정교한 사이버 공격 증가와 IT 환경의 복잡화 기업이 진보된 지속적 위협, 랜섬웨어 공격, 내부 위협 등을 다루는 동안 UEBA 솔루션은 이상 및 잠재적 침해를 감지하기 위해 동적 패턴을 연구함으로써 가시성과 통찰력을 향상시킵니다.
게다가 인공지능(AI)과 머신러닝(ML)을 UEBA 시스템에 통합함으로써 위협의 검출과 대응에 있어서의 정확성과 유효성이 높아집니다. 기업은 첨단 보안 솔루션에 대한 투자를 강요받아 업계 전체의 UEBA 수요가 확대되어 2024년부터 2031년에 걸쳐 CAGR 약 40.50%로 성장할 전망입니다.
사용자 및 엔티티 행동 분석(UEBA) 시장 : 정의/개요
UEBA(User and Entity Behavior Analytics)는 조직의 정보 기술 환경에서 사용자 및 엔티티의 행동을 모니터링하고 평가하기 위해 고급 분석 및 머신러닝 기술을 적용하는 것입니다. 내부 위협, 침해된 계정, 고급 지속적 위협 등 잠재적인 보안 위협을 감지하는 데 도움이 됩니다. 사고 대응 개선, 사이버 보안 태세의 전반적인 강화 등이 있습니다. 기업이 사이버 보안 및 규제 규정 준수를 선호하는 동안 UEBA는 실용적인 통찰력을 제공하고 변화하는 사이버 위협으로부터 보호하는 데 중요한 역할을 할 것입니다.
인공지능(AI)과 머신러닝(ML)의 활용 확대는 사용자 및 엔티티 행동분석(UEBA) 시장을 추진하고 있습니다. 이러한 방식으로 UEBA 솔루션의 능력을 향상시킵니다. 그러므로 기업은 사이버 보안의 방어를 강화하고 첨단 사이버 위협을 감지하고 대응하기 위해 AI와 ML을 활용한 UEBA 솔루션에 대한 의존도를 강화하고 있습니다.
2024년 5월, 데이터 분석으로 유명한 Splunk는 회사의 UEBA 플랫폼에 강력한 머신러닝 알고리즘을 통합하는 것을 발표했습니다. 실시간으로 평가함으로써 위협 감지의 정확성과 속도를 높이려고 합니다.
또한 사이버 보안 운영의 확장성과 자동화 요구 사항은 UEBA에서 AI와 머신러닝의 활용을 뒷받침하고 있습니다. AI와 ML 기술은 방대한 양의 데이터를 관리하고 위협 감지 업무를 자동화하는 데 필요한 확장성을 가능하게합니다.
구현 복잡성은 사용자 및 엔티티 행동 분석(UEBA) 업계의 성장을 방해할 수 있는 중요한 요소입니다. 기술을 기존 IT 인프라에 통합해야 하는데, 이는 어려우며 리소스 집계 적인 프로세스가 될 수 있습니다. 올바른 행동 통찰력을 얻기 위해서는 조직이 데이터를 확실하게 얻고, 표준화하고, 효과적으로 분석해야 합니다. 조직이 UEBA 솔루션의 도입을 망설이고 시장 전체의 성장을 지연시킬 수 있습니다.
또한 보안 정보 및 이벤트 관리(SIEM) 플랫폼과 같은 다른 보안 시스템과 UEBA를 통합하면 추가 문제를 일으킬 수 있습니다. 고급 기술 지식과 지속적인 유지 보수가 필요합니다. 스템 및 기타 보안 용도과 잘 작동하도록 UEBA를 설정하는 것은 어렵고 통합 문제와 운영 비용을 증가시킬 수 있습니다. 특히 사내에 필요한 지식이 없는 경우에는 UEBA 솔루션에 대한 투자를 떠올릴 수 있습니다.
