain words, enjoy rap, or frequently use certain emojis—all criteria employed by this experimental AI.
The shortcomings do not end here. The data on Twitter is being analyzed in a silo. For example, let us assume that few gang members are identified using the algorithm (remember, no location information is taken into consideration by the AI), what next?
Is it not necessary then to also identify other social media profiles of the supposed gang members, look at Big Data generated by them, analyze their communication patterns and then form some conclusion? Unfortunately, none of this is done by the AI. It, in fact, would be a mammoth task to extrapolate data from multiple sources just to identify people with certain traits.
And most importantly, what if the AI is put in place, and someone just for the sake of fun projects an innocent person as a gang member? As rightly pointed out in the article – machines trained on prejudiced data tend to reproduce those same, very human, prejudices.
Vishal Ingole, November 16, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Big Data Is So Big
November 4, 2016
I love simplifications. I love simplifications even more when they arrive with nary a footnote, explanation of sources, or comments about methodology. Ta da. Let me point you to an IDC chart at this location. If the link does not resolve, contact IDC. I bet you can buy this picture.
My copy arrived via a tweet. More fascinating that the weird collection of circles is that the work comes from the same outfit which tried to sell my research on Amazon. The tweet with the wonky chart was free, but IDC slapped a $3,500 price tag on eight pages of information with my name but without my permission for its Amazon venture. At least my research team used footnotes. Ah, IDC, home of the “how much time you waste looking for information” craziness. A wonderful resource because — you know, like, really — Big Data are so big.
Stephen E Arnold, November 4, 2016
The CIA Claims They Are Psychic
November 2, 2016
Today’s headline sounds like something one would read printed on a grocery store tabloid or a conspiracy Web site. Before I start making claims about the Illuminati, this is not a claim about magical powers, but rather big data and hard science…I think. Defense One shares that, “The CIA Says It Can Predict Social Unrest As Early As 3 To 5 Days Out.” While deep learning and other big data technology is used to drive commerce, science, healthcare, and other industries, law enforcement officials and organizations are using it to predict and prevent crime.
The CIA users big data to analyze data sets, discover trends, and predict events that might have national security ramifications. CIA Director John Brennan hired Andrew Hallman to be the Deputy Director for Digital Innovations within the agency. Under Hallman’s guidance, the CIA’s “anticipatory intelligence” has improved. The CIA is not only using their private data sets, but also augment them with open data sets to help predict social unrest.
The big data science allows the CIA to make more confident decisions and provide their agents with better information to assess a situation.
Hallman said analysts are “becoming more proficient in articulating” observations to policymakers derived in these new ways. What it adds up to, Hallman said, is a clearer picture of events unfolding—or about to unfold—in an increasingly unclear world.
What I wonder is how many civil unrest events have been prevented? For security reasons, some of them remain classified. While the news is mongering fear, would it not be helpful if the CIA shared some of its success stats with the news and had them make it a priority to broadcast it?
Whitney Grace, November 2, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Be Prepared for Foggy Computing
October 31, 2016
Cloud computing allows users to access their files or hard drive from multiple devices at multiple locations. Fog computing, on the other hand, is something else entirely. Fog computing is the latest buzzword in the tech world and pretty soon it will be in the lexicon. If you are unfamiliar with fog computing, read Forbes’s article, “What Is Fog Computing? And Why It Matters In Our Big Data And IoT World.”
According to the article, smartphones are “smart” because they receive and share information with the cloud. The biggest problem with cloud computing is bandwidth, slow Internet speeds. The United States is 35th in the world for bandwidth speed, which is contrary to the belief that it is the most advanced country in the world. Demand for faster speeds increases every day. Fog computing also known as edge computing seeks to resolve the problem by grounding data. How does one “ground” data?
What if the laptop could download software updates and then share them with the phones and tablets? Instead of using precious (and slow) bandwidth for each device to individually download the updates from the cloud, they could utilize the computing power all around us and communicate internally.
Fog computing makes accessing data faster, more efficient, and more reliably from a local area rather than routing to the cloud and back. IBM and Cisco Systems are developing projects that would push computing to more local areas, such as a router, devices, and sensors.
Considering that there are security issues with housing data on a third party’s digital storage unit, it would be better to locate a more local solution. Kind of like back in the old days, when people housed their data on CPUs.
Whitney Grace, October 31, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Online Drugs Trade Needs Surgical Strikes
October 25, 2016
Despite shutdown of Silk Road by the FBI in 2013, online drug trade through Dark Net is thriving. Only military-precision like surgical strikes on vendors and marketplaces using technological methods can solve this problem.
RAND Corporation in its research papaer titled Taking Stock of the Online Drugs Trade says that –
Illegal drug transactions on cryptomarkets have tripled since 2013, with revenues doubling. But at $12-21 (€10.5-18.5) million a month, this is clearly a niche market compared to the traditional offline market, estimated at $2.3 (€2) billion a month in Europe alone.
The primary goal of the research paper was to determine first, the size and scope of cryptomarkets and second, to device avenues for law enforcement agencies to intervene these illegal practices. Though the report covered the entire Europe, the role of Netherlands, in particular, was studied in this report. This was owing to the fact that Netherlands has the highest rate of consumption of drugs acquired using cryptomarkets.
Some interesting findings of the report include –
- Though revenues have doubled, drug cryptomarkets are still niche and generate revenues of $21 million/month as compared to $2.1 billion in offline trade.
- Cannabis still is the most in demand followed by stimulants like cocaine and ecstasy-type drugs
- Vendors from US, Australia, Canada and Western Europe dominate the online marketplace
Apart from following the conventional methods of disrupting the drug trade (dismantling logistics, undercover operations, and taking down marketplaces), the only new method suggested includes the use of Big Data techniques.
Cryptomarkets are going to thrive, and the only way to tackle this threat is by following the money (in this case, the cryptocurrencies). But who is going to bell the cat?
Vishal Ingole, October 25, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
What Lurks in the Dark Web?
October 20, 2016
Organizations concerned about cyber security can effectively thwart any threats conditionally they know a threat is lurking in the dark. An Israeli SaaS-based startup claims it can bridge this gap by offering real-time analysis of data on Dark Web.
TechCrunch in an article Sixgill claims to crawl the Dark Web to detect future cybercrime says:
Sixgill has developed proprietary algorithms and tech to connect the Dark Web’s dots by analyzing so-called “big data” to create profiles and patterns of Dark Web users and their hidden social networks. It’s via the automatic crunching of this data that the company claims to be able to identify and track potential hackers who may be planning malicious and illegal activity.
By analyzing the data, Sixgill claims that it can identify illegal marketplaces, data leaks and also physical attacks on organizations using its proprietary algorithms. However, there are multiple loopholes in this type of setup.
First, some Dark Web actors can easily insert red herrings across the communication channels to divert attention from real threats. Second, the Dark Web was created by individuals who wished to keep their communications cloaked. Mining data, crunching it through algorithms would not be sufficient enough to keep organizations safe. Moreover, AI can only process data that has been mined by algorithms, which is many cases can be false. TOR is undergoing changes to increase the safeguards in place for its users. What’s beginning is a Dark Web arms race. A pattern of compromise will be followed by hardening. Then compromise will occur and the Hegelian cycle repeats.
Vishal Ingole, October 20, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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