Discover what PII Data Masking is and why it's crucial for protecting sensitive information. Learn how it works, its benefits, and best practices for safeguarding personal data.
Data masking can be referred to as the method of creating structurally similar but a different version of all sensitive data. Masked data remains valid for several purposes, like user training, software testing, and machine learning data sets.
IBM offers unified data protection solutions for four key data environments:
1) Big data security - Solutions are needed to securely harness rapidly growing data from diverse sources in big data platforms and prevent unauthorized access and data breaches.
2) Cloud and virtual environment data security - Both private and public cloud infrastructures need protection against data leakage.
3) Enterprise data security - Heterogeneous enterprise data from various sources like databases and data warehouses requires protection.
4) Enterprise application security - Solutions are needed to securely protect multi-tier enterprise applications.
IBM's InfoSphere Guardium provides next-generation activity monitoring, auditing and data protection across physical, virtual and cloud environments.
Fujifilm’s data security solutions protect your company’s intellectual property from unauthorized access. Start by authenticating users, monitoring and controlling confidential information, and tracking the authenticity of all your critical documents.
It is shocking to note that about 3.5 billion people saw their
personal data stolen in the top two of the 15 biggest breaches
of this century alone. With the average cost of a data breach
exceeding $8 million, it is no wonder that safeguarding
confidential business and customer information has become
more important than ever. Furthermore, with stricter laws and governance requirements, data security is now everyone’s
responsibility across the entire enterprise.
However, that is easier said than done, and for that reason, an
an increasing number of organizations are relying heavily on data masking to proactively protect their data, avoid the cost of security breaches, and ensure compliance.
Insurance companies of all sizes are challenged to keep up with emerging technologies that deliver a competitive advantage. Recording: https://www.brighttalk.com/webcast/9573/192877
Big data holds the key to greater customer insight and stronger customer relationships. But risk of sensitive data exposure — and compliance violations — keeps many insurers from pursuing big data initiatives and reaping the rewards of business-driven analytics. Join Dataguise and Hortonworks for this live webinar to learn how you can free your organization from traditional information security constraints and unlock the power of your most valuable business assets.
• What do you need to know about PII/PHI privacy before embarking on big data initiatives?
• Why do so many big data initiatives fail before they’ve even begun—and what can you do about it?
• How can IT security organizations help data scientists extract more business value from their data?
• How are leading insurance companies leveraging big data to gain competitive advantage?
Fortify Your Business with Data Security Services: Protect Your Assets with M...basilmph
In the digital era, data has become one of the most valuable assets for businesses. From sensitive customer information to proprietary business strategies, data is at the core of every organization’s operations. However, with the rise of cyber threats and data breaches, ensuring the security of this critical asset has never been more important.
Encryption is a key defence against cyber threats in big data analytics. By securing data at rest and in transit, organisations can prevent unauthorised access and data leaks. Coupled with role-based access and strong authentication, encryption helps businesses maintain confidentiality while enabling secure data processing and storage.
Source - https://www.docullyvdr.com/blog/data-room/data-security-platform-securing-data-in-big-data-and-analytics-environments/
There are three key challenges to effective data governance and security in the big data era: 1) ethics and compliance as personally identifiable data is widespread and regulations are increasing, 2) poor data management when there is no clear ownership or lifecycle management of data, and 3) insecure infrastructure as many IoT and other devices were not designed with security in mind. Effective data governance requires a combination of people, processes, and technology to classify, secure, and manage data throughout its lifecycle.
The document discusses three key challenges for data governance and security with big data: 1) ethics and compliance as personally identifiable data is widespread and regulations are increasing, 2) poor data management when there is no clear ownership or lifecycle management of data, and 3) insecure infrastructure as many devices and systems generating data were not designed with security in mind. Effective data governance is important for security, and requires defining responsibilities, auditing data use, and protecting data during collection, storage, and analysis. Technologies can help automate and scale governance, but it is ultimately a combination of people, processes, and tools.
The Role of Privacy-Enhancing Technologies in Cybersecurity.pdfkhushnuma khan
Privacy-enhancing technologies (PETs) are crucial in modern cybersecurity, helping to safeguard sensitive data, ensure regulatory compliance, and build consumer trust. With threats evolving, businesses must adopt PETs like encryption, anonymization, tokenization, and access controls to protect user privacy and secure critical data.
