#DataMasking

[technology098]

Organizations collect data to improve their products and services and support their business. To use this data effectively, it must be shared with internal and external teams for various purposes. However, using this data for non-productive uses can lead to security breaches and compromised sensitive information.

[jjbizconsult]

Data for All, But Secure: Unlocking Data Democratization Responsibly ✨

[gis56]

Your Data Needs a Bodyguard 🔐 Data-Centric Security to Triple by 2034! #Cybersecurity #DataMatters

Data-centric Security Market is rapidly expanding as organizations shift focus from perimeter-based defenses to strategies that protect the data itself. With rising threats like ransomware, insider attacks, and data breaches, securing sensitive information across cloud, hybrid, and on-premise environments has become critical. Data-centric security ensures that protection travels with the data — through encryption, access controls, data masking, tokenization, and real-time monitoring.

To Request Sample Report : https://www.globalinsightservices.com/request-sample/?id=GIS20927 &utm_source=SnehaPatil&utm_medium=Article

 It offers granular visibility, compliance support, and risk mitigation, empowering businesses to innovate securely in an increasingly digital world. Industries such as finance, healthcare, retail, and government are investing heavily in these solutions to safeguard intellectual property and maintain trust. As regulations tighten and cyberattacks grow more sophisticated, the demand for intelligent, adaptive data-centric security tools continues to surge.

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Research Scope:

· Estimates and forecast the overall market size for the total market, across type, application, and region

· Detailed information and key takeaways on qualitative and quantitative trends, dynamics, business framework, competitive landscape, and company profiling

· Identify factors influencing market growth and challenges, opportunities, drivers, and restraints

· Identify factors that could limit company participation in identified international markets to help properly calibrate market share expectations and growth rates

· Trace and evaluate key development strategies like acquisitions, product launches, mergers, collaborations, business expansions, agreements, partnerships, and R&D activities

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[lovelypol]

Securing Distributed Storage and Processing Frameworks

Big Data Security is a critical area of focus as organizations increasingly rely on vast and complex datasets to drive decision-making and innovation.

Ensuring the security of big data involves addressing several key challenges, including data privacy, integrity, and availability. Advanced encryption techniques, such as homomorphic encryption, are employed to protect data at rest, in transit, and during processing, allowing computations to be performed on encrypted data without compromising its confidentiality. Access control mechanisms, including role-based access control (RBAC) and attribute-based access control (ABAC), are crucial in managing permissions and ensuring that only authorized users can access sensitive data. Additionally, the implementation of robust data masking and anonymization techniques helps in safeguarding personally identifiable information (PII) and complying with regulatory requirements such as GDPR and CCPA. Big data environments often utilize distributed storage and processing frameworks like Hadoop and Spark, necessitating comprehensive security measures across multiple nodes and clusters. Security information and event management (SIEM) systems are deployed to monitor and analyze security events in real-time, enabling the detection and mitigation of potential threats. Machine learning algorithms play an increasingly significant role in identifying anomalous patterns and predicting security breaches before they occur. As cyber threats continue to evolve, continuous vulnerability assessments and penetration testing are essential to maintain the security posture of big data infrastructures. The future of big data security lies in the integration of advanced technologies such as blockchain for immutable audit trails and zero-trust architectures to minimize the attack surface and enhance overall data protection. #BigDataSecurity #Encryption #DataPrivacy #AccessControl #DataMasking #Anonymization #GDPR #CCPA #DistributedStorage #SIEM #MachineLearning #CyberSecurity #ThreatDetection #VulnerabilityAssessment #Blockchain #ZeroTrust #DataProtection #HadoopSecurity #SparkSecurity #DataIntegrity #Compliance #DataGovernance #SecurityArchitecture #InformationSecurity #TechInnovation

[jisasoftech]

JISA SOLUTIONS. Creating Secured Ecosystem For More Info Call @ +919619222553 or mail sales@jisasoftech.com or visit http://jisasoftech.com #AadharDataVault

[ryadel]

Securing Databases in the Cloud: 4 Best Practices

In October 2019, Adobe faced a data breach in which around 7 million Creative Cloud accounts were compromised. The source of the breach? A database that was directly exposed to the Internet.  According to some estimates, there is over an Exabyte of data currently stored in the cloud. A significant amount of that data, often confidential, is stored in databases, such as in the case of Adobe. This makes databases an appealing target for attackers.  If you are storing databases in the cloud, it’s less a question of if you’ll be attacked, but more of when it will happen. To minimize your liability, you need to take proactive steps to secure your databases. 

Cloud Security Basics

Public cloud services work on a shared responsibility model. According to this model, your responsibilities differ depending on the type of cloud service you use. The table below breaks down security responsibilities for each available public cloud model.   Software as a Service Platform as a Service Infrastructure as a Service Your Responsibility Data, endpoints, accounts, access management Data, endpoints, accounts, access management Data, endpoints, accounts, access management, Identity and directory infrastructure, applications, network controls, and OS Shared Responsibility Identity and directory infrastructure Identity and directory infrastructure, applications, and network controls Cloud Provider’s Responsibility applications, network controls, OS, physical hosts, physical network, and physical data centers OS, physical hosts, physical network, and physical data centers physical hosts, physical network, and physical data centers   Cloud providers offer a variety of paid and unpaid services to help you meet your responsibilities for security. For example, monitoring and logging solutions, key management solutions, and access control services. They also typically provide recommendations and best practices in their documentation. The cloud services you choose to use determine the specific services and practices that are applicable to you.  You have different responsibilities and risks if you connect your applications to an external database or host your own. Cloud providers do not take responsibility for self-hosted resources. If you need to host your databases separately, you can choose storage that integrates directly. For example, those available for Azure file storage. Supported integrations often include at least some direct security support from your cloud provider.

4 Best Practices for Securing Databases in the Cloud

#1. Keep Database and Applications Separate You can use network segmentation to isolate your databases. Network segmentation is the use of firewalls and Access Control Lists (ACLs) to isolate services by controlling traffic flow. It often includes layering levels of authentication with your highest priority data at the lowest level. You can use network segmentation to ensure that Internet connections are only able to access your applications, not your databases directly. Virtual Private Clouds (VPCs) are one way of accomplishing segmentation. AWS, Azure, and GCP all have services for creating VPCs. In a VPC, Applications can still access databases via predefined IP addresses and network gateways. Direct Internet connections are not allowed. VPCs and network segmentation can help limit access to your databases in case an application or endpoint is breached. 2#. Always Use Encryption  You should always encrypt data at rest and in transit. The major cloud vendors provide built-in encryption with  their services. Depending on the service, they may also include in-transit encryption. Typically, in-transit encryption is performed with SSL and TLS. At-rest encryption is either performed client-side or server-side and typically uses AES-256. Client-side encryption occurs on-premises. Your data is first encrypted and then transferred to the cloud. Server-side encryption occurs in the cloud and requires plaintext data to be transferred from on-premises. Client-side encryption is more secure but it requires you to independently manage your encryption keys. The major cloud vendors offer paid services that enable you to use client-side keys. Alternatively, you can use a third party service.  You can also consider using tokenization. Tokenization involves mapping data values to a generated token value. The relationship between the value and the assigned token is stored in a database called a token vault. This token value is then sent to the application or user requesting the data to be used as a reference. The data value itself is never transferred to the application or user. Tokenization is particularly useful for one-time access of data and for processing payment information.  3#. Restrict Access to Data You should restrict access to your databases according to the principle of least privilege. The principle states that only those users and applications that require access should have it. You should grant users and applications the minimum amount of privileges necessary to perform required tasks.  Set up permissions according to roles whenever possible. Role-based permissions enable you to more easily apply uniform permissions to users. You can also more easily modify permissions when roles change.  Role-based distribution prevents you from having to modify users individually. Consider also separating administrative credentials into role-specific users. Separating high-level privileges limits the amount of damage that can be done by compromised credentials. #4. Store Only the Data You Need In general, you should only store the data you need. In particular, you should try to limit the amount of Personally Identifiable Information (PII) you store. PII is any information that can be used to identify an individual. This includes, name, ID number, date of birth,and biometric records. It also includes information linked directly to an individual, such as financial, medical, employment, or educational information.  You can anonymize your data before storage if you collect PII but don’t need to retain actual PII values. For example, if you are analyzing medical trend data but only need general demographic data.  You can anonymize data using a variety of techniques, including data masking, pseudonymization, and generalization:  Data masking—involves modifying data with techniques like encryption or character substitution.  Pseudonymization—involves replacing private IDs with fake IDs while preserving statistical accuracy.  Generalization—involves classifying data into categories or ranges to remove specific data. Limiting the data you store helps limit your liability in case of a breach. In addition to limiting live data, take care to limit backups and archive data. Ensure that your backups and archives don’t contain overlapping data to minimize your amount of stored data.  Store backups and archives in highly restricted areas or on-premises. Backups and archives typically only need to be accessed by administrators. There is no reason to store them with the same access permissions as your active databases.

Conclusion

Keeping your databases secure can be challenging but it’s not impossible. If you take the proper precautions you can significantly limit your risks. Hopefully, this article helped you understand the basics of database security and provided some useful tips for protecting your databases.  If you’ve already implemented these practices and are still looking for a little extra security, consider adding some  “canary data” to your databases. Canary data is data that has no legitimate purpose. If you find it in the wild, you know it was stolen from your database.  You can also use this data as a flag, so that if an attacker attempts to transfer it outside of your system, you’ll receive an alert. Canary data can’t keep an attacker out of your system, but it can help you minimize or prevent damage. Read the full article

[operaextensions]

Smart and high-speed web browsing; opera is ranked among the top browsers in the world. Although, DataMask extension for opera many amazing features this unique web and mobile browser. Maybe, DataMask add-ons developed by AgileSaturday. In this article, The extension has a lot of features and options, so it can be a bit confusing to […]

[shanthababu]

Understand the ACID and BASE in Modern Data Engineering

https://lnkd.in/edvnY8DR #dataanalytics #dataanalytics #DataScience #dataprivacy #datasecurity #datamanagement #datamining #datamodeling #datamigration #datamodel #datamonitoring #datastructuresandalgorithms #datasciencetraining #databasemanagement #databackup #datamaturity #datamesh #dataarchitecture #datamonetization #datamapping #datamarketplace #datamart #datamanager #datamanipulation #datamasking

[technology098]

Fortifying Data Masking: Strategies for Protecting Sensitive Information and Ensuring Compliance in Today's Digital Landscape

In today's data-driven world, organizations harness data to refine their offerings, enhance customer experiences, and fortify their operations. However, the strategic utilization of Data Masking its dissemination among internal and external stakeholders. While this sharing is crucial for fostering innovation and collaboration, it also introduces risks of security breaches and compromises to sensitive information. Consequently, safeguarding data integrity has become paramount in contemporary data environments.

To mitigate the peril of data breaches and uphold regulatory compliance, such as GDPR, PCI-DSS, and HIPAA, organizations must adopt robust security protocols. These measures are indispensable for curtailing the exposure of sensitive data throughout its lifecycle. By implementing stringent security practices, enterprises can fortify their defenses and uphold the trust of their customers and partners.

In adhering to security and compliance imperatives, organizations deploy a multifaceted approach encompassing various phases of their operational cycle. From data acquisition to storage, processing, and transmission, each stage demands tailored security measures to mitigate vulnerabilities and thwart potential threats. By integrating security seamlessly into their workflows, organizations can engender a culture of vigilance and resilience against evolving cybersecurity challenges.

Central to data masking is the concept of least privilege, whereby access to sensitive information is restricted only to authorized personnel and systems. By limiting access based on roles and responsibilities, organizations minimize the risk of unauthorized data exposure and inadvertent leaks. Moreover, encryption techniques are instrumental in safeguarding data integrity during transit and storage, rendering it indecipherable to unauthorized entities.

Furthermore, organizations invest in robust authentication and authorization mechanisms to validate the identity of users and govern their access privileges. Multi-factor authentication, biometric verification, and access controls are pivotal in fortifying defenses against unauthorized access attempts. Similarly, audit trails and logging mechanisms enable organizations to monitor and trace user activities, facilitating timely detection and mitigation of security incidents.

In parallel, organizations leverage advanced technologies such as artificial intelligence and machine learning to augment their threat detection capabilities. By analyzing vast troves of data in real-time, these systems can discern anomalous patterns indicative of potential security breaches. This proactive approach empowers organizations to preemptively thwart threats before they escalate into full-fledged breaches.

Moreover, robust incident response plans are indispensable for orchestrating swift and coordinated responses to security incidents. By delineating roles, responsibilities, and escalation procedures, organizations can minimize the impact of breaches and expedite recovery efforts. Regular drills and simulations enable teams to refine their response strategies and bolster their preparedness for emergent cyber threats.

Beyond technological fortifications, fostering a culture of security awareness is imperative for cultivating a vigilant workforce. Comprehensive training programs equip employees with the knowledge and skills to identify and mitigate security risks in their daily activities. By instilling a sense of collective responsibility, organizations empower their employees to serve as frontline defenders against cyber threats.

In conclusion, safeguarding sensitive data is an ongoing imperative for organizations navigating the complexities of today's Data Masking. By embracing a holistic approach to data security, encompassing technological, procedural, and cultural dimensions, enterprises can fortify their defenses and uphold the trust of their stakeholders. In a landscape fraught with evolving cyber threats, proactive measures are indispensable for preserving data integrity and fostering sustainable business growth.

[annotationsupport]

What is Data masking, types and techniques?

#Datamasking is a technique for creating a phony but realistic replica of your organization’s data. Know more the details at:https://annotationsupport.com/blog/what-is-data-masking-types-and-techniques/?utm_source=tumblr&utm_medium=organic

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モジラ「Firefox 74」のTLS 1.0/1.1廃止を一時撤回 - 新型コロナウイルスの影響で (窓の杜)

新刊 書籍：演奏するプログラミング、ライブコーディングの思想と実践 - Show Us Your Screens (アマゾン)

低品質コンテンツの削除は、クロール効率とサイト品質の改善に役立つ (海外SEO情報ブログ)

クッキー規制で企業のデータ保持はどう変わる？GDPR/CCPAの動向もおさらい (Web担当者Forum)

任意のウェブページのスクリーンショットを撮る前に個人情報が含まれる部分を加工できる��ラウザ拡張「DataMask」 (かちびと)

Copy Excel Paste Markdown - エクセルの表をMarkdownに変換 (MOONGIFT)

現代ウェブフロントエンド (ウェブアプリケーション) について理解する唯一の方法 (erukiti | note)

プログラミングを実務に生かすには？コードを書かない業務自動化のススメ (ITmedia)

商用利用無料、おしゃれな筆記体の英語フリーフォント・手書きの英語フリーフォントの総まとめ (コリス)

[herrprofessor]

DataMask — Mask private data before taking screenshots http://bit.ly/2KjSVrg #hotproduct

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— herrprofessor (@ilprofessoredi) August 3, 2019

from Twitter https://twitter.com/ilprofessoredi August 03, 2019 at 12:21PM via IFTTT

[hottestproducts]

Mask private data before taking screenshots

[mrzanko]

SQL/T-SQL LEAD

Job Title:                SQL/T-SQL LEAD Location:               RESTON ,VA Duration:                6+Months Interview Type:        Skype Primary Skills::    Data Masking exp with SQL  Job Description: End-to-End analysis to identify sensitive information (PII, PHI) using Redgate DataMasker Develop, Design and Execute for DataMasker and de-identifying solution ...

Source: https://www.jobisite.com/sj/id/9035797-SQL/T-SQL LEAD

[jobisitejobsusa]

SQL/T-SQL LEAD

Job Title:                SQL/T-SQL LEAD Location:               RESTON ,VA Duration:                6+Months Interview Type:        Skype Primary Skills::    Data Masking exp with SQL  Job Description: End-to-End analysis to identify sensitive information (PII, PHI) using Redgate DataMasker Develop, Design and Execute for DataMasker and de-identifying solution ... from Job Portal https://www.jobisite.com/sj/id/9035797-SQL/T-SQL LEAD