Not too long ago, many security experts believed that the best way to defend data was to apply the strongest possible technological protections to all of the data, all of the time. While that plan may work perfectly in theory, in the real world of business this model creates unacceptable costs, performance and availability problems.
What works from both IT and management standpoints? Risk-adjusted data security. Protecting data according to risk enables organizations to determine their most significant security exposures, target their budgets towards addressing the most critical issues, strengthen their security and compliance profile, and achieve the right balance between business needs and security demands.
Other issues that risk-adjusted security addresses are the unnecessary expenses, availability problems and system performance lags that result when data is over-protected. And cloud-based technologies, mobile devices and the distributed enterprise require a risk-mitigation approach to security, focused on securing mission critical data, rather than the now-unachievable ‘protect all the data at all costs’ model of years past.
Here’s how to develop and deploy a risk-adjusted data protection plan
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.
Nowadays Organisations rely on data heavily to increase the efficiency and effectiveness of their business activities. It is necessary for organisations to secure their database from external attack in other to ensure confidentiality, integrity and availability. Different approaches to protect sensitive database are needed in an enterprise environment and can be combined together to strengthen an organization's security posture, while minimizing the cost and effort of data protection. Some of which are explained below. 1
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.
Transforming Expectations for Treat-Intelligence SharingEMC
Gain insight into a new approach to information-sharing processes for threat intelligence which ensures that data distribution is relevant, actionable, and automated.
RSA Security Briefs provide executives and practitioners with essential guidance on today’s most pressing information-security risks and opportunities. Each Brief is created by a select response team of security and technology experts who mobilize across companies to share specialized knowledge on a critical emerging topic. Offering both big-picture insight and practical technology advice, these papers are vital reading for today’s forward-thinking security leaders.
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.
Nowadays Organisations rely on data heavily to increase the efficiency and effectiveness of their business activities. It is necessary for organisations to secure their database from external attack in other to ensure confidentiality, integrity and availability. Different approaches to protect sensitive database are needed in an enterprise environment and can be combined together to strengthen an organization's security posture, while minimizing the cost and effort of data protection. Some of which are explained below. 1
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.
Transforming Expectations for Treat-Intelligence SharingEMC
Gain insight into a new approach to information-sharing processes for threat intelligence which ensures that data distribution is relevant, actionable, and automated.
RSA Security Briefs provide executives and practitioners with essential guidance on today’s most pressing information-security risks and opportunities. Each Brief is created by a select response team of security and technology experts who mobilize across companies to share specialized knowledge on a critical emerging topic. Offering both big-picture insight and practical technology advice, these papers are vital reading for today’s forward-thinking security leaders.
Webinar: Endpoint Backup is not Enough - You Need an End-user Data StrategyStorage Switzerland
More data outside of the data center is staying on endpoints and in the cloud than ever before. That means the risks to that data are also at an all time high. Plus regulations encompassing end-user data are also increasing, challenging IT to manage data when they have less control than ever. IT needs more than an endpoint protection plan, it needs an end-user data strategy.
In this webinar, learn how to evolve from an endpoint data protection plan to a comprehensive end-user data strategy.
Extending Information Security to Non-Production EnvironmentsLindaWatson19
This paper discusses the threats that non-production environments pose to database security and provides practical advice and multiple options for ensuring data assets remain secure against unauthorized access.
The growing costs of security breaches and manual compliance efforts have given rise to new data security solutions specifically designed to prevent data breaches and deliver automated compliance. This paper examines the drivers for adopting a strategic approach to data security, compares and contrasts current approaches, and presents the Return on Security Investment (ROSI) of viable data security solutions.
Mergers & Acquisitions security - (ISC)2 Secure Summit DACHEQS Group
It does not have an ISO standard. NIST barely mentions it. Despite hundreds of publications, no dedicated book is in sight. Enterprise Risk Management frameworks barely touch on it - if they even do. A chapter in Tipton's book dating 2007, proprietary solutions and sparse articles is all we have. In 2007 there was no Cloud yet - and that can be both a big help or a major issue in the process. Mergers & Acquisition is a matter left to Business Administration professionals, who don't like thinking about Information Security risks anyway. Information Security for Mergers & Acquisition is often an afterthought and rarely a deciding factor in due diligence exercises - but when your company acquires a new firm every quarter, you need to start thinking about something. This session will propose a simple framework and you will walk away with an actionable material you can start using tomorrow.
