市場調查報告書
商品編碼
1372042
全球機密運算市場,到 2030 年的預測:按組件、部署模式、應用程式、最終用戶和地區進行的全球分析Confidential Computing Market Forecasts to 2030 - Global Analysis By Component (Services, Hardware and Software),Deployment Mode (Cloud and On-premises), Application, End User and By Geography |
根據 Stratistics MRC 的數據,2023 年全球機密計算市場規模為 62.62 億美元,預計將以 24% 的年複合成長率成長,到 2030 年達到 282.27 億美元。
機密計算是一種可以在記憶體中處理加密資料以限制存取的概念,以確保資料在使用時受到保護。機密運算可確保寶貴的智慧財產權得到適當保護,免受惡意行為者和內部威脅。它只能由那些為了提供特權存取程式碼而專門授權的人進行存取。
據 Informatica 稱,2019 年發生了 5,000 多起資料外洩事件,洩露了 80 億筆記錄。
資料隱私法規,例如《一般資料保護規範》(GDPR) 和《加州消費者隱私法案》(CCPA),要求企業保護客戶資料。組織可以透過使用機密計算來遵守法規,這提供了安全且私密的處理環境。機密運算可以透過確保安全、保密地處理資料來幫助組織滿足這項需求。組織可以透過提供安全的處理環境和使用機密運算來保護商業機密免遭未經授權的個人存取或洩露,從而擴大市場。
部署和維護機密運算解決方案需要具備資料安全、密碼學和雲端運算知識的合格專業人員。僱用和留住此類專業人員的成本很高,並且需要定期培訓以保持他們的能力與時俱進。此外,現有的IT基礎設施必須與敏感的運算解決方案相鏈接,這既耗時又昂貴。這需要從頭開始創建新的系統和應用程式,或修改現有系統和應用程式以使用安全計算解決方案。這些因素正在阻礙市場成長。
隨著人工智慧 (AI) 應用的激增,對有助於保護 AI 模型和資料隱私的解決方案的需求不斷成長。為了保護敏感的人工智慧資料,敏感的人工智慧解決方案使用安全隔離區和同態加密技術。 AI 模型通常使用包含個人識別資訊(PII) 和商業機密等敏感資料的大型資料進行訓練。預計這將在預期期間推動市場成長。
部署和維護機密運算需要特定的專業知識和技能,這使得一些公司和組織難以進入機密運算市場,尤其是IT資源較少的小型公司。造成這種情況的原因之一是,機密計算背後的技術相對較新且不斷發展。此外,敏感運算解決方案通常需要整合到目前的IT基礎設施中,這可能很困難。需要進行密集的測試和調試,以確保解決方案按計劃工作並且不會引入新的漏洞或相容性問題。
COVID-19大流行和遠距工作的興起使企業營運變得更加困難。 COVID-19 對近期經濟衰退的影響凸顯了對替代商業方法的需求。企業主現在必須擁抱雲端運算並將其資料倉儲遷移到雲端。然而,這可能有助於企業在短期內維持穩定的商業環境,同時實現長期成長和擴張。由於提高可用性、減少延遲、可擴充性和企業級安全性等優點,資料倉儲服務被各行各業的公司採用。
預計服務業將成為預測期內最大的領域。敏感運算系統的安裝、部署和維護很大程度上依賴於服務。他們提供知識、支援和專業服務,幫助企業部署和利用敏感運算技術。採用機密計算的組織可能會受益於諮詢和顧問服務,幫助他們認知到這樣做的好處、風險和影響。我們還提供有關在實施機密運算時選擇正確的技術、建立安全架構和製定安全策略的建議。服務可協助企業創建安全運算解決方案並將其整合到其當前的系統和軟體中。
資料安全領域預計在預測期內年複合成長率最高。使用專用硬體基礎設施為資料處理和機密運算提供安全且隔離的環境。該基礎設施包括基於硬體的安全功能、安全隔離區、可信任執行環境等。為了提供客戶可靠、安全的運算環境,雲端服務供應商和資料中心正在投資私有運算基礎設施。此外,隨著雲端運算和分散式運算系統的普及,維護資料安全變得越來越困難。引入機密計算來解決這些問題。機密運算使資料所有者能夠委託其資料,從而降低與外包資料相關的風險,即使資料是在外部環境中處理的。
預計北美將在整個預測期內佔據最大佔有率。這是機密運算採用率最高的市場,受到多種因素的推動,包括有利的IT基礎設施、大量組織的存在以及技術人才的可用性。秘密運算的採用也受到 Fed RAMP 等法律要求的影響,該法律要求應用定義的方法對雲端產品和服務進行安全評估、授權和持續監控。此外,隨著資料隱私和安全要求隨著技術進步而增加,需求也在增加。為了保護敏感資料並遵守資料保護法,美國多家公司正在實施機密運算。主要採用者來自金融、醫療保健、政府和科技部門。
預計亞太地區在預測期內複合年複合成長率最高。在亞太地區,對雲端驅動和支援雲端的雲端資料倉儲的需求不斷增加,導致各行業的支出增加和技術突破。在亞太地區,製造業是最大的產業,其次是零售、電子商務和 BFSI。為了保持市場競爭力,必須迅速解決這些挑戰。該地區的公司繼續專注於增強客戶服務,以獲得競爭優勢和收益成長。
According to Stratistics MRC, the Global Confidential Computing Market is accounted for $6.262 billion in 2023 and is expected to reach $28.227 billion by 2030 growing at a CAGR of 24% during the forecast period. Confidential computing is a concept in which encrypted data can be processed in memory to limit access to ensure data in use is protected. Confidential computing ensures that valuable intellectual property is properly protected from malicious and insider threats. This is only accessible to specially authorized for the purpose of providing privileged access programming code.
According to Informatica, in 2019, the company noted over 5,000 data breaches with 8 billion records exposed.
Data privacy regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) require businesses to protect their customers' data. Organisations can comply with the regulations through the use of confidential computing, which offers a safe and private processing environment. By ensuring that data is processed safely and confidentially, confidential computing can assist organisations in meeting this need. Organisations can safeguard their trade secrets from being accessed or compromised by unauthorised individuals by using confidential computing, which offers a secure processing environment and leads to market expansion.
Implementing and maintaining confidential computing solutions requires qualified experts with knowledge of data security, cryptography, and cloud computing. Such specialists can be expensive to hire and maintain, and they need regular training to keep their abilities current. Additionally, the existing IT infrastructure must be linked with confidential computing solutions, which can be time-consuming and expensive. This may entail creating new systems and apps from scratch or modifying already-existing ones to work with secure computing solutions. These factors hamper market growth.
A rising need exists for solutions that can aid in preserving the privacy of AI models and data as the number of artificial intelligence (AI) applications increases. Secure enclaves and homomorphic encryption techniques are used by confidential AI solutions to safeguard sensitive AI data. AI models are frequently trained using sizable datasets, including sensitive data such as personally identifiable information (PII) or secret corporate secrets. Over the course of the anticipated period, this is expected to fuel the market's growth.
It is challenging for some firms and organizations, especially smaller ones with fewer IT resources, to crack the confidential computing market since it requires specific expertise and skills to deploy and maintain. There are many causes, one of which is the fact that the technology underlying secret computing is relatively young and continually developing. Additionally, integrating confidential computing solutions into the current IT infrastructure is frequently required, which can be difficult. To make sure the solution works as planned and does not create additional vulnerabilities or compatibility problems, intensive testing and debugging are needed.
