Interesting, but why in the Justice Dept? Have they decided these are not warlike acts?
Justice Department Announces New National Security Cyber Section Within the National Security Division
The Justice Department today announced the creation of the new National Security Cyber Section – known as NatSec Cyber – within its National Security Division. The newly established litigating section has secured congressional approval and comes in response to the core findings in Deputy Attorney General Lisa O. Monaco’s Comprehensive Cyber Review in July of 2022.
“NatSec Cyber will give us the horsepower and organizational structure we need to carry out key roles of the Department in this arena,” said Assistant Attorney General Matthew G. Olsen of the Justice Department’s National Security Division. “This new section will allow NSD to increase the scale and speed of disruption campaigns and prosecutions of nation-state threat actors, state-sponsored cybercriminals, associated money launderers, and other cyber-enabled threats to national security.”
The National Security Cyber Section will increase the Justice Department’s capacity to disrupt and respond to malicious cyber activity, while promoting Department-wide and intragovernmental partnerships in tackling increasingly sophisticated and aggressive cyber threats by hostile nation-state adversaries. The Section will bolster collaboration between key partners, notably the Criminal Division’s Computer Crimes and Intellectual Property Section (CCIPS) and the FBI’s Cyber Division and will serve as a valuable resource for prosecutors in the 94 U.S. Attorneys’ Offices and 56 FBI Field Offices across the country.
“Responding to highly technical cyber threats often requires significant time and resources,” said Assistant Attorney General Olsen. “NatSec Cyber will serve as an incubator, able to invest in the time-intensive and complex investigative work for early-stage cases.”
Today’s announcement builds upon recent successes in identifying, addressing and eliminating national security cyber threats, including the charging of an alleged cybercriminal with ransomware attacks against U.S. critical infrastructure and disruption the Russian government’s premier cyberespionage malware tool.
Might be interesting to law enforcement too.
https://www.bespacific.com/how-your-new-car-tracks-you/
How Your New Car Tracks You
Wired (free link) -” Vehicles from Toyota, Honda, Ford, and more can collect huge volumes of data. Here’s what the companies can access… In May, US-based automotive firm Privacy4Cars released a new tool, dubbed the Vehicle Privacy Report, that reveals how much information on your car can be hoovered up. Much like Apple and Google’s privacy labels for apps — which show how Facebook might use your camera, or how Uber might use your location data—the tool indicates what vehicle manufacturers can know. Using industry sales data, WIRED ran 10 of the most popular cars in the US through the privacy tool to see just how much information they can collect. Spoiler: It’s a lot. The analysis follows previous reporting on the amount of data modern cars can collect and share—with estimates saying cars can produce 25 gigabytes of data per hour …”
“On the Internet, nobody knows you’re a dog.” Not so in the office.
Gen-Z Is Taking Courses On How To Send An Email and What To Wear In the Office
Business Insider: “Recent graduates from Generation Z, who have primarily experienced virtual classes and remote internships during college, may need to improve their soft skills such as email writing, casual conversation, and appropriate work attire. According to a new report from the Wall Street Journal, companies like KPMG, Deloitte, and PwC are offering training programs to help these employees adapt to the office, focusing on in-person communication, eye contact, conversation pauses, and professional dress. Insider reports: KPMG is offering new hires introductory training that includes how to talk to people in person, with tips on the appropriate level of eye contact and pauses in a conversation, the company’s vice chair of talent and culture, Sandy Torchia, told the Journal. Deloitte and PwC also began offering similar trainings earlier this year, the Financial Times reported in May. Similarly, the consulting company Proviti said it expanded its training for new hires during the pandemic to include a series of virtual meetings that focus on issues like how to make authentic conversation, according to the Journal. Scott Redfearn, Protiviti’s executive vice president of global human resources, told the Journal the company has had to remind new hires to avoid casual attire like blue jeans with holes in them. Some universities have also stepped in to bridge the gap. Michigan State University’s director of career management, Marla McGraw, told the Journal that companies need to be more direct when it comes to telling new hires what to wear and how to act in the office. The school now requires many of its business majors to take classes that foster soft skills like how to network in person. The Journal reported that one course breaks down a networking conversation by reminding students to pause after they introduce themselves in order to let the other person say their name, as well as respond to signs the other person might be looking to end the conversation. While it’s common for companies to host onboarding sessions that cover office dynamics like attire and rules for interpersonal relationships, some experts say younger employees need these reminders now more than ever.”
Perspective. (It’s not that complicated…)
https://www.kdnuggets.com/2023/06/data-scientist-essential-guide-exploratory-data-analysis.html
A Data Scientist’s Essential Guide to Exploratory Data Analysis
Best practices, techniques, and tools to fully understand your data.
Exploratory Data Analysis (EDA) is the single most important task to conduct at the beginning of every data science project.
In essence, it involves thoroughly examining and characterizing your data in order to find its underlying characteristics, possible anomalies, and hidden patterns and relationships.
This understanding of your data is what will ultimately guide through the following steps of you machine learning pipeline, from data preprocessing to model building and analysis of results.
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