Learning Objectives:
- Understand information security risks and threats connected with merger and acquisition activities, which include months of often precarious IT migrations, a Cloud mess, and legacy services left exposed for months or years.
- Understand how Cloud Computing affects information security risks and threats during a merger and acquisition activities, as well as the positive opportunities they can offer.
- Why it is important that Information Security is involved in the early phases of due diligence, including during the phases in which the deal is structured and evaluated, and the acquisition model is defined.
- Walk home with a simple framework and actionable material they can start using the day after.
The objective of this workshop is to show existing Oracle Database (Enterprise
Edition, Exadata, Autonomous Database, EXACS, DBCS) customers how to
attach your Database to Data safe and gain valuable understanding of
potential risks. Using user Assessment, understand rights and entitlement of
users and review activity auditing which provides powerful insight to database
interaction. The workshop will finish with a full sensitive data discovery and
then how to anonymize date with sensitive data masking.
The workshop is delivered in an interactive way with Presentations and Hands on
Labs to ensure complete understanding.
Solutions.Information Security During Mergers & Acquisitions:
Issues, Safety Measures, and Need-to-Know Solutions.
Information security risks and threats connected with mergers and acquisitions, which can include months of often precarious IT migrations and legacy services left exposed; how Cloud computing affects information security risks and threats during merger and acquisition activities, as well as the positive opportunities that they can offer; why Information Security should be involved in the early phases of due diligence, including the phases during which the deal is structured and the acquisition model is defined; a simple framework and actionable material.
This paper discusses the question of optimizing security decisions in an organization, based on the information provided by the technical security infrastructure.
IT Executive Guide to Security IntelligencethinkASG
Transitioning from log management and SIEM to comprehensive security intelligence.
This white paper discusses the increasing need for organizations to maintain comprehensive and cost-effective information security, and describes the integrated set of solutions provided by the IBM QRadar Security Intelligence Platform designed to help achieve total security intelligence.
Webinar: Endpoint Backup is not Enough - You Need an End-user Data StrategyStorage Switzerland
More data outside of the data center is staying on endpoints and in the cloud than ever before. That means the risks to that data are also at an all time high. Plus regulations encompassing end-user data are also increasing, challenging IT to manage data when they have less control than ever. IT needs more than an endpoint protection plan, it needs an end-user data strategy.
In this webinar, learn how to evolve from an endpoint data protection plan to a comprehensive end-user data strategy.
Extending Information Security to Non-Production EnvironmentsLindaWatson19
This paper discusses the threats that non-production environments pose to database security and provides practical advice and multiple options for ensuring data assets remain secure against unauthorized access.
The growing costs of security breaches and manual compliance efforts have given rise to new data security solutions specifically designed to prevent data breaches and deliver automated compliance. This paper examines the drivers for adopting a strategic approach to data security, compares and contrasts current approaches, and presents the Return on Security Investment (ROSI) of viable data security solutions.
Mergers & Acquisitions security - (ISC)2 Secure Summit DACHEQS Group
It does not have an ISO standard. NIST barely mentions it. Despite hundreds of publications, no dedicated book is in sight. Enterprise Risk Management frameworks barely touch on it - if they even do. A chapter in Tipton's book dating 2007, proprietary solutions and sparse articles is all we have. In 2007 there was no Cloud yet - and that can be both a big help or a major issue in the process. Mergers & Acquisition is a matter left to Business Administration professionals, who don't like thinking about Information Security risks anyway. Information Security for Mergers & Acquisition is often an afterthought and rarely a deciding factor in due diligence exercises - but when your company acquires a new firm every quarter, you need to start thinking about something. This session will propose a simple framework and you will walk away with an actionable material you can start using tomorrow.
Learning Objectives:
- Understand information security risks and threats connected with merger and acquisition activities, which include months of often precarious IT migrations, a Cloud mess, and legacy services left exposed for months or years.
- Understand how Cloud Computing affects information security risks and threats during a merger and acquisition activities, as well as the positive opportunities they can offer.
- Why it is important that Information Security is involved in the early phases of due diligence, including during the phases in which the deal is structured and evaluated, and the acquisition model is defined.
