
Get Visibility and Control Over Sensitive Data
Shine a light on dark data with extensive data discovery and highly accurate classification.
Forcepoint DSPM software scans any data source and uses proprietary AI Mesh technology to identify, categorize and remediate high-risk data.
It’s a perfect solution if your security teams struggle with:
Large amounts of shadow data
Over-permissioned data
GenAI data leakage risks
Unidentified data locations


Pinpoint Accuracy and Transparent Reporting
Enda Kyne, CTO at FBD Insurance, says that DSPM and DDR has been embraced by his IT security and data protection teams for their ability to control critical data and report activity to regulators.
Forcepoint DSPM Software Leads the Pack
Forcepoint is the only Data Security Posture Management vendor that uses AI Mesh technology to deliver highly accurate data classification. Read the full comparison chart to learn why organizations trust the leading data security provider to discover and catalogue data and remediate risk at scale.
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Forcepoint
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Forcepoint DSPM 솔루션과 경쟁 제품 비교
Forcepoint | 기존 공급업체 | 데이터 거버넌스 공급업체 | |
데이터 분류
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데이터 검색
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확장성
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분석 제품군:
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사건 분석
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사용자 지정 및 확장성
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위험 기반 접근 방식
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제품 비교는 2024년 5월 7일부터 동일한 공급업체에서 제공하는 제품 내 기능 및 교차 포트폴리오 통합을 기준으로 합니다. 타사 공급업체와의 통합은 비교 대상에서 제외됩니다. 기능 비교는 2024년 5월 7일부터 제공되는 각 공급업체의 최신 버전과 최신 버전을 기준으로 합니다. 2024년 5월 7일 기준으로 공개 웹 사이트 및 포럼, 분석 보고서, 제품 데이터시트 등에서 수집된 데이터를 기반으로 합니다.
Forcepoint DSPM이 최고 평가를 받은 보안 도구인 이유
데이터 가시성 향상
클라우드와 온프레미스 환경 모두에서 데이터에 대한 완전한 가시성을 확보하여 민감한 데이터를 어디서나 추적하고 관리합니다.

AI를 통한 검색 및 분류
매우 정확한 AI Mesh 기술을 활용하여 효율적이고 안정적인 데이터 검색 및 분류를 수행하여 오탐을 줄이고 사고 경보의 정확성을 향상시킵니다.

사전 예방적인 위험 개선
실행 가능한 인사이트를 통해 권한을 관리하고, 잘못된 위치된 데이터를 이동하며, 데이터 주권성, 데이터 액세스 및 중복 또는 ROT 문제를 해결할 수 있습니다.

규정 준수 관리 자동화
자동화를 통해 규정 준수 프로세스를 간소화하여 진화하는 규정에 대해 일관되고 지속적인 조정을 보장하여 수동적인 노력을 줄입니다.





Ability to integrate DLP, DSPM and DDR for data discovery, classification, protection and remediation.

Provides effective risk reporting, allowing you to see ROT (redundant, obsolete, trivial) data, over-permissioned data, data sovereignty issues and many others that make the overall data posture risky.

Offers visibility and control into data readiness for all GenAI applications. It is also able to secure Copilot and ChatGPT Enterprise usage.
What Real Customers Are Saying
What Real Customers Are Saying

"As part of Forcepoint’s broader data security ecosystem, DSPM has integrated seamlessly with our existing solutions. It’s an essential component of our overall data security strategy."
Indonesia Financial Group (IFG)


데이터가 위험에 노출되어 있나요?
데이터 위험 평가는 미분류 민감 파일, 과도한 권한을 가진 사용자와 같은 데이터 위협 요소를 선제적으로 발견합니다. Forcepoint의 무료 데이터 위험 평가를 통해 DSPM의 기능을 직접 체험해 보고 내 데이터가 얼마나 안전한지 확인해 보세요.
분석가가 추천합니다.
사용자가 인정합니다.
Forcepoint는 사용자와 업계 분석가들이 선정한 최고의 Data Loss Prevention 소프트웨어 및 데이터 보안 소프트웨어 공급업체 중 하나로 꾸준히 선정되었습니다.

Forcepoint가 IDC MarketScape: Worldwide DLP 2025 Vendor Assessment에서 리더로 선정되었습니다.