Data foundation for analytics excellenceMudit Mangal
The document discusses predictive analytics and business insights. It covers what data analytics is and its challenges, the importance of data foundation and governance, security issues with data, and a retail use case. The future of data analytics is also discussed, with more structured, human interaction, and machine data expected to be analyzed. Establishing a robust data foundation is key to enabling trusted reporting and analytics.
The document discusses data security and data management. It defines data security as processes and practices to protect critical IT systems and information. Effective data security uses controls, applications, and techniques to identify important data and apply appropriate security controls. Data security is important for organizations to protect user and customer data from unauthorized access. Common data security methods include access controls, authentication, backups, encryption, and data erasure. Data management techniques aim to ensure data quality, integrate data across systems, and govern data use and access. The document also discusses specific techniques for data cleansing, integration, and other aspects of data management.
Isaca global journal - choosing the most appropriate data security solution ...Ulf Mattsson
Recent breaches demonstrate the urgent need to secure enterprise identities against cyberthreats that target today’s hybrid IT environment of cloud, mobile and on-premises. The rapid rise of cloud databases, storage and applications has led to unease among adopters over the security of their data. Whether it is data stored in a public, private or hybrid cloud, or used in third party SaaS applications, companies have good reason to be concerned. The biggest challenge in this interconnected world is merging data security with data value and productivity. If we are to realize the benefits promised by these new ways of doing business, we urgently need a data-centric strategy to protect the sensitive data flowing through these digital business systems.
Protecting Data Privacy Beyond the Trusted System of RecordCor Ranzijn
Data Privacy Passports is a new IBM capability that can help businesses maintain data privacy and protection when sensitive data leaves a trusted system of record. It works by encrypting data into trusted data objects (TDOs) and controlling access to the encrypted data through a central Passport Controller. This allows businesses to enforce access policies, revoke access remotely, and more easily audit who has accessed data. The document discusses how Data Privacy Passports addresses key data privacy concerns and provides benefits like reduced risk, lower administrative costs, and an estimated 300% return on investment over five years.
Big data refers to large, complex datasets that are difficult to process using traditional methods. It is growing exponentially from sources like the internet, sensors, and social media. Big data has characteristics like volume, velocity, variety, and veracity. While it enables better decision making and customer insights, big data also poses challenges around privacy, security, complexity, and cost. Effective use of big data requires investment in tools, skills, and governance strategies.
The Growing Importance of Data Encryption in IT Security.pdfnetsquad123
Data encryption is vital for IT security, protecting sensitive data from cyber threats. Netsquad, a leading WhatsApp Service Provider, ensures secure communications with advanced encryption, compliance, and trust through robust cybersecurity solutions.
The document discusses organizations' experiences with GDPR compliance after the May 2018 deadline. It finds that many organizations are still dealing with residual risks and have uncovered more personal data than expected during their discovery processes. Specifically, organizations have struggled to fully comply with data deletion requests due to data being spread across systems without full lineage. The document advocates that organizations view GDPR not just as a compliance burden but as an opportunity to improve data governance, build customer trust, and enable digital expansion.
Data Privacy | Data Management Frameworks - Tejasvi AddagadaTejasvi Addagada
Explore insights by Tejasvi Addagada on data privacy, robust data management frameworks, and strengthening security. Learn how privacy-enhancing technologies, data governance strategies, and generative AI improve data quality and protection. Discover best practices to secure sensitive information, ensure compliance, and build trust in the evolving digital landscape. Consult now!
Fujifilm offers advanced data security solutions to protect sensitive information from cyber threats and unauthorized access. Our technology ensures data encryption, user authentication, and secure data transfer. Trust Fujifilm to keep your data safe.
In 2025, protecting personal and company data is more important than ever. As technology keeps evolving and consumers become more aware of how their information is being used, businesses are under growing pressure to keep that data safe. Strict privacy laws and higher expectations from customers mean companies cannot afford to treat cybersecurity as an afterthought anymore.
Big data security is important to protect sensitive data from cyberthreats, comply with regulations, and ensure business continuity. Securing big data is challenging due to its large volume, complexity, and need for real-time processing. Effective big data security strategies include implementing strong encryption, access control, data anonymization, threat detection, security analytics, and regular auditing.
Modern data protection and privacy rests on accurate data classification and labeling for smarter more accurate enforcement. BigID's award-winning sensitive data discovery and tagging provides a first of its kind ability to accurately find and secure personal data.
BigID Data Sheet: Smart Data Labeling and TaggingBigID Inc
Effective data protection enforcement depends on understanding what data needs to be protected - especially as mandates like the EU GDPR and pending California Consumer Privacy Act add privacy protection requirements. Through smart labeling that leverages machine learning for discovery and classification and identity correlation for privacy understanding, BigID enables smarter, more accurate and automated policy enforcement actions. Customers can optimize their existing enforcement investments to take smarter policy actions and address new
The document discusses 7 ways for businesses to better protect data and improve their security posture in the modern workplace. It outlines steps to reduce threats through identity and access management, manage mobile devices and apps, leverage conditional access, increase enterprise data protection, prevent data loss, enable secured collaboration, and reduce malware exposure. The overall message is that businesses can give employees mobility and productivity while also protecting sensitive data through proper planning, tools, and education.
A data security platform ensures seamless access while maintaining top-notch security. With encrypted storage, multi-factor authentication, and role-based permissions, users can confidently access critical data from anywhere. The right platform balances speed and security, enhancing productivity without compromising confidentiality.
Source - https://www.docullyvdr.com/blog/virtual-data-room/exploring-the-key-features-of-a-data-security-platform/
Data is an important assets for an enterprise. Data must be protected against loss and destruction. In IT field huge data is being exchanged among multiple people at every moment. During sharing of the data, there are huge chances of data vulnerability, leakage or alteration. So, to prevent these problems, a survey on data leakage detection system has been done. This paper talks about the concept, causes and techniques to detect the data leakage. Businesses processes facts and figures to turn raw data into useful information. This information is used by businesses to generate and improve revenue at every mile stone. Thus, along with data availability and accessibility data security is also very important.
Today’s online world brings new challenges to businesses, making the security of your businesses’ internal information extremely critical. As we are all connected to the Internet,
we all can become a victim of cyber-attacks.
So, what can you do to better protect your business and secure your internal data?
Protect your confidential information while improving servicesCloudMask inc.
The document discusses security issues with cloud computing and software as a service (SaaS) applications. It introduces CloudMask as a solution that protects sensitive data by masking it before it enters encryption channels and at data centers. This prevents unauthorized access to data even if user credentials or data center security are compromised. CloudMask allows secure use of cloud services without the risks of data breaches and regulatory issues from exposed sensitive data.
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The document discusses three key challenges for data governance and security with big data: 1) ethics and compliance as personally identifiable data is widespread and regulations are increasing, 2) poor data management when there is no clear ownership or lifecycle management of data, and 3) insecure infrastructure as many devices and systems generating data were not designed with security in mind. Effective data governance is important for security, and requires defining responsibilities, auditing data use, and protecting data during collection, storage, and analysis. Technologies can help automate and scale governance, but it is ultimately a combination of people, processes, and tools.
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Data foundation for analytics excellenceMudit Mangal
The document discusses predictive analytics and business insights. It covers what data analytics is and its challenges, the importance of data foundation and governance, security issues with data, and a retail use case. The future of data analytics is also discussed, with more structured, human interaction, and machine data expected to be analyzed. Establishing a robust data foundation is key to enabling trusted reporting and analytics.
The document discusses data security and data management. It defines data security as processes and practices to protect critical IT systems and information. Effective data security uses controls, applications, and techniques to identify important data and apply appropriate security controls. Data security is important for organizations to protect user and customer data from unauthorized access. Common data security methods include access controls, authentication, backups, encryption, and data erasure. Data management techniques aim to ensure data quality, integrate data across systems, and govern data use and access. The document also discusses specific techniques for data cleansing, integration, and other aspects of data management.
Isaca global journal - choosing the most appropriate data security solution ...Ulf Mattsson
Recent breaches demonstrate the urgent need to secure enterprise identities against cyberthreats that target today’s hybrid IT environment of cloud, mobile and on-premises. The rapid rise of cloud databases, storage and applications has led to unease among adopters over the security of their data. Whether it is data stored in a public, private or hybrid cloud, or used in third party SaaS applications, companies have good reason to be concerned. The biggest challenge in this interconnected world is merging data security with data value and productivity. If we are to realize the benefits promised by these new ways of doing business, we urgently need a data-centric strategy to protect the sensitive data flowing through these digital business systems.
Protecting Data Privacy Beyond the Trusted System of RecordCor Ranzijn
Data Privacy Passports is a new IBM capability that can help businesses maintain data privacy and protection when sensitive data leaves a trusted system of record. It works by encrypting data into trusted data objects (TDOs) and controlling access to the encrypted data through a central Passport Controller. This allows businesses to enforce access policies, revoke access remotely, and more easily audit who has accessed data. The document discusses how Data Privacy Passports addresses key data privacy concerns and provides benefits like reduced risk, lower administrative costs, and an estimated 300% return on investment over five years.
