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Accelerating the pace of machine learning

Machine learning happens a lot like erosion. Data is hurled at a mathematical model like grains of sand skittering across a rocky landscape. Some of those grains simply sail along with little or no impact. But some of them make their mark: testing, hardening, and ultimately reshaping the landscape according to inherent patterns and fluctuations that emerge over time. Effective? Yes. Efficient? Not so much. Researchers are now seeking to bring efficiency to distributed learning techniques emerging as crucial to modern artificial intelligence (AI) and machine learning (ML). In essence, the goal is to hurl far fewer grains of data without degrading the overall impact.
http://news.poseidon-us.com/SQdVsN

Coffee Talk: Why Hybrid Cloud and Why Now?

Competitiveness requires agility, the ability to pivot instantly and effortlessly whenever business opportunity presents itself. Nothing supports agility better than hybrid environments. In this Coffee Talk session, Senior Resultant Howard M. Cohen discusses what a natural development hybrid cloud solutions really are, and how to strategically design best solutions with logical combinations.
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AI contracts have special licensing needs to prevent bias, encourage transparency

Data requirements to ensure lack of bias in AI and transparency and how it works are not part of the standard license agreements.
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Trilio Continuous Restore enhances recovery times for cloud-native applications

Trilio announced a technical preview of a new “Continuous Restore” capability. Continuous Restore offers faster levels of replication, restoration and migration of data and metadata from any storage or cloud platform to another, improving recovery times for cloud-native applications. Entirely storage-, cloud- and distribution-agnostic, Trilio’s “Continuous Restore” capability will enable users to continuously stage data at multiple and heterogeneous clouds. This means that applications—regardless of where they reside—will be able to tap into that data … More → The post Trilio Continuous Restore enhances recovery times for cloud-native applications appeared first on Help Net Security.
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Keyfactor collaborates with Fortanix to improve machine identity protection for organizations

Keyfactor announced a technology integration with Fortanix, allowing leading enterprises and managed service providers to effectively manage all machine identities across hybrid and multi-cloud infrastructure while reducing complexity in ensuring sensitive private keys remain protected. “The use of public key infrastructure (PKI) and certificates to securely authenticate digital identities has grown exponentially with accelerated cloud transformation,” said BJ Ferguson, VP of Channel, North America, Keyfactor. “Managing a growing number of keys and certificates across multiple … More → The post Keyfactor collaborates with Fortanix to improve machine identity protection for organizations appeared first on Help Net Security.
http://news.poseidon-us.com/SQYxtP

BrandPost: DDos Extortion Takes VoIP Providers Offline

Threat actors are continually innovating and rethinking their attack patterns – as well as who they target with attacks. This is clearly seen in their targeting of  Voice over Internet Protocol (VoIP) providers, as highlighted in NETSCOUT’s 2H 2021 Threat Report. Why target VoIP providers? The short answer is financial gain. Attackers know bringing down VoIP providers that service a large number of customers causes a lot of pain and therefore is ripe for extortion. Cyber attackers launched three worldwide distributed denial-of-service (DDoS) extortion attack campaigns in 2021 – a startling new achievement carried out by a REvil copycat, Lazarus Bear Armada (LBA), and Fancy Lazarus. But threat actors did more than simply increase such global attacks. To read this article in full, please click here
http://news.poseidon-us.com/SQXjcj

ISC Stormcast For Tuesday, May 17th, 2022 https://isc.sans.edu/podcastdetail.html?id=8010, (Tue, May 17th)

(c) SANS Internet Storm Center. https://isc.sans.edu Creative Commons Attribution-Noncommercial 3.0 United States License.
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