게다가 사이버 위협의 끊임없는 진화로 인해 UEBA 시스템을 성공시키기 위해서는 항상 적응하고 개선할 필요가 있습니다. 특히 사이버 보안 전문 팀이 없는 조직에서는 이러한 요구에 대응하기 위해 고생할 수 있습니다.
The rise of sophisticated cyber-attacks and the increasing complexity of IT environments. As enterprises deal with sophisticated persistent threats, ransomware attacks, and insider threats, UEBA solutions provide increased visibility and insights by studying behavioral patterns to detect anomalies and potential breaches growth surpassing USD 1035.54 Million in 2024 and reachingUSD 11215.59 Million by 2031.
Furthermore, integrating artificial intelligence (AI) and machine learning (ML) into UEBA systems increases their accuracy and efficacy in detecting and responding to threats. Furthermore, increasing legal requirements for data protection and cybersecurity force organizations to invest in advanced security solutions, driving up demand for UEBA across industries expansion is expected to grow at aCAGR of about 40.50% from 2024 to 2031.
User and Entity Behavior Analytics Market: Definition/ Overview
User and Entity Behavior Analytics (UEBA) is the application of advanced analytics and machine learning techniques to monitor and evaluate the behavior of users and entities in an organization's information technology environment. UEBA aids in the detection of potential security threats such as insider threats, compromised accounts, and advanced persistent threats by establishing baselines of typical activity and identifying deviations from them. Its applications include improved threat detection, better incident response, and a stronger overall cybersecurity posture. The future of UEBA seems optimistic, with predicted advances in AI and machine learning leading to more complex and accurate threat detection capabilities. As firms prioritize cybersecurity and regulatory compliance, UEBA will play an important role in providing actionable insights and protecting against changing cyber threats.
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The growing use of artificial intelligence (AI) and machine learning (ML) is propelling the user and entity behavior analytics (UEBA) market. AI and machine learning technologies improve UEBA solutions' capabilities by allowing for more accurate and efficient analysis of large amounts of data. These technologies allow for the detection of small behavioral anomalies and trends that could suggest possible security vulnerabilities, such as insider threats, compromised accounts, and advanced persistent threats. As a result, enterprises are increasingly relying on AI and ML-powered UEBA solutions to bolster their cybersecurity defenses and detect and respond to advanced cyber threats.
In May 2024, Splunk, a renowned data analytics company, announced the inclusion of powerful machine learning algorithms into its UEBA platform. This integration seeks to increase threat detection accuracy and speed by using machine learning models to assess user and object behavior in real time. These improvements show how AI and ML are revolutionizing UEBA systems, making them more effective at detecting and mitigating emerging cyber threats.
Furthermore, the requirement for scalability and automation in cybersecurity operations drives the use of AI and machine learning in UEBA. As firms expand and their IT environments get increasingly sophisticated, manual monitoring and analysis of user behavior becomes impossible. AI and ML technologies enable the scalability needed to manage enormous amounts of data and automate threat detection operations.
The increasing complexity of implementation is a significant factor that may impede the growth of the user and entity behavior analytics (UEBA) industry. Implementing UEBA solutions entails integrating new technologies such as artificial intelligence (AI) and machine learning (ML) with existing IT infrastructure, which can be a difficult and resource-intensive process. To obtain correct behavioral insights, organizations must ensure that their data is captured, standardized, and analyzed effectively. This complexity may dissuade smaller organizations with fewer IT resources from implementing UEBA solutions, delaying overall market growth.
Furthermore, integrating UEBA with other security systems, such as Security Information and Event Management (SIEM) platforms, may provide additional issues. Ensuring seamless compatibility between various security measures necessitates a high level of technical knowledge and continual maintenance. For instance, configuring UEBA to function successfully with existing SIEM systems and other security applications might be difficult, resulting in integration challenges and higher operational expenses. This complexity can lead to lengthier implementation timelines and dissuade firms from investing in UEBA solutions, especially if they lack the required in-house knowledge.
