Sunday, January 12, 2020


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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