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市場調查報告書
商品編碼
1841557
網路安全防火牆市場-全球產業規模、佔有率、趨勢、機會和預測(按組件、類型、最終用戶產業、地區和競爭細分,2020-2030 年預測)Network Security Firewall Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Type, By End-User Industry, By Region & Competition, 2020-2030F |
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2024 年全球網路安全防火牆市場價值為 68.8 億美元,預計到 2030 年將達到 162.8 億美元,預測期內複合年成長率為 15.26%。
| 市場概況 | |
|---|---|
| 預測期 | 2026-2030 |
| 2024年市場規模 | 68.8億美元 |
| 2030年市場規模 | 162.8億美元 |
| 2025-2030年複合年成長率 | 15.26% |
| 成長最快的領域 | 包過濾防火牆 |
| 最大的市場 | 北美洲 |
網路安全防火牆市場是指軟體產業的一個專業領域,提供旨在簡化電池設計、模擬、建模、測試和製造端到端流程的數位化工具和平台。這些軟體解決方案有助於精確建立電池虛擬原型,使工程師和研究人員能夠最佳化電池性能、改進材料選擇、改善熱管理,並確保在開始實際生產之前符合行業標準。該軟體還支援電池組組裝、生命週期分析和品質控制的自動化,從而顯著縮短開發週期和降低成本。隨著電動車、消費性電子、再生能源和航太等產業越來越依賴先進的儲能系統,對精確且可擴展的電池設計能力的需求也日益成長。由於全球碳中和監管要求以及消費者對永續交通日益成長的偏好推動電動車普及率激增,預計該市場將大幅成長。各國政府和私人企業正在大力投資電池超級工廠和儲能基礎設施,這增加了對設計軟體的需求,以確保快速創新和生產效率。此外,固態電池和鋰矽技術等電池化學技術的進步,催生了對適應性強、面向未來的軟體平台的需求,這些平台能夠模擬複雜的電化學行為。人工智慧和機器學習的融合也實現了預測建模、故障診斷和即時資料分析,從而提升了電池系統的可靠性和性能。此外,軟體供應商和電池製造商之間的合作正在推動針對特定行業需求的客製化解決方案的開發。永續性、能源效率和創新是未來出行和電力系統的核心,網路安全防火牆市場可望強勁擴張。數位工程工具的整合、向電動車的轉型以及全球對透過更智慧的能源解決方案實現脫碳的重視,都將推動網路安全防火牆市場的崛起。
網路威脅情勢不斷升級
網路威脅日益複雜
防火牆系統中人工智慧和機器學習的整合
The Global Network Security Firewall Market was valued at USD 6.88 billion in 2024 and is expected to reach USD 16.28 billion by 2030 with a CAGR of 15.26% during the forecast period.
| Market Overview | |
|---|---|
| Forecast Period | 2026-2030 |
| Market Size 2024 | USD 6.88 Billion |
| Market Size 2030 | USD 16.28 Billion |
| CAGR 2025-2030 | 15.26% |
| Fastest Growing Segment | Packet Filtering Firewall |
| Largest Market | North America |
The Network Security Firewall Market refers to the specialized segment of the software industry that offers digital tools and platforms designed to streamline the end-to-end processes of battery design, simulation, modeling, testing, and manufacturing. These software solutions facilitate the accurate virtual prototyping of batteries, enabling engineers and researchers to optimize battery performance, enhance material selection, improve thermal management, and ensure compliance with industry standards before initiating physical production. The software also supports automation of battery pack assembly, lifecycle analysis, and quality control, significantly reducing development cycles and costs. As industries such as electric vehicles, consumer electronics, renewable energy, and aerospace increasingly rely on advanced energy storage systems, the need for precise and scalable battery design capabilities is intensifying. This market is expected to witness substantial growth due to the surge in electric vehicle adoption driven by global regulatory mandates for carbon neutrality and growing consumer preference for sustainable transportation. Governments and private sector companies are heavily investing in battery gigafactories and energy storage infrastructure, which is increasing the demand for design software to ensure rapid innovation and production efficiency. Furthermore, advancements in battery chemistries like solid-state batteries and lithium-silicon technologies are creating the need for adaptable and future-ready software platforms that can simulate complex electrochemical behaviors. Integration with Artificial Intelligence and Machine Learning is also enabling predictive modeling, fault diagnostics, and real-time data analytics, enhancing the reliability and performance of battery systems. Additionally, collaborations between software providers and battery manufacturers are leading to the development of customized solutions tailored to specific industrial requirements. With sustainability, energy efficiency, and innovation at the core of future mobility and power systems, the Network Security Firewall Market is poised for strong expansion. Its rise will be driven by the convergence of digital engineering tools, the transition to electric mobility, and the global emphasis on decarbonization through smarter energy solutions.
