Ulf Mattsson - Issued us patents - Apr 24 2017
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Inventor in the areas of mobile payment, cloud security, database security, tokenization and encryption with more than 45 patents granted in the US.
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Jun 29 new privacy technologies for unicode and international data standards ...
Protecting the increasing use International Unicode characters is required by a growing number of Privacy Laws in many countries and general Privacy Concerns with private data. Current approaches to protect International Unicode characters will increase the size and change the data formats. This will break many applications and slow down business operations. The current approach is also randomly returning data in new and unexpected languages. New approach with significantly higher performance and a memory footprint can be customizable and fit on small IoT devices.
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Data Security Policy and Zero Trust Architecture ..................................................................................... 8
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When we think about developing AI responsibly, there’s many different activities that we need to think about.
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We will review how different industries are taking opportunity of these privacy preserving techniques. A retail company used secure multi-party computation to be able to respect user privacy and specific regulations and allow the retailer to gain insights while protecting the organization’s IP. Secure data-sharing is used by a healthcare organization to protect the privacy of individuals and they also store and search on encrypted medical data in cloud.
We will also review the benefits of secure data-sharing for financial institutions including a large bank that wanted to broaden access to its data lake without compromising data privacy but preserving the data’s analytical quality for machine learning purposes.
Nov 2 security for blockchain and analytics ulf mattsson 2020 nov 2b
Blockchain
- What is Blockchain?
- Blockchain trends
Emerging data protection techniques
- Secure multiparty computation
- Trusted execution environments
- Use cases for analytics
- Industry Standards
Tokenization
- Convert a digital value into a digital token
- Tokenization local or in a centralized model
- Tokenization and scalability
Cloud
- Analytics in Hybrid cloud
Unlock the potential of data security 2020
Explore challenges of managing and protecting data. We'll share best practices on establishing the right balance between privacy, security, and compliance
What is tokenization in blockchain?
Tokenization on Blockchain is a steady trend. It seems that everything is being tokenized on Blockchain from paintings, diamonds and company stocks to real estate. Thus, we took an asset, tokenized it and created its digital representation that lives on Blockchain. Blockchain guarantees that the ownership information is immutable.
Unfortunately, some problems need to be solved before we can successfully tokenize real-world assets on Blockchain. Main problem stems from the fact that so far, no country has a solid regulation for cryptocurrency. For example, what happens if a company that handles tokenization sells the property? They have no legal rights on the property and thus are not protected by the law. Another problem is that this system brings us back some sort of centralization. The whole idea of Blockchain and especially smart contracts is to create a trustless environment.
Tokenization is a method that converts a digital value into a digital token. Tokenization can be used as a method that converts rights to an asset into a digital token.
The tokenization system can be implemented local to the data that is tokenized or in a centralized model. We will discuss tokenization implementations that can provide scalability across hybrid cloud models. This session will position different data protection techniques, use cases for blockchain, and protecting blockchain.
Protecting Data Privacy in Analytics and Machine Learning
In this session, we will discuss a range of new emerging technologies for privacy and confidentiality in machine learning and data analytics. We will discuss how to use open source tools to put these technologies to work for databases and other data sources.
When we think about developing AI responsibly, there’s many different activities that we need to think about. In this session, we will discuss technologies that help protect people, preserve privacy, and enable you to do machine learning confidentially.
This session discusses industry standards and emerging privacy-enhanced computation techniques, secure multiparty computation, and trusted execution environments. We will discuss Zero Trust philosophy fundamentally changes the way we approach security since trust is a vulnerability that can be exploited particularly when working remotely and increasingly using cloud models. We will also discuss the “why, what, and how” of techniques for privacy preserving computing.
We will review how different industries are taking opportunity of these privacy preserving techniques. A retail company used secure multi-party computation to be able to respect user privacy and specific regulations and allow the retailer to gain insights while protecting the organization’s IP. Secure data-sharing is used by a healthcare organization to protect the privacy of individuals and they also store and search on encrypted medical data in cloud.
We will also review the benefits of secure data-sharing for financial institutions including a large bank that wanted to broaden access to its data lake without compromising data privacy but preserving the data’s analytical quality for machine learning purposes.
ISACA Houston - How to de-classify data and rethink transfer of data between ...
Updated deck for Aug 25 isaca houston webinar
Isaca atlanta - practical data security and privacy
My deck from my Jul 29 webinar at ISACA Atlanta about PRACTICAL DATA SECURITY and PRIVACY
ISACA Houston - Practical data privacy and de-identification techniques
I uploaded the slide deck from my Jul 25 webinar at ISACA about Practical Data Privacy and De-Identification Techniques
Jul 16 isaca london data protection, security and privacy risks - on premis...
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Privacy preserving computing and secure multi party computation
Privacy preserving computing and secure multi party computation
Evolving regulations are changing the way we think about tools and technology
Discover the latest in RegTech and stay up-to-date on compliance tools and best practices.
The move to digital has meant that many organizations have had to rethink legacy systems.
They need to put the customer first, focus on the Customer Experience and Digital Experience Platforms.
They also need to understand the latest in RegTech and solutions for hybrid cloud.
We will discuss Regtech for the financial industry and related technologies for compliance.
We will discuss new International Standards, tools and best practices for financial institutions including PCI v4, FFIEC, NACHA, NIST, GDPR and CCPA.
We will discuss related technologies for Data Security and Privacy, including data de-identification, encryption, tokenization and the new API Economy.
More from Ulf Mattsson (20)
GDPR and evolving international privacy regulations
GDPR and evolving international privacy regulations
Privacy preserving computing and secure multi-party computation ISACA Atlanta
Privacy preserving computing and secure multi-party computation ISACA Atlanta
Safeguarding customer and financial data in analytics and machine learning
Safeguarding customer and financial data in analytics and machine learning
Protecting data privacy in analytics and machine learning ISACA London UK
Protecting data privacy in analytics and machine learning ISACA London UK
New opportunities and business risks with evolving privacy regulations
New opportunities and business risks with evolving privacy regulations
Protecting data privacy in analytics and machine learning - ISACA
Protecting data privacy in analytics and machine learning - ISACA
Nov 2 security for blockchain and analytics ulf mattsson 2020 nov 2b
Nov 2 security for blockchain and analytics ulf mattsson 2020 nov 2b
Protecting Data Privacy in Analytics and Machine Learning
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ISACA Houston - How to de-classify data and rethink transfer of data between ...
ISACA Houston - How to de-classify data and rethink transfer of data between ...
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ISACA Houston - Practical data privacy and de-identification techniques
ISACA Houston - Practical data privacy and de-identification techniques
Jul 16 isaca london data protection, security and privacy risks - on premis...
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Privacy preserving computing and secure multi party computation
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Evolving regulations are changing the way we think about tools and technology
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- 1. PAT. NO. Title 9,563,788 Tokenizationinacentralizedtokenizationenvironment 9,516,031 Assignmentof securitycontextstodefine accesspermissionsforfile systemobjects 9,514,457 Tokenizationinmobile environments 9,514,334 Decentralizedtoken table generation 9,514,330 Meta-complete datastorage 9,514,319 Database and methodforcontrollingaccesstoa database 9,514,169 Columnartable dataprotection 9,443,104 Tokenizationof structureddata 9,430,767 Tokenizationinmobile environments 9,430,652 Use rule-basedtokenizationdataprotection 9,426,141 Verifiable tokenization 9,313,195 Collisionavoidance inadistributedtokenizationenvironment 9,274,241 Methodand systemforsuppressingswell-inducedelectromagneticnoise 9,237,006 Table-connectedtokenization 9,230,136 Tokenizationcolumnreplacement 9,230,128 Assignmentof securitycontextstodefine accesspermissionsforfile systemobjects 9,229,987 Mappingbetweentokenizationdomains 9,219,716 Distributedtokenization usingseveral substitutionsteps 9,202,086 Tokenizationinacentralizedtokenizationenvironment 9,152,579 Meta-complete datastorage 9,148,476 Verifiable tokenization 9,111,116 Collisionavoidance inadistributedtokenizationenvironment 9,092,614 Preventingimpersonationof acomputersystemuser 9,087,209 Database access control 8,978,152 Decentralizedtokentable generation 8,935,802 Verifiable tokenization 8,935,787 Multi-layersystemforprivacyenforcementandmonitoringof suspiciousdata accessbehavior 8,893,250 Tokenizationinmobile environments 8,826,449 Data securityina disconnectedenvironment 8,769,272 Differential encryptionutilizingtrustmodes 8,745,094 Distributedtokenizationusingseveral substitutionsteps 8,701,191 Multi-layersystemforprivacyenforcementandmonitoringof suspiciousdataaccessbehavior 8,661,263 Meta-complete datastorage 8,578,176 Methodand apparatusfor tokenizationof sensitivesetsof characters 8,510,335 Database and methodforcontrollingaccesstoa database 8,443,426 Methodand systemforpreventingimpersonationof acomputersystemuser 8,225,106 Differential encryptionutilizingtrustmodes 7,984,025 Methodfor reencryptionof adatabase 7,594,266 Data securityand intrusiondetection 7,490,248 Methodfor reencryptionof adatabase 7,418,098 Data type preservingencryption 7,325,129 Methodfor alteringencryptionstatusinarelational database inacontinuousprocess
- 2. 7,305,707 Methodfor intrusiondetectionina database system 7,120,933 Methodfor intrusiondetectioninadatabase system 6,963,980 Combinedhardware andsoftware basedencryptionof databases