Furthermore, the continual evolution of cyber threats necessitates that UEBA systems constantly adapt and improve to be successful. This needs constant updates and fine-tuning of AI and ML models, adding complexity to the implementation and maintenance processes. Organizations may struggle to keep up with these demands, particularly if they do not have dedicated cybersecurity teams.
The growing demand for comprehensive software platforms is a key driver of the user and entity behavior analytics (UEBA) industry. Organizations are increasingly looking for integrated solutions that include advanced threat detection and response capabilities on a single platform. These sophisticated software solutions integrate a variety of security technologies, including machine learning, behavioral analytics, and real-time monitoring, to provide a full picture of potential risks. The need for a unified approach to cybersecurity grows as cyber threats become more complex, prompting organizations to invest in UEBA solutions that can seamlessly integrate with their existing security infrastructure while providing robust protection against sophisticated attacks.
Furthermore, the growing volume of data generated by modern IT settings needs powerful analytics and automation capabilities, which comprehensive UEBA solutions can deliver. These platforms use artificial intelligence (AI) and machine learning (ML) to process and analyze enormous datasets in real time, looking for patterns and abnormalities that could indicate malicious behavior.
Scalability and ease of management are further motivators for the adoption of complete software systems. As businesses grow and their IT infrastructures get more sophisticated, managing several independent security systems becomes more difficult. Comprehensive UEBA solutions make this easier by providing a consolidated solution that unifies several security activities, lowering administrative burdens and increasing operational efficiency. For instance, in July 2024, Microsoft announced the merging of Azure Sentinel with UEBA capabilities, resulting in a unified security management system that scales with an organization's requirements. This integration enables enterprises to streamline their security operations, making it easier to manage and respond to threats in big, distributed systems.
The services category, on the other hand, is expanding at the highest rate, owing to the growing demand for specialist assistance in establishing, administering, and optimizing UEBA systems. Organizations need expert help to efficiently implement these complex solutions and continuously improve their security posture, resulting in a significant increase of the services industry.
The increasing use of on-premises solutions is driving the growth of the user and entity behavior analytics (UEBA) industry. Large corporations and organizations in highly regulated areas like finance, healthcare, and government prefer on-premises implementation since data security and compliance are critical. These firms prefer on-premises solutions because they provide direct control over their data and security infrastructure, ensuring compliance with demanding regulatory standards and lowering the risk of data breaches. The demand for on-premises UEBA solutions is driving market expansion, as businesses want to use advanced analytics and behavioral insights while maintaining complete data sovereignty.
The growing complexity of cyber threats, as well as the necessity for comprehensive security measures, are contributing to an increase in demand for on-premises UEBA solutions. As cyberattacks get increasingly complex, organizations must use advanced analytics and real-time monitoring to successfully identify and neutralize risks. On-premises UEBA systems provide the performance and dependability required to process huge amounts of security data and give actionable insights quickly. The ability to maintain tight control over security infrastructure and data enables enterprises to ensure that their UEBA systems are always up to date and capable of guarding against emerging threats. The growing demand for advanced, dependable, and configurable security solutions is driving the growth of the UEBA market through greater use of on-premises deployments.
The cloud-based category, on the other hand, is expanding at a rapid pace, thanks to its flexibility, scalability, and low cost. The growing adoption of cloud technologies, as well as the demand for remote monitoring and control of security analytics, are driving the rapid expansion of cloud-based UEBA solutions, particularly among small to medium-sized enterprises and companies with hybrid or totally remote workforces.
Country/Region-wise
The robust technical infrastructure in North America is a major driver of the user and entity behavior analytics (UEBA) market. The region has a strong IT ecosystem, defined by widespread use of cutting-edge technologies like artificial intelligence (AI) and machine learning (ML). This architecture enables the integration and deployment of advanced UEBA solutions that employ AI and ML to monitor user and entity activity patterns and detect possible security issues. Organizations in North America are increasingly investing in UEBA to strengthen their cybersecurity posture, threat detection capabilities, and risk mitigation for complex cyber-attacks.