Big data refers to large, complex datasets that are difficult to process using traditional methods. It is growing exponentially from sources like the internet, sensors, and social media. Big data has characteristics like volume, velocity, variety, and veracity. While it enables better decision making and customer insights, big data also poses challenges around privacy, security, complexity, and cost. Effective use of big data requires investment in tools, skills, and governance strategies.
The Growing Importance of Data Encryption in IT Security.pdfnetsquad123
Data encryption is vital for IT security, protecting sensitive data from cyber threats. Netsquad, a leading WhatsApp Service Provider, ensures secure communications with advanced encryption, compliance, and trust through robust cybersecurity solutions.
The document discusses organizations' experiences with GDPR compliance after the May 2018 deadline. It finds that many organizations are still dealing with residual risks and have uncovered more personal data than expected during their discovery processes. Specifically, organizations have struggled to fully comply with data deletion requests due to data being spread across systems without full lineage. The document advocates that organizations view GDPR not just as a compliance burden but as an opportunity to improve data governance, build customer trust, and enable digital expansion.
Data Privacy | Data Management Frameworks - Tejasvi AddagadaTejasvi Addagada
Explore insights by Tejasvi Addagada on data privacy, robust data management frameworks, and strengthening security. Learn how privacy-enhancing technologies, data governance strategies, and generative AI improve data quality and protection. Discover best practices to secure sensitive information, ensure compliance, and build trust in the evolving digital landscape. Consult now!
Fujifilm offers advanced data security solutions to protect sensitive information from cyber threats and unauthorized access. Our technology ensures data encryption, user authentication, and secure data transfer. Trust Fujifilm to keep your data safe.
In 2025, protecting personal and company data is more important than ever. As technology keeps evolving and consumers become more aware of how their information is being used, businesses are under growing pressure to keep that data safe. Strict privacy laws and higher expectations from customers mean companies cannot afford to treat cybersecurity as an afterthought anymore.
Big data security is important to protect sensitive data from cyberthreats, comply with regulations, and ensure business continuity. Securing big data is challenging due to its large volume, complexity, and need for real-time processing. Effective big data security strategies include implementing strong encryption, access control, data anonymization, threat detection, security analytics, and regular auditing.
Modern data protection and privacy rests on accurate data classification and labeling for smarter more accurate enforcement. BigID's award-winning sensitive data discovery and tagging provides a first of its kind ability to accurately find and secure personal data.
BigID Data Sheet: Smart Data Labeling and TaggingBigID Inc
Effective data protection enforcement depends on understanding what data needs to be protected - especially as mandates like the EU GDPR and pending California Consumer Privacy Act add privacy protection requirements. Through smart labeling that leverages machine learning for discovery and classification and identity correlation for privacy understanding, BigID enables smarter, more accurate and automated policy enforcement actions. Customers can optimize their existing enforcement investments to take smarter policy actions and address new
The document discusses 7 ways for businesses to better protect data and improve their security posture in the modern workplace. It outlines steps to reduce threats through identity and access management, manage mobile devices and apps, leverage conditional access, increase enterprise data protection, prevent data loss, enable secured collaboration, and reduce malware exposure. The overall message is that businesses can give employees mobility and productivity while also protecting sensitive data through proper planning, tools, and education.
A data security platform ensures seamless access while maintaining top-notch security. With encrypted storage, multi-factor authentication, and role-based permissions, users can confidently access critical data from anywhere. The right platform balances speed and security, enhancing productivity without compromising confidentiality.
Source - https://www.docullyvdr.com/blog/virtual-data-room/exploring-the-key-features-of-a-data-security-platform/
Data is an important assets for an enterprise. Data must be protected against loss and destruction. In IT field huge data is being exchanged among multiple people at every moment. During sharing of the data, there are huge chances of data vulnerability, leakage or alteration. So, to prevent these problems, a survey on data leakage detection system has been done. This paper talks about the concept, causes and techniques to detect the data leakage. Businesses processes facts and figures to turn raw data into useful information. This information is used by businesses to generate and improve revenue at every mile stone. Thus, along with data availability and accessibility data security is also very important.
Today’s online world brings new challenges to businesses, making the security of your businesses’ internal information extremely critical. As we are all connected to the Internet,
we all can become a victim of cyber-attacks.
So, what can you do to better protect your business and secure your internal data?
Protect your confidential information while improving servicesCloudMask inc.
The document discusses security issues with cloud computing and software as a service (SaaS) applications. It introduces CloudMask as a solution that protects sensitive data by masking it before it enters encryption channels and at data centers. This prevents unauthorized access to data even if user credentials or data center security are compromised. CloudMask allows secure use of cloud services without the risks of data breaches and regulatory issues from exposed sensitive data.
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2. In today’s data-driven world, protecting sensitive
information has become a critical priority for
organizations across industries. With the rise of data
breaches, regulatory compliance requirements, and the
increasing value of personal data, safeguarding Personally
Identifiable Information (PII) is no longer optional—it’s
essential. This is where PII Data Masking comes into play,
offering a powerful solution to ensure privacy while
maintaining data usability. Let’s explore how data masking
works, its importance, and why it’s a game-changer for
3. What is PII Data Masking?
PII Data Masking is a data security technique that involves
obscuring or replacing sensitive information with fictional but
realistic data. The goal is to protect PII, such as names, Social
Security numbers, credit card details, and email addresses,
while ensuring that the data remains functional for testing,
development, or analytics purposes. Unlike encryption, which
transforms data into an unreadable format but can be
reversed, data masking is irreversible, making it a safer option
for sharing data in non-production environments.
4. Why is PII Data Masking
Important?
Governments worldwide have introduced stringent data
protection laws, such as the General Data Protection Regulation
(GDPR) in Europe and the California Consumer Privacy Act
(CCPA) in the United States. These regulations mandate that
organizations protect PII and impose heavy penalties for non-
compliance. PII Data Masking helps organizations meet these
requirements by ensuring that sensitive data is not exposed
during internal processes like software testing or data analysis.
Compliance with Data Privacy Regulations
5. Mitigating Data Breach Risks
Data breaches can have devastating consequences, including financial
losses, reputational damage, and legal liabilities. By masking PII,
organizations can significantly reduce the risk of sensitive data being
exposed in the event of a breach. Even if masked data is accessed, it
holds no value to attackers, as the original information cannot be
reconstructed.
Enabling Secure Data Sharing
Organizations often need to share data with third parties, such as
vendors, partners, or contractors. PII Data Masking ensures that
sensitive information is not exposed during these exchanges, allowing
businesses to collaborate securely without compromising privacy.
6. Supporting Development and Testing
Software development and testing often require access to realistic data
sets. However, using real PII in these environments can pose significant
risks. Data masking provides a safe alternative by generating realistic but
fake data that mimics the structure and format of the original
information, enabling developers and testers to work effectively without
exposing sensitive details.
7. How Does PII Data Masking Work?
• Substitution: Replacing real data with fictional but realistic values.
For example, replacing actual names with randomly generated ones.
• Shuffling: Randomly rearranging data within a column to break the
link between the original and masked values.
• Redaction: Removing or blacking out sensitive information entirely.
• Tokenization: Replacing sensitive data with unique tokens that have
no exploitable value.
• Data Perturbation: Slightly altering numerical data (e.g., dates or
salaries) to make it unrecognizable while preserving its utility for
PII Data Masking employs various techniques to protect sensitive information,
including:
8. Best Practices for Implementing PII Data
Masking
Identify Sensitive Data: Start by identifying all PII within your
organization’s data sets. This includes not only obvious fields like names
and Social Security numbers but also less apparent ones like IP
addresses or geolocation data.
Choose the Right Masking Technique: Select the most appropriate
masking method based on the type of data and its intended use. For
example, substitution may work well for names, while tokenization might
be better suited for credit card numbers.
Ensure Consistency: Maintain consistency in masked data to avoid
disrupting business processes. For instance, if a customer’s name is
masked, ensure that the same masked value is used across all systems.
Test Masked Data: Validate that the masked data retains its usability for
9. The Future of PII Data Masking
As data privacy concerns continue to grow, PII Data Masking
will play an increasingly vital role in safeguarding sensitive
information. Advances in artificial intelligence and machine
learning are also enhancing data masking techniques,
enabling more sophisticated and dynamic approaches to
privacy protection. By adopting PII Data Masking,
organizations can strike the perfect balance between data
utility and security, ensuring privacy remains in plain sight.
10. Conclusion,
PII Data Masking is not just a technical solution—it’s
a strategic imperative for any organization that
handles sensitive data. By implementing robust data
masking practices, businesses can protect their
customers, comply with regulations, and build trust
in an increasingly data-centric world.