They
didn’t hack their targets directly, they hack the Twitter employees
who already had access to these accounts.
Twitter
says hacking of high-profile Twitter accounts was a "coordinated
social engineering attack"
Some
of the world's richest and most influential politicians, celebrities,
tech moguls and companies were the subject of a massive Twitter hack
on Wednesday. Elon Musk, Joe Biden, Jeff Bezos, Michael Bloomberg,
Kim Kardashian West and Bill Gates were among the accounts pushing
out tweets asking millions of followers to send money to a Bitcoin
address.
… Twitter
said in a statement that the company detected what they believed to
be "a coordinated social engineering attack by people who
successfully targeted some
of our employees with access to internal systems and tools."
… Companies,
including Apple and Uber, were apparently hacked as well. Following
the incident, all of Apple's tweets appeared to have been deleted.
(Related)
This is a bit of an overreaction – isn’t it?
A
catastrophe at Twitter
…
After
today it is no longer unthinkable, if it ever truly was, that someone
take over the account of a world leader and attempt to start a
nuclear war. (A report on that subject from King’s College London
came
out just last week.)
Start
securing your data…
TrojanNet
– a simple yet effective attack on machine learning models
Injecting
malicious backdoors into deep neural networks is easier than
previously thought, a new study by researchers at Texas A&M
University shows.
… The
threat of trojan attacks against AI systems has also drawn the
attention of US government agencies.
“With
the rapid commercialization of DNN-based products, trojan attacks
would become a severe threat to society,” the Texas A&M
researchers write.
Previous
research pertains that hiding a trojan in a deep learning system is
an arduous, costly, and time-consuming process.
But
in their paper, titled ‘An
Embarrassingly Simple Approach for Trojan Attack in Deep Neural
Networks’,
the Texas A&M researchers show that all it takes to weaponize a
deep learning algorithm is a few tiny patches of pixels and a few
seconds’ worth of computation resources.
Should
work as well as any other predictive policing.
Cities
Turn to Software to Predict When Police Will Go Rogue
A
startup selling tech to identify ‘bad apples’ shows the promise
and challenges of using data to improve policing.
Another
perspective.
An
Ethics Guide for Tech Gets Rewritten With Workers in Mind
IN
2018, SILICON Valley,
like Hamlet’s engineer, was hoist with its own petard. Citizens
were panicking
about data privacy,
researchers were sounding
alarms about
artificial
intelligence,
and even industry stakeholders
rebelled
against app addiction. Policymakers, meanwhile, seemed to take a
renewed interest in breaking up big tech, as a string
of
congressional
hearings
put
CEOs in the hot seat over the products they made. Everywhere,
techies were grasping for answers to the unintended consequences of
their own creations. So the Omidyar Network—a “philanthropic
investment firm” created by eBay founder Pierre Omidyar—set out
to provide them. Through the firm’s newly minted Tech and Society
Solutions Lab, it issued a tool kit called the
EthicalOS,
to teach tech leaders how to think through the impact of their
products ahead of time.
Two
years later, some things have changed. But it’s not CEOs who are
leading the charge. It’s the workers—engineers, designers,
product managers—who have become the loudest voices for reform in
the industry. So when it came time for the Omidyar Network to
refresh its tool kit, it became clear that a new target audience was
needed.
… The
kit includes a “field guide” for navigating eight risk zones:
surveillance, disinformation, exclusion, algorithmic bias, addiction,
data control, bad actors, and outsize power
For
anyone keeping score...
These
Are the Highest Penalties under GDPR – Including Fines Issued to
Private Individuals
PrivacyAffairs,
a leading source of data privacy and cybersecurity research, has
issued a report tallying fines issued under the 2018 General Data
Protection Regulation (GDPR). It also lists the countries where the
highest fines were dealt, as well as the nations with the most
punishable incidents.
According
to the research firm, since its rollout in May 2018, the GDPR has
claimed 340 ‘victims’ for unlawful data protection practices.
The
report notes
that every single one of the 28 EU nations, including the now
Brexited United Kingdom, has issued at least one penalty under the
new data protection legislature.
Two
people out of a million (or more).
Amazon,
Google, Microsoft sued over photos in facial recognition database
Amazon,
Google parent
Alphabet and Microsoft
used
people's photos to train their facial
recognition technologies
without obtaining the subjects' permission, in violation of an
Illinois biometric privacy statute, a trio of federal lawsuits filed
Tuesday allege.
The
photos in question were part of IBM's
Diversity
in Faces database,
which is designed to advance the study of fairness and accuracy in
facial recognition by looking at more than just skin tone, age and
gender. The data includes 1 million images of human
faces,
annotated with tags such as face symmetry, nose length and forehead
height.
The
two Illinois residents who brought the lawsuits, Steven Vance and Tim
Janecyk, say their images were included in that data set without
their permission, despite
clearly identifying themselves as residents of Illinois. [Can
that be accomplished when only the image is used? Bob]
But
will all this activity result in a Covid vaccine?
Deep
Dive Into Big Pharma AI Productivity: One Study Shaking The
Pharmaceutical Industry
… On
June 15th, one article titled “The
upside of being a digital pharma player”
got
accepted and quietly went online in a reputable peer-reviewed
industry journal Drug
Discovery Today.
… Upon
a closer look it turned out to be not a perspective but a
comprehensive research study with a head-to-head comparison of the
pharmaceutical companies by their efforts in AI in research and
development.
No comments:
Post a Comment