Forcepoint가 Frost & Sullivan에서 선정한 2024년 글로벌 DLP 올해의 기업 으로 2년 연속 선정되었습니다.
Forcepoint가 2025년 1분기 The Forrester Wave™: Data Security Platforms에서 우수 성과 를 거두는 기업으로 선정되었습니다.
Data Security Posture Management 모범 사례 구현
Frequently Asked Questions
What is Data Security Posture Management (DSPM)?
DSPM is a security solution that enables enterprises to discover and classify structured and unstructured data across file storage locations, such as cloud applications or on-premises. It also helps to proactively address incident remediation.
How do DSPM solutions work?
Structured and unstructured data is littered across Software-as-a-Service (SaaS) applications, Infrastructure-as-a-Service (IaaS) locations and on-premises storage, making it difficult to get a handle on where the most important and sensitive information is. DSPM provides the visibility and control needed to secure this complex environment.
How does DSPM software’s data discovery capabilities work?
DSPM continuously discovers data across cloud, network and on-premises storage to uncover and catalog every piece of data your organization has. Finding sensitive data is the crucial first step in protecting it. DSPM solutions scan your entire data ecosystem such as:
- Cloud platforms (AWS, Azure, GCP)
- SaaS applications (Microsoft 365, Salesforce)
- On-premises storage and databases
Modern DSPM software maintains continuous visibility as data moves and changes through built-in functionality or solution integrations.
What data classification and risk assessment abilities does a DSPM solution provide?
Once discovered, data must be categorized and evaluated for risk exposure. Modern DSPM solutions typically employ advanced AI-driven techniques in this critical phase:
- AI detectors identify regulated information (SSNs, credit cards, health records) and proprietary data using sophisticated recognition capabilities that surpass traditional pattern matching approaches.
- AI summarizers analyze contextual signals like location, access patterns, user behavior and business relevance to understand data meaning and usage.
- Rich classification assignment provides comprehensive data insights that extend well beyond basic Public/Internal/Confidential/Restricted labels, delivering detailed information about file content, business context, regulatory implications and specific risk factors.
These advanced classifications are then combined with protection controls, access permissions and compliance requirements to generate dynamic risk scores. AI-powered classification has become a baseline functionality for usable DSPM platforms, with modern solutions leveraging multiple AI types working together including GenAI, deep neural network classifiers and specialized detection engines to continuously improve both classification accuracy and risk assessment.
How does a DSPM platform help organizations manage and remediate risk?
Identifying issues without resolution creates little value. Modern DSPM platforms bridge this gap with customizable controls that adapt to your organization's unique needs and challenges. These controls include permissions management to implement the Principle of Least Privilege (PoLP), ensuring users only access files required for their tasks and addressing over-permissioned or publicly accessible data. Additional capabilities include data mapping to properly categorize sensitive information, mislocated data remediation to address files stored in inappropriate repositories and data archiving/deletion workflows for managing at-risk files past retention periods or classified as ROT (redundant, obsolete, trivial).
How does reporting and analytics work within DSPM software?
DSPM solutions include reporting and analytics tools that provide visibility into an organization's overall data security status. These reporting capabilities typically feature dashboards showing where sensitive data exists across environments, highlighting specific risk factors such as ROT (redundant, obsolete, trivial) data, over-permissioned files, mislocated information and duplicated content. Security teams can use these insights to track metrics over time and prioritize remediation efforts where they'll have the greatest impact.
What are the different ways you can deploy a DSPM solution?
DSPM solutions offer flexible implementation options:
- Cloud-native SaaS for rapid deployment
- Hybrid models for sensitive environments
- On-premises for control over data sovereignty
- Agentless architectures to minimize overhead
Most enterprises start with their most critical data repositories and expand coverage incrementally.
How does AI and automation enhance Data Security Posture Management?
Automation enables continuous, large-scale data discovery and scanning across enterprise environments. Organizations can now automatically classify data in real-time as it's created, moved or modified—eliminating the delays and gaps inherent in manual reviews. Artificial intelligence's primary value lies in delivering highly accurate data classification while reducing false positives. AI brings the precision needed to confidently distinguish between truly sensitive data and benign information that might trigger traditional rule-based systems. For DSPM solutions to confidently incorporate these capabilities, modern solutions must handle a wide range of file types, from PDFs to video, as well as understand an even broader array of data fields to assign correct classifications and adjust for compliance requirements. This includes leveraging GenAI capabilities, deep neural network classifiers and other predictive AI technologies working together.
What are the key benefits organizations could get from implementing a DSPM platform?
The benefits of Data Security Posture Management can boil down to four outcomes:
- Increase productivity
- Cut costs
- Reduce risk
- Streamline compliance
Does DSPM integrate with other security technologies?
DSPM rarely operates in isolation. Most organizations integrate it with complementary security technologies to create a comprehensive data protection strategy. The insights DSPM software provides about data location, sensitivity and risk naturally enhance other security tools such as:
- Data Detection and Response (DDR)
- Data Loss Prevention (DLP)
- Cloud Access Security Broker (CASB)
- Identity and Access Management (IAM)
- Cloud Security Posture Management (CSPM)
How does DSPM differ from legacy data classification tools?
Unlike traditional tools that work with known data repositories using predefined rules, DSPM continuously discovers both known and unknown data across environments, leveraging AI for more accurate classification and providing context about access patterns and security controls.
What organizational roles should be involved in DSPM implementation?
Because successful DSPM deployment requires collaboration beyond security teams, many organizations establish a data risk committee to regularly review DSPM insights and coordinate remediation efforts. This could include IT infrastructure managers, data governance specialists, compliance officers and business unit representatives who understand departmental data value.
How can organizations measure DSPM ROI beyond compliance?
You can track metrics such as reduction in sensitive data exposure (attack surface reduction), time savings in data discovery processes, improvements in mean-time-to-remediate incidents and reductions in storage costs from eliminating redundant or obsolete data.