North America is committed to improving its cybersecurity infrastructure. For instance, in June 2024, IBM announced a significant expansion of its cybersecurity offerings, which included improvements to its QRadar UEBA platform. This expansion underscores the company's commitment to integrate sophisticated analytics and AI-powered insights to better threat identification and response. Such investments by large technology companies highlight the significance of strong technological infrastructure in driving the adoption and expansion of UEBA solutions in the region.
Furthermore, the growing regulatory requirements for data protection and cybersecurity in North America are driving up demand for UEBA solutions. Companies must implement advanced security solutions to comply with rules like GDPR and CCPA, which need robust threat detection and response capabilities. The ongoing transformation of North America's technical landscape, combined with strong regulatory requirements, is projected to fuel the region's UEBA market expansion, confirming its position as a worldwide cybersecurity leader.
The rising cybersecurity concerns in the Asia-Pacific region are driving the user and entity behavior analytics (UEBA) market. As digital transformation increases across the region's various industries, there is an increase in cyber-attacks on sensitive information and key infrastructure. The rise of sophisticated cyber dangers, such as advanced persistent threats (APTs) and ransomware assaults, is prompting enterprises to implement advanced security solutions like UEBA. These solutions leverage AI and machine learning to evaluate user and entity activity, detect anomalies, and respond to possible threats in real time, increasing the region's overall cybersecurity resilience.
The Asia-Pacific region is increasingly focused on addressing cybersecurity risks. In July 2024, Cisco announced a strategic collaboration with a prominent cybersecurity business to strengthen its SecureX platform with sophisticated UEBA capabilities. This alliance intends to address rising cyber threats in Asia-Pacific by combining behavioral analytics with Cisco security solutions. Such activities underscore the critical need for sophisticated threat detection and response systems, which is driving the adoption of UEBA solutions throughout the area.
Furthermore, legal concerns and the rising complexity of cyber threats are driving up demand for UEBA solutions in Asia Pacific. Governments and regulatory bodies are enacting stronger data protection laws and cybersecurity rules, requiring businesses to invest in advanced security systems. For instance, in August 2024, the Australian government issued new legislation mandating firms to improve their cybersecurity defences. This regulatory shift, combined with a developing threat landscape, is hastening the adoption of UEBA solutions in Asia-Pacific, as businesses strive to increase threat detection capabilities and maintain compliance with changing security standards.
The competitive landscape of the user and entity behavior analytics (UEBA) market is characterized by a dynamic environment with a mix of emerging players and established technology vendors. The market is driven by increasing cybersecurity threats and the need for advanced threat detection and response capabilities. Companies are leveraging advancements in artificial intelligence (AI) and machine learning (ML) to enhance the accuracy and efficiency of their UEBA solutions. Additionally, there is a growing emphasis on integrating UEBA with other security information and event management (SIEM) systems and broader security frameworks to offer more comprehensive threat intelligence and analysis. This integration facilitates better detection of sophisticated attacks and insider threats, contributing to the evolving competitive dynamics of the market.
Some of the prominent players operating in the user and entity behavior analytics market include:
Splunk, Inc.
IBM Security (QRadar SIEM with UEBA module)
Palo Alto Networks
MacAfee
Fortinet
In January 2024, Exabeam, a cybersecurity startup that specializes in UEBA, has introduced "Exabeam IoT Sentinel," the industry's first UEBA solution intended exclusively for Internet of Things (IoT) devices. This revolutionary tool employs machine learning algorithms to build baseline behavior patterns for diverse IoT devices and detect anomalies that may indicate security breaches or device compromise. The solution addresses the growing security risks associated with the proliferation of IoT devices in business networks. Exabeam IoT Sentinel connects with the company's existing UEBA technology, allowing for a comprehensive picture of both user and device behavior.
In December 2023, BASF, a multinational chemical business, and Terramera, an agricultural technology company specializing in computational chemistry, have launched a research collaboration aimed at understanding the molecular mechanisms of humic compounds in plant growth promotion. The cooperation intends to employ Terramera's computational biology platform to find the most effective humic chemicals and enhance their formulations.