Key Market Drivers
Escalating Cyber Threat Landscape
The Network Security Firewall Market is experiencing robust growth due to the escalating sophistication and frequency of cyber threats targeting organizations across industries. Advanced persistent threats (APTs), ransomware, phishing, and distributed denial-of-service (DDoS) attacks are increasingly exploiting vulnerabilities in network infrastructures, necessitating robust firewall solutions to protect sensitive data and ensure business continuity. Modern firewalls, equipped with features like intrusion prevention systems (IPS), deep packet inspection, and artificial intelligence-driven threat detection, provide real-time monitoring and mitigation of complex attacks.
As businesses expand their digital footprints through cloud adoption, remote work, and IoT integration, the attack surface widens, amplifying the need for next-generation firewalls (NGFWs) that can secure diverse network environments. This driver is critical in industries such as finance, healthcare, and retail, where data breaches can result in significant financial and reputational damage.
The rapid evolution of cybercriminal tactics, including zero-day exploits and AI-powered attacks, compels organizations to invest in advanced firewall technologies to safeguard critical assets. Additionally, the growing reliance on digital transformation initiatives underscores the importance of firewalls in maintaining secure network perimeters, driving demand for scalable, adaptive solutions that can address dynamic threat landscapes and ensure compliance with industry standards.
In 2025, global cyberattacks increased by 40%, with ransomware incidents rising by 30% compared to 2023. Over 4 billion records were exposed in data breaches in 2024. By 2027, 80% of enterprises are projected to adopt next-generation firewalls, with cybersecurity spending expected to reach USD210 billion, reflecting a 25% annual increase in demand for advanced network security solutions to combat evolving threats.
Key Market Challenges
Increasing Sophistication of Cyber Threats
One of the most significant challenges confronting the Network Security Firewall Market is the rapid evolution and increasing sophistication of cyber threats. Cyber attackers are continually developing more advanced techniques such as polymorphic malware, zero-day exploits, and advanced persistent threats that can bypass traditional firewall defenses. These advanced attack vectors often remain undetected until significant damage has already occurred, challenging the efficacy of conventional network security infrastructures.
Moreover, threat actors are leveraging artificial intelligence and machine learning to automate and refine their attacks, making them more adaptive and harder to predict. This escalating complexity demands equally advanced firewall solutions capable of deep packet inspection, behavioral analytics, and real-time anomaly detection. However, developing and deploying such intelligent firewall systems require significant investment in research and development, highly skilled personnel, and continuous updates to threat databases.
Smaller enterprises, in particular, struggle to implement these advanced solutions due to budget constraints and lack of expertise. As a result, the gap between sophisticated threats and available defense mechanisms continues to widen, posing a formidable challenge to market growth.
Key Market Trends
Integration of Artificial Intelligence and Machine Learning in Firewall Systems
The integration of Artificial Intelligence and Machine Learning technologies into firewall systems is emerging as a significant trend within the Network Security Firewall Market. Traditional firewalls relied heavily on pre-configured rules and manual monitoring, which proved insufficient in identifying sophisticated threats and zero-day vulnerabilities. However, with Artificial Intelligence and Machine Learning capabilities, firewall solutions are now evolving to deliver intelligent, adaptive, and real-time threat detection and prevention. These technologies can analyze vast volumes of network traffic data to identify anomalies, classify potential threats, and proactively respond to evolving attack patterns without human intervention.
Machine Learning algorithms enable the development of predictive models that enhance the accuracy of intrusion detection systems by learning from historical data. As cybercriminals employ increasingly advanced tactics such as polymorphic malware and coordinated botnet attacks, firewalls equipped with Artificial Intelligence can provide an essential line of defense by identifying these behaviors early and mitigating risk more effectively. Furthermore, Artificial Intelligence can automate routine tasks such as threat classification, traffic analysis, and rule updates, reducing the administrative burden on cybersecurity teams and enhancing operational efficiency.
The growing demand for these intelligent firewalls is fueled by the rapid digitization of enterprises, proliferation of Internet of Things devices, and expanding cloud infrastructure. Organizations are increasingly recognizing the need for adaptive cybersecurity frameworks that go beyond static rule-based systems. Vendors in the Network Security Firewall Market are investing heavily in research and development to integrate Artificial Intelligence and Machine Learning into their offerings, thereby enhancing their competitive edge. As cyber threats become more dynamic and complex, the continued evolution of firewalls through Artificial Intelligence and Machine Learning integration is expected to reshape the competitive landscape and drive long-term growth within the Network Security Firewall Market.
In this report, the Global Network Security Firewall Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global Network Security Firewall Market.
Global Network Security Firewall Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: