The Senate Committee on Homeland Security and Governmental Affairs passed multiple cybersecurity bills, including the Cybersecurity Vulnerability Identification and Notification Act of 2019 and the Cybersecurity State Coordinator Act of 2020 at a March 11 markup.
The Cybersecurity and Infrastructure Security Agency (CISA) late last week issued a practical checklist to help executives “think through” infrastructure protection, supply chain, and cybersecurity issues in light of the COVID-19 coronavirus, and potential effects to workforce and operations.
Despite an increased focus on the gender imbalance in the tech workforce, a significant gender pay gap remains, according to a March 5 report from Dice, a career hub for technology professionals.
President Trump today signed into law a bill quickly approved by House and Senate this week that provides $8.3 billion of funding for Federal government response to the COVID-19 coronavirus, including vaccine and treatment development, support for state and local health agencies, and loans for small businesses impacted by the virus.
West Virginia Secretary of State Mac Warner announced Feb. 28 that the state will cease using the Voatz app to allow West Virginians living abroad and voters with disabilities to vote via smartphone.
The House voted late on March 4 to approve the Coronavirus Preparedness and Response Supplemental Appropriations Act (HR 6074) that would make $8.3 billion of new funding available for a “robust response” to the COVID-19 coronavirus, including vaccine and treatment development, support for state and local health agencies, and loans for small businesses impacted by the virus.
While business owners told members of the House Small Business Committee at a March 4 hearing how they use blockchain in their operations, a question from the committee’s chairwoman led to talk of bigger operations that could benefit from blockchain – state governments.
In a report released Feb. 25, the Government Accountability Office (GAO) said that “most” of nine agencies tasked with protecting the 16 critical infrastructure sectors “have not developed methods to determine the level and type of adoption of the National Institute of Standards and Technology’s (NIST) Framework for Improving Critical Infrastructure Cybersecurity.”
A group of graduate researchers from the University of California-Berkeley trained a machine learning model to predict voter preferences using only readily available personal information, suggesting further-reaching implications on the use of AI to infer voter behavior and potentially influence elections.
State and local election officials said at the RSA security conference in San Francisco on Feb. 24 that Federal election assistance funding has been vital to their efforts to shore up election infrastructure security over the past few years.
