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Software Defined Security Market Is Expected to Reach $68 83 Billion by 2030, Claims AMR

Software Defined Security Market Is Expected to Reach $68 83 Billion by 2030, Claims AMR
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CSP Inc Reports Fiscal 2021 Second Quarter Results; Sixth Consecutive Quarter of Year-Over-Year Gross Margin Improvement

CSP Inc. Reports Fiscal 2021 Second Quarter Results; Sixth Consecutive Quarter of Year-Over-Year Gross Margin Improvement Proactive Customer Engagement and Maintenance of Organizational Infrastructure During Pandemic Leads to Emerging Revenue Opportunities and Increased Profitability LOWELL, Mass., May 11, 2021 (GLOBE NEWSWIRE) CSP Inc. (NASDAQ: CSPI), an award-winning provider of security and packet capture products, managed IT and professional services and technology solutions, reported financial and operating results for the fiscal 2021 second quarter and provided a business update. Second Quarter Operating Highlights and Recent Achievements Continued positive impact of a favorable revenue mix led to a gross margin improvement of 4.0 percentage points compared to the year-ago fiscal second quarter.

ARIA Cybersecurity to Leverage NVIDIA Morpheus Framework for Cyber Attack Detection Applications

ARIA Cybersecurity to Leverage NVIDIA Morpheus Framework for Cyber Attack Detection Applications Brings advanced data center and cybersecurity services to the edge cloud BOSTON, April 27, 2021 (GLOBE NEWSWIRE) ARIA Cybersecurity Solutions, a CSPi business (NASDAQ: CSPi) that delivers a software-defined approach for improved cyber-attack incident detection and response, announced today it will be using the NVIDIA Morpheus cybersecurity application framework to develop ARIA Software Defined Security (SDS) applications. The Morpheus framework combined with NVIDIA BlueField DPUs provides a powerful platform to support data-intensive applications and provide value-added cybersecurity services to edge cloud and 5G network build-outs. For effective cyber-attack detection and automated remediation, such applications require AI-driven ML processes run against real-time network traffic analytics.

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