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.
To address this current losing war with cyberattackers, the future of cybersecurity requires augmenting the current focus of “indicators of compromise” with “indicators of exposure & warning” in real-time. Where the measure would be to gauge the shift of incident management that would tilt on managing more incidents at warning stages than on compromise stages. It is imperative to build an AI engine to perform this very task as that would be the only way to perform in real-time, scale with the growing nature of cloud as well as to cover the evolving nature to attack scenarios.
Deloitte’s third edition of the “State of AI in the Enterprise” survey finds businesses are entering a new chapter in AI implementation where early adopters may have to work harder to preserve an edge over their industry peers.
Artificial Intelligence (AI) has gone mainstream when it comes to customer interactions, according to a new report from the Capgemini Research Institute.