- Walk home with a simple framework and actionable material they can start using the day after.
The objective of this workshop is to show existing Oracle Database (Enterprise
Edition, Exadata, Autonomous Database, EXACS, DBCS) customers how to
attach your Database to Data safe and gain valuable understanding of
potential risks. Using user Assessment, understand rights and entitlement of
users and review activity auditing which provides powerful insight to database
interaction. The workshop will finish with a full sensitive data discovery and
then how to anonymize date with sensitive data masking.
The workshop is delivered in an interactive way with Presentations and Hands on
Labs to ensure complete understanding.
Solutions.Information Security During Mergers & Acquisitions:
Issues, Safety Measures, and Need-to-Know Solutions.
Information security risks and threats connected with mergers and acquisitions, which can include months of often precarious IT migrations and legacy services left exposed; how Cloud computing affects information security risks and threats during merger and acquisition activities, as well as the positive opportunities that they can offer; why Information Security should be involved in the early phases of due diligence, including the phases during which the deal is structured and the acquisition model is defined; a simple framework and actionable material.
This paper discusses the question of optimizing security decisions in an organization, based on the information provided by the technical security infrastructure.
IT Executive Guide to Security IntelligencethinkASG
Transitioning from log management and SIEM to comprehensive security intelligence.
This white paper discusses the increasing need for organizations to maintain comprehensive and cost-effective information security, and describes the integrated set of solutions provided by the IBM QRadar Security Intelligence Platform designed to help achieve total security intelligence.
Because the biggest impact of cyber breach is data loss, data protection should be architected into the DNA of your cyber security solution. This means focusing security efforts around data from the very beginning, from initial risk assessment, to control design, to implementation and auditing.
Most cyber security solutions protect infrastructure, assuming that data stored within containers will be protected. This white paper explains why this assumption is no longer valid and outlines an approach to designing a cyber security solution directly around data.
Compliance Officers, Risk Managers, Security Professionals, and IT Leaders will understand
the goals and steps of data-centric solution design, as well as its potential benefits.
Module 02 Performance Risk-based Analytics With all the advancemIlonaThornburg83
Module 02 Performance Risk-based Analytics
With all the advancements in technology and encryption levels, some methods are faster or slower than others. In most cases a cybersecurity professional must weigh cost, performance, and security. Risk is a powerful tool used by all cybersecurity professionals to assist in making these decisions, and in influencing appropriate stakeholders by providing appropriate information with regard to these three elements.
Risk analysis or risk base analytics helps determine the level of risk to an organization. The first step in this process is to determine the sensitivity of the data being processed. The example below is a common data classification for many organizations; however, depending on how the data will be used, these data fields may vary due to classification levels.
· Public: Data available to the general public and approved for distribution outside the organization.
· Examples: press releases, directory information (not subject to a government regulations or blocks), product catalogs, application and request forms, and other general information that is openly shared. The type of information an organization would choose to post on its website offers a good example of Public data.
· Internal: Data necessary for the operation of the business and generally available to all internal users, users of that particular customer, and potentially interested third-parties if appropriate and when authorized.
· Examples: Some memos, correspondence, and meeting minutes; contact lists that contain information that is not publicly available; and procedural documentation that should remain internal.
· Confidential: Data generally not made available outside the organization and the unauthorized access, use, disclosure, duplication, modification, or destruction of which could adversely impact the organization and/or customers. All confidential information is sensitive in nature and must be restricted to those with a legitimate business need to know.
· Examples:
· Information covered by the Family Educational Rights and Privacy Act (FERPA), which requires protection of records for current and former students. This includes pictures of students kept for official purposes.
· Personally identifiable information entrusted to the organization’s care that is not restricted use data, such as information regarding applicants, donors, potential donors, or competitive marketing research data.
· Information covered by the Gramm-Leach-Bliley Act (GLB), which requires protection of certain financial records.
· Individual employment information, including salary, benefits and performance appraisals for current, former, and prospective employees.
· Legally privileged information.
· Information that is the subject of a confidentiality agreement.
· Restricted: Data that MUST be specifically protected via various access, confidentiality, integrity and/or non-repudiation controls in order to comply with legislative, regulatory, con ...
Mobile Security: 5 Steps to Mobile Risk ManagementDMIMarketing
Hundreds of companies, and the most demanding Federal agencies rely on DMI for Mobile Security services and solutions. And with more than 500,000 devices under management, we know how to do it right.
Now we’ve distilled 9 years of Mobile Security best practices into a white paper you can download. The paper lays out a smart, sensible approach to managing mobile risk without unnecessary cost and business disruption.
Please be our guest and check out the white paper. You’ll learn:
How to identify and protect against the threats that matter the most
What to do about “the hottest new technologies”
How to get the most protection for the least cost and disruption
The key differences and similarities between Mobile and traditional cybersecurity
- See more at: http://dminc.com/solutions/enterprise-mobility-services/mobilesecuritywp/#sthash.yTptNZRw.dpuf
In this exclusive Security Leadership Series eBook, Citrix chief information security officer Stan Black and chief security strategist Kurt Roemer share best practices for leading meaningful security discussions with the board of directors; engaging end users to protect business information; and meeting security-related compliance requirements.
Partner with HARMAN Digital Transformation Solutions (DTS) to build products and solutions that address real customer needs in real-time, and accelerate business growth.
Why Data-Centric Security Needs to be a Top Priority for Enterprises.pdfEnterprise Insider
In today’s business world, data is one of the most valuable assets that any company can own. As a result, a significant amount of effort and money is spent ensuring that the most effective data security procedures are in place to safeguard it. However, with so many choices, deciding which path to choose is getting increasingly difficult.
Manage Risk by Protecting the Apps and Data That Drive Business ProductivityCitrix
Today you face the challenge of securing a business environment transformed by technologies such as cloud and new workforce requirements such as mobility, BYO and third-party talent.
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?
From Target to Equifax, we're learning just how expensive data breaches can be. And the cost isn't just financial - it's a hit to reputation as well. Learn how to avoid putting your organization at risk by identifying the three pitfalls of data security...and how to navigate around them.
the_role_of_resilience_data_in_ensuring_cloud_security.pptxsarah david
Enhance data security with our Data Resilience Cloud. No software/hardware; solve security challenges. Scale resources dynamically. Achieve resilience, efficiency, compliance. Partner with Cuneiform for seamless cloud data protection.
In this work we highlighted some of the concepts of data privacy, techniques used in data privacy, and some techniques used in data privacy in the cloud plus some new research trends.
Data security to protect pci data flow ulf mattsson - insecure-mag-40Ulf Mattsson
There are innumerable ways that data thieves can attack and penetrate your network. As the saying goes - it’s not if your systems will be breached, but when. Every organization, especially those that handle PCI data, should operate under the assumption that sooner or later, they will be breached.
The new best practices to protect sensitive data and the data flow throughout the enterprise are designed with this assumption in mind. They are about reducing risk of data loss, and responding quickly to attacks when they occur.
First, minimize the amount of sensitive data you collect and store. Some elements, such
as PIN numbers and CVV/CVC codes, are prohibited from being stored, but in general, if you’re not using certain data but you store it anyways, you’re only increasing risk with no returns. If you are using it, or planning to, minimize the number of systems that store or process sensitive data. This will make it easier to protect it, as you will have less to defend. The next step is to implement some sort of data security, as required by PCI DSS regulations. While access controls provide a basic level of protection, they do nothing to protect the data flow, and the PCI council has recognized a need to go beyond them. Data security is applied in one of two ways: coarse-grained security at the volume or file level; and fine-grained security at the column or field-level.
Similar to ISACA New York Metro, Developing, Deploying and Managing a Risk-Adjusted Data Security Plan (20)
Jun 29 new privacy technologies for unicode and international data standards ...Ulf Mattsson
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.
We will discuss new approaches to achieve portability, security, performance, small memory footprint and language preservation for privacy protecting of Unicode data. These new approaches provide granular protection for all Unicode languages and customizable alphabets and byte length preserving protection of privacy protected characters.
Old Approaches
Major Issues
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.
Old approaches to protect International Unicode characters will typically increase the size and change the data formats.
This will break many applications and slow down business operations. This is an example of an old approach that is also randomly returning data in new and unexpected languages
Book about
Quantum Computing Blockchain Reversable Protection Privacy by Design, Applications and APIs Privacy, Risks, and Threats Machine Learning and Analytics Non-Reversable Protection International Unicode Secure Multi-party Computing Computing on Encrypted Data