How
do we prove that you are you and not “some guy in China?”
Chinese
hacker group caught bypassing 2FA
Security
researchers say they found evidence that a Chinese government-linked
hacking group has been bypassing two-factor authentication (2FA) in a
recent wave of attacks.
The
attacks have been attributed to a group the cyber-security industry
is tracking as APT20, believed to operate on the behest of the
Beijing government, Dutch cyber-security firm Fox-IT said in a report
published last week.
The
group's primary targets were government entities and managed service
providers (MSPs). The government entities and MSPs were active in
fields like aviation, healthcare, finance, insurance, energy, and
even something as niche as gambling and physical locks.
Another
security failure?
Data,
Passwords Easily Extracted From Locked iPhones On iOS 13.3
A
Russian cybersecurity company that makes digital forensic tools for
law enforcement and business specialists has discovered a way to hack
into locked Apple iPhone devices. The method reportedly works on
most iPhone models ranging between iPhone 5s and iPhone X. It is
also effective on iPhone devices running on iOS 12 through iOS 13.3.
The
cybersecurity company is called Elcomsoft. It's newly expanded
capability to extract data even on devices running on iOS 13.3, which
many claims unlockable, is through the update rolled out on its iOS
Forensic Toolkit. The company claims that its iOS Forensic Toolkit
can extract specific pieces
of data from an iOS device before it has been unlocked.
Implications
for Bloggers everywhere!
RCFP
urges Delaware court to reject hyperlink republication argument
“The
Reporters Committee for Freedom of the Press and a coalition of 23
news organizations are
urging a Delaware court to reject a defamation claim that could
threaten the use of hyperlinks in news stories.
In
a friend-of-the-court
brief,
filed on Dec. 19 by Reporters Committee attorneys and David L. Finger
of Finger & Slanina LLP, the coalition urges the Delaware
Superior Court to rule that linking to previously published articles
online does not constitute republication…”
For
my Architecture students.
AI
infrastructure doesn’t have to be complicated or overwhelming
Artificial
Intelligence (AI) and Deep Learning (DL) are no longer the exclusive
realm of high performance computing (HPC) research used by government
and universities. A wide range of industries are now using AI and DL
to extract value from data and aid in business decisions. AI is
being used to uncover significant breakthroughs in areas such as
medical diagnostics, locating financial fraud, autonomous vehicles
and speech recognition for a number of market applications. However,
AI and DL pose exceptional challenges and put significant strain on
compute, storage and network resources. An AI-enabled datacenter
must concurrently and efficiently handle activities involved in DL
workflows, including data
ingest, data curation, training, inference, validation and
simulation. Thus, the storage and management of data has
become a critical component of today’s data centers.
AI
law is likely to be complicated and overwhelming.
EPO
rejects ‘AI inventor’ patent applications
Late
last week, the European
Patent Office (EPO)
refused two patent applications that list an artificial intelligence
(AI) application as the sole inventor.
After
hearing the arguments of the applicant, the EPO refused
the
European patent applications as they don’t meet the requirement
that an inventor designated in the application has to be a human
being, not a machine.
Design
for uncertainty?
How
to teach artificial intelligence and say, “I’m not sure”
One
of the biggest challenges in advanced analytics is developing
mechanisms to determine how reliable the decisions made by algorithms
are. Now, research by BBVA’s Artificial Intelligence Factory is
proposing a new method to make machine learning models capable of
expressing the uncertainty in their predictions in a clearer manner.
It’s an exploratory approach to make artificial intelligence more
transparent, measure the reliability of its predictions and fine
tune the accuracy of its results.
… “The
problem is that these kind of systems do not normally provide us
information on the uncertainty underlying their prediction
processes,” explains Axel Brando, Data Scientist at BBVA’s AI
Factory and one of the authors of the research. In other words, they
are trained to always provide a single solution, even when there
could be equally probable options, thus crucial information could be
lost. “By default, most
predictive systems are usually designed in a way that they cannot
offer an “I don’t know”, or “I’m not sure” as an answer,
he adds. The researcher explains that this situation is problematic
when predictive models are applied to risk scenarios where the cost
of making mistakes in predictions is sufficiently elevated. In these
situations it is preferable to not make automated predictions “when
the systems knows that it is very likely that they won’t be
correct.”
… in
order to understand
the technical aspects of
this work, you can watch a three minute video-summary,
read the scientific
paper presented
at the conference, or experiment
with
the implementation of the model proposed in the article (UMAL;
Uncountable Mixture of Asymmetric Laplacians) individually in
different public access problems.
An
interesting question for my students. (How far from that are we
today?)
Would
You Want a Personal AI That Knows Everything About You?
… The
AI
Foundation,
which describes
itself as
“a non-profit
and a
for-profit
organization
working to move the world forward with AI responsibly,” is
developing a tool that will let anyone build their own AI. Those at
the Foundation believe that personalizing and distributing the power
of AI,
as opposed to having it concentrated and controlled by a select few,
will help unleash its full positive potential. They emphasize that
the AIs built using their tool will possess each user’s unique
values and goals, and will help users overcome limitations we’re
currently subject to in the non-personal-AI world.
… Author
and alternative medicine advocate Deepak Chopra was happy to be the
Foundation’s guinea pig: an AI
version of him,
in the form of an app, will go live in early 2020. Users will be
able to talk to digital Deepak and get advice from him, and the app
will customize itself to each user; if you tell digital Deepak that
you’re prone to sinus infections or that you tend to feel sad on
Sundays, he’ll remember and take that information into account for
future conversations, perhaps reminding you to devote some extra time
to meditation each Sunday morning.
(Related)
What
does your car know about you?
Washington
Post –
“Our
privacy experiment found that automakers collect data through
hundreds of sensors and an always-on Internet connection. Driving
surveillance is becoming hard to avoid… Cars have become the most
sophisticated computers many of us own, filled with hundreds of
sensors. Even older models know an awful lot about you. Many copy
over personal data as soon as you plug in a smartphone… We’re at
a turning point for driving surveillance: In the 2020 model year,
most new cars sold in the United States will come with built-in
Internet connections, including 100 percent of Fords, GMs and BMWs
and all but one model Toyota and Volkswagen. (This independent
cellular service is often included free or sold as an add-on.) Cars
are becoming smartphones on wheels, sending and receiving data from
apps, insurance firms and pretty much wherever their makers want.
Some
brands even reserve the right to use the data to track you down if
you don’t pay your bills…”
(Related) Using public data to develop products
you didn’t know you wanted.
Social
Listening Is Revolutionizing New Product Development
Every day, billions of people talk on social media
about where they’ve been, what they’ve bought, and their feelings
and opinions about products and services. This information is a gold
mine for consumer-facing industries, including retail, consumer
goods, retail banking, insurance, and health care. But few companies
have acted on this valuable data.
Companies have traditionally relied on surveys,
focus groups, and research reports to assess what consumers think of
their products or services, but these traditional approaches have
several shortcomings. Sample sizes are limited and subject to bias.
Studies take time to organize, and results quickly become dated.
Moreover, what people say often differs from what they do, like
complaining about discount airlines but using them all the same.
Leaders who employ social listening — analyzing
what consumers say on social media — can gain a competitive
advantage by getting better insights that they can act on quickly,
without incurring the higher cost of traditional approaches.
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