A successful day of phishing. Very little useful data so far.
Texas
school district loses $2.3 million from phishing scam
KSAT
reports:
Manor Independent School District, just east of Austin, is out of $2.3 million from a phishing scam.
Investigators say the phishing email was sent to multiple people at the school district and it was a single person that responded.
The money was sent through three separate transactions.
Read
more on KSAT,
[From
the article:
Investigators said whoever paid didn’t realize
the bank account information was changed and it was being sent to a
fake bank.
Security and AI
The dangers
of IoT and AI
The
risks of cybersecurity are more complex than ever. Due to the rise
of the Internet of Things (IoT) and
Artificial
Intelligence (AI),
by
2020 every person will generate 1.7 megabytes of information per
second.
As new technologies evolve, cyber criminals adapt and discover new
hacking methods to apprehend sensitive data. AI and IoT have the
potential to revolutionise society, but what happens when these new
technologies are weaponized by cyber criminals?
Unless
hardware-based endpoint
security solutions
are implemented in IoT and AI devices, users leave themselves
vulnerable to cyberattacks. Anyone in control of one or more of
these devices can access a huge number of computers and networks.
This
may have real potential! If nothing else, a guide to forensic
investigators when something goes wrong?
Datasheets
for Datasets
Currently
there is no standard way to identify how a dataset was created, and
what characteristics, motivations, and potential skews it represents.
To begin to address this issue, we propose the concept of a
datasheet for datasets, a short document to accompany public
datasets, commercial APIs, and pretrained models. The goal of this
proposal is to enable better communication between dataset creators
and users, and help the AI community move toward greater transparency
and accountability. By analogy, in computer hardware, it has become
industry standard to accompany everything from the simplest
components (e.g., resistors), to the most complex microprocessor
chips, with datasheets detailing standard operating characteristics,
test results, recommended usage, and other information. We outline
some of the questions a datasheet for datasets should answer. These
questions focus on when, where, and how the training data was
gathered, its recommended use cases, and, in the case of
human-centric datasets, information regarding the subjects'
demographics and consent as applicable. We develop
prototypes of datasheets for two well-known datasets: Labeled Faces
in The Wild and the Pang \& Lee Polarity Dataset.
Hits everything I’m teaching this year!
The 4
Hottest Trends in Data Science for 2020
Companies
all over the world across a wide variety of industries have been
going through what people are calling a digital
transformation.
That
is, businesses are taking traditional business processes such as
hiring, marketing, pricing, and strategy, and using digital
technologies to make them 10 times better.
Data
Science has become an integral part of those transformations. With
Data Science, organizations no longer have to make their important
decisions based on hunches, best-guesses, or small surveys. Instead,
they’re analyzing large amounts of real data to base their
decisions on real, data-driven facts.
… The
following are the 4 hottest Data Science trends for the year 2020.
These are trends which have gathered increasing interest this year
and will continue to grow in 2020.
(1)
Automated Data Science
(2)
Data Privacy and Security
(3)
Super-sized Data Science in the Cloud
(4)
Natural Language Processing
The logic of selfies?
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