This website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.
This Website Uses Cookies By closing this message or continuing to use our site, you agree to our cookie policy. Learn MoreThis website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.
It’s undeniable that Machine Learning (ML) is changing the game for securing cloud infrastructure. Security vendors have rapidly adopted ML as part of their solutions, and for good reason: By analyzing massive quantities of data, it can help identify threats, speed incident response, and ease the burden on over-taxed security operations teams.
Over the last six months, COVID-19 has fueled online shopping. In fact, according to the U.S. Department of Commerce, online (e-commerce) sales grew more than 31% from Q1 to Q2 2020.
Small-to-medium-sized businesses (SMBs) have a number of unique considerations when it comes to video surveillance. For starters, with SMBs, managing security and risk often falls to a manager, store owner, or hourly security professional. Therefore, the convenience of being able to view multiple sites at once whether remotely or onsite is paramount.
NOAA’s Satellite and Information Service (NESDIS) has signed an agreement with Google to explore the benefits of Artificial Intelligence (AI) and Machine Learning (ML) for enhancing NOAA’s use of satellite and environmental data.
A couple of months ago, I described in this column how security professionals could unify a divided country. I chose a mask as a symbol of that cohesiveness. But that thin piece of fabric worn around the mouth and nose can also be a gag — a barrier that distances leaders and stifles communication.
Security operations centers (SOCs) across the globe are most concerned with advanced threat detection and are increasingly looking to artificial intelligence (AI) and machine learning (ML) technologies to proactively safeguard the enterprise, according to a new study by Micro Focus, in partnership with CyberEdge Group.
Financial services institutions and banks around the globe face monumental challenges as they look to streamline service delivery for customer transactions, manage multi-party loan processes, collaborate on industry benchmarks and indices, and eliminate fraud and cybercrime. Historically the market has primarily relied upon manual approaches for sharing and managing transaction data. But advances in confidential computing (sometimes called CC or trusted computing), combined with federated machine learning (FML), are helping financial organizations better share data and outcomes, while alleviating many privacy and security concerns.
With a growing need to improve the security, efficiency and accuracy of passenger and baggage screening, the Department of Homeland Security (DHS) Small Business Innovation Research (SBIR) Program is working with a small business to advance explosive detection equipment. Synthetik Applied Technologies was awarded funding to develop machine learning training data that simulates human travelers and baggage object models to support machine learning algorithms.
The shortage of skilled information security practitioners continues to grow around the globe. Based on 200 IT executives and contributors who primarily serve in information or IT security roles, this new research found that in the United States, for organizations with at least 500 employees, the average number of open positions enterprises are trying to fill is 1,324. For the largest percentage of respondents in this survey, that number increased between 1 percent and 25 percent over the last year, although that increase is higher for large enterprises.
The U.S. Department of Energy (DOE) announced $37 million in funding for research and development in artificial intelligence and machine learning methods to handle data and operations at DOE scientific user facilities.