The COVID-19 pandemic and the rise of remote work settings have rendered it more challenging for companies to operate. The influence of COVID-19 on the recent economic recession highlights the necessity for alternative business methods. Business owners now need to embrace cloud computing and move their data warehouses to the cloud. However, this will assist firms in maintaining a stable business environment in the short term while aiming for long-term growth and expansion. Data warehouse services are employed by businesses in a wide range of industries due to their improved availability, reduced latency, scalability, and enterprise-grade security, among other benefits.
The services segment is anticipated to be the largest during the projected period. The implementation, deployment, and maintenance of confidential computing systems depend significantly on services. To assist enterprises in implementing and utilizing confidential computing technology, they offer knowledge, support, and specialized services. Organizations which employ confidential computing might benefit from consulting and advisory services that assist them recognize the advantages, dangers, and effects of doing so. Moreover, for implementations of confidential computing, they offer advice on choosing the appropriate technology, creating safe architectures, and establishing security policies. Services help firms create and incorporate secure computing solutions into their current systems and software.
The data security segment is anticipated to have highest CAGR during the forecast period. Secure and isolated environments are offered for data processing via confidential computing with the use of specialized hardware infrastructure. This infrastructure includes hardware-based security features, secure enclaves, and trusted execution environments. To provide their clients with reliable and safe computing environments, cloud service providers and data centers are investing in private computing infrastructure. Moreover, data security is becoming increasingly challenging to maintain as cloud computing and distributed computing systems become more popular. These issues are addressed by confidential computing, which reduces the risks associated with outsourcing data by enabling data owners to keep control over their data even when it is processed in external environments.
North America is projected to have largest share throughout the extrapolated period. It is the most developed market in terms of the adoption of secret computing, driven by a variety of circumstances, including beneficial IT infrastructure, the presence of many organizations, and the availability of technical talents. Confidential computing adoption is also influenced by legal requirements like Fed RAMP, which applies a defined methodology to security evaluation, authorization, and continuous monitoring for cloud products and services. Additionally, it is growing in demand as data privacy and security requirements grow along with technological improvements. To safeguard sensitive data and adhere to data protection laws, several US firms are implementing confidential computing. Leading adopters consist of the financial, healthcare, government, and technology sectors.
The Asia Pacific region is estimated to witness highest CAGR throughout the projected period. The Asia Pacific region is experiencing a rise in demand for cloud-driven and cloud-supported cloud data warehouses, which has led to higher expenditures and technological breakthroughs in a variety of industries. In the APAC area, manufacturing is the largest industry vertical, followed by retail, e-commerce, and BFSI. Lower operational costs and higher productivity have grown to be major challenges for local manufacturers as a result of global competition; these issues must be swiftly resolved in order to maintain market competitiveness. For competitive advantage and revenue growth, businesses in this region continue to put their attention on enhancing customer service.
Some of the key players in Confidential Computing Market include: AMD (Advanced Micro Devices), Anjuna Security, Amazon Web Services, Decentriq AG, Arm Holdings, Google LLC, Huawei Technologies Co., Ltd., Fortanix, Microsoft Corporation, OVHcloud, Swisscom, Intel Corporation, Super Protocol, R3, IBM Corporation and Alibaba Cloud.
In May 2023, Intel announced the release of a new security-as-a-service solution called Project Amber. The solution is an independent trust authority, designed to remotely verify whether a compute asset in the cloud, network's edge or on-premises environment is trustworthy.
In April 2023, Microsoft announced the expansion of its confidential VM family with the launch of the DCesv5-series and ECesv5-series in preview. Featuring 4th Gen Intel Xeon Scalable processors, these VMs are backed by an all-new hardware-based Trusted Execution Environment called Intel Trust Domain Extensions (TDX). Organizations can use these VMs to seamlessly bring confidential workloads to the cloud without any code changes to their applications.
In April 2023, Google and Intel collaborated on a new research project to identify potential security vulnerabilities in Intel's new confidential computing technology, Intel Trust Domain Extensions (Intel TDX). In addition to an expanded feature set, Intel Tdx offers full vm compute models without requiring any code changes.