Apple Sends Facebook To The Principal’s Office
February 8, 2019
Facebook was wearing a dunce cap. According to Recode, Apple is not happy with the social media giant: “Apple Says It’s Banning Facebook’s Research App That Collects Users’ Personal Information.” Apple is accusing Facebook of breaching an agreement with a new “research” app. Basically, Facebook paid users for sharing their personal information with the app, such as private messages, location data, etc. The big stickler is that users as young as thirteen were targeted.
It is against Apple’s privacy policy to collect any kind of data and apps of this nature are no available in the Apple App Store. Facebook found a loop through Apple’s “Developer Enterprise Program,” where Apple partners can release apps for testing, mostly for their own employees. The apps are not available to the general public and Facebook used this method to pay users to download the app and get paid.
Facebook’s options are similar to country-to-country negotiations: Do what’s necessary to reduce tensions. The Facebook can figure out how to work around the “problem.” I learned:
“The story also shows how important it is for Facebook to collect data on other apps people use on their phones. It’s a big competitive advantage, and collecting this kind of data isn’t foreign to Facebook. The company actually collected similar user data through a separate app Facebook owns called Onavo Protect, which was just removed from the App Store in August for violating Apple’s guidelines. (It’s still available for Android users.)”
User data tell social media sites like Facebook about their habits and then that information can be sold to advertisers. The question is how long will Apple abide by its privacy guidelines, or is Apple flexing its muscles for another reason?
Whitney Grace, February 8, 2019
Deep Fakes: A Tough Nut to Crack
February 8, 2019
If you are in the media or intelligence business, you undoubtedly already know about the potential of deep fakes or “deepfake” videos. Clips that utilize AI technology to create realistic and completely fake videos using existing footage. The catch is that they are getting more and more convincing…and that’s not good, as we discovered in a recent Phys.org article, “Misinformation Woes Could Multiply with Deepfake Videos.”
According to the story:
“As the technology advances, worries are growing about how deepfakes can be used for nefarious purposes by hackers or state actors. ‘A well-timed and thoughtfully scripted deepfake or series of deepfakes could tip an election, spark violence in a city primed for civil unrest, bolster insurgent narratives about an enemy’s supposed atrocities, or exacerbate political divisions in a society.’”
What’s “true” and what’s “false” is an issue which may not lend itself to zeros and ones. Google asserts that it is developing software that helps spot deepfakes. Does Google have a solution?
Does anyone?
If an artifact is created and someone labels it “false,” smart software has to decide. Humans, history suggests, struggle with defining the truth.
The problem is likely to be difficult to resolve. Censorship anyone?
Patrick Roland, February 8, 2019
Google: Is Waze Getting Lost?
February 7, 2019
I read “NYPD Demands Google Stop Waze from Revealing User-Reported Location of DWI Checkpoints.” According to the write up:
the NYPD has just sent a cease and desist letter to Google, demanding that the reporting feature no longer reveal the location of DWI checkpoints.
User reported data may become a contentious issue. Some drivers may believe that their individual decision to post information is okay.
Google’s clever managers and engineers want users to rely on their services.
What if these services put lives at risk; specifically, make it possible for a person under the influence of a substance which impairs reflexes and thought? The issue of responsibility may be worth considering in the event of a pedestrian or injury to another driver? The driver, the map vendor, and/or the law enforcement entity?
What’s interesting is that government agencies in the US seem to be unable to work with certain high technology firms to resolve certain issues.
European regulators, on the other hand, seem to be more willing to adopt mechanisms to enforce applicable rules and regulations.
According to the write up:
Google essentially declined the request and cited benefits to the feature.
Interesting.
Stephen E Arnold, January 7, 2019
Google Translation: Getting More Intelligent?
February 7, 2019
Translation has never been easier with AI and NLP tools. It is amazing for people who cannot speak foreign languages to communicate with the assistance of translation apps, like Google Translation. While there are many translation apps on the market, Google is by far the best free one. As with many of its products and services, Google spends countless hours perfecting its language algorithms. The Verge published “Google’s Head of Translation On Fighting Bias In Language And Why AI Loves Religious Texts.”
Macduff Hughes heads Google’s translation and in the interview discusses how Google has moved from translating word by word but entire sentences. The new and smarter translation method is called “neural machine translation,” it uses machine learning, and a lot of its data comes from religious texts. One problem Google Translation faces is gender biased language. In order for translation AI to learn, it needs to be fed a lot of accurate and diverse data. These data sources, however, reflect societal biases which the AI can learn and replicate, such as doctors are male and nurses are female. The goal is to overcome these limitations so people know there is more than one way to phrase something as well as explain the differences.
Google is addressing three big bias and nuance initiatives. The first is to expand full sentence gender translation to more languages, the second is improving document translation based on context, and the third is addressing gender neutral languages. On a funnier and conspiracy based note is in 2018, when people typed nonsense words into Translate it spat back religious information. The explanation is a logical way of teaching AI:
“Usually it’s because the language you’re translating to had a lot of religious text in the training data. For every language pair we have, we train using whatever we can find on the world wide web. So the typical behavior of these models is that if it gets gibberish in, it picks out something that’s common in the training data on the target side, and for many of these low-resource languages — where there’s not a lot of text translated on the web for us to draw on — what is produced often happens to be religious.”
Translation is becoming a tool to organize more of the world’s information, according to Hughes, because it allows more people to access stuff that was in a different language. The naysayers argue that Translation provides a very shallow translation and Hughes acknowledges that. However, Translation works for basic translation and someday AI might have the skills of a professional linguist. It is not perfect, but Google Translate gets you to the train station and the bathroom.
Whitney Grace, February 6, 2019
Is Dark Web Search Getting Crowded?
February 7, 2019
Stephen E Arnold said in a recent DarkCyber video news report:
The Dark Web is one of the most crawled, most index content sources in the world.
The Dark Web may feel like a lawless Wild West for law enforcement and intelligence communities. A cesspool where illegal drugs and weapons and activities roam freely. But, the challenge of monitoring the actions on this covert online forum is getting easier because there are fewer sites to crawl and index, about 4,000 depending on the day one takes a count. Of these fewer than 60 account for most activity of interest to government authorities.
We learned in a recent Deep Dot Web article, “Categorizing Content on the Dark Web Via a Novel Crawler.”
According to the story:
“This crawler is developed to specifically crawl hidden services on the Tor network. Results were assessed via two steps: First, an initial group of hidden services were manually grouped into different categories and used to train a special document classifier (Support Vector Machine), which represents a statistical categorization algorithm that utilizes machine learning for content classification purposes. Secondly, an automated classifier was utilized to complete categorization of the remainder of dark web pages.”
While crawling through the muck of the deep web is currently the provenance of military, law enforcement and intelligence communities, that is poised to change.
Are there enough customers to support incumbents like Recorded Future and Digital Shadows as well as the newcomers?
Patrick Roland, February 7, 2019
Google Search and ATT Exposed Cable Report
February 6, 2019
Update at 320 US Eastern time:
I stopped an ATT repair truck (not a subcontractor). I reported the open box managing voice and data. The ATT employee told me, “The company doesn’t care. I can’t call it in. Even if I see a downed cable, management does not want to know. The new ATT.” Interesting insight into a company which advertises “moments together.” More like no moments whatsoever.
Original Story:
Come across an exposed cable or exposed cables? Run a Google query for ATT cable down and one gets the first result: 800 288 2020. Like this:
Now the first hit means relevance, or that’s my assumption. Dial the number and the automated system only responds if one is an ATT customer who has an account number. What happens if a child fiddles with the exposed cable or gear? Let’s think about the risks to the youngster. What about the risks to actual ATT wireless, DirecTV, or phone / data services?
Nice work Google. A useless phone number. Nicer work ATT. Putting children and users at risk. (Please, don’t call me and tell me that someone somewhere is sorry. I don’t believe those sophistries.) We can make moments together in another way.
Stephen E Arnold, February 6, 2019
Google: GDPR Vulnerability?
February 6, 2019
If you are curious about the impact of the GDPR on Google, you may want to take a look at “What to Know about Google’s GDPR Troubles.” I don’t have a good sense of what constitutes an objective review of Google and GDPR. Also, I don’t know if the information in the write up from Digiday is 100 percent accurate. Footnotes can be helpful when they are included.
Nevertheless, the article suggests that Google may be a target for individual EU member actions related to GDPR. At this point, it is not clear how many legal entities can go after the company generating more than $80 million a day in profit.
The write up states:
While the majority of GDPR warnings and fines have come from the French regulator, it won’t likely remain that way.
The cost of litigating in separate companies and any fines levied could become onerous even to an outfit like Alphabet Google.
Stephen E Arnold, February 6, 2019
Excitement for Twitter Slurpers
February 6, 2019
TechTimes reported that Facebook now makes publicly available what the Zuck has had for some time. One can delete Facebook messages. The options are delete for everyone or just for the sender. The speed with which the messages disappear from the Facebook servers is murky. If you are a Twitter slurper, you may have to make certain that the slurps are taking place with alacrity. DarkCyber does not have a full count of the number of entities engaged in chugging down tweets, but there are more than some people may think. Tweets, like Facebook, provide a quite useful stream of data. Zippy analytics can make tweets turn cartwheels. Losing tweets from certain handles of interest is not good news.
Stephen E Arnold, February 6, 2019
Factualities for February 6, 2019
February 6, 2019
Did you pay attention in Statistics 101? If you did, some of these data may bring back recollections about what’s required for valid outputs. Test your knowledge.
$13 billion. The amount of revenue Apple generated fro China in the last 12 weeks. The number is 27 percent lower than the number reported one year ago for the comparable quarter. Source: CNBC
$7.37. Facebook’s average revenue per user. This number is up 19 percent year on year. Source: CNBC
$22.4 billion. The amount of money raised by startups in the San Francisco Bay area in 2018. Startups in the rest of the US raised $24.9 billion. Source: Crunchbase
6 hours, 42 minutes. The average amount of time an individual spends online every day. The total time spent online per year is more than 100 days. Source: Metro
356. The number of Iran linked Facebook accounts removed from the service. The reason? “Coordinated inauthentic behavior.” Source: Facebook
24,500. The number of injection drug users in San Francisco. Source: Marginal Revolution
4.3 million. The number of times Google Play apps facilitating malicious apps were downloaded. Source: Arstechnica
267,000. The number of DirecTV subscribers lost by AT&T after a $5 price hike. Source: Motherboard
20 percent. The percentage of “people” in the world who believe the economic system is working for them. Source: Palladium Magazine
Fourth place. The rank of Iran’s cyber army in size among world powers. Source: IDG
1,580. Number of counterfeiting arrests the US Secret Service made in 2018. Source: LA Times
$17.9 billion. The cost of revenues for Google in 2018. The number is up 26 percent year on year. Source: CBR Online
Stephen E Arnold, February 5, 2019
LA Times and Its Counterfeiting Thriller
February 5, 2019
I read “Glowing Reviews Tout Counterfeit Cash on the Dark Web.” The news story is more like a thriller, however. The Dark Web, fake money, online investigations, and a shoot out.
DarkCyber noted several interesting factoids in the write up:
- Reviews by customers of the Dark Web counterfeiting operation were important to the criminal’s business. The article refers to a “loyal fan base.”
- The agency taking the lead in the investigation was the US Secret Service. DarkCyber has heard that this entity is the most capable team of cyber sleuths in the US government.
- The “printing” was carried out on lasers and special paper.
- The bad actor had a long history of illegal activities. (This suggests that pattern analysis may be a useful adjunct to a traditional investigation.)
- The bad actor mailed counterfeit bills on several occasions from a traditional outdoor mail box across from a police station.
- After neutralizing the bad actor, agents discovered “about $300,000 in fake $100 bills, lined up and hanging to dry in neat rows.”
Investigators have not solved the problem of the location of the digital currency to which the bad actor had access. Also, computers seized in the raid were encrypted, and these, according to the write up, have not yet been decrypted by the USSS.
Stephen E Arnold, February 5, 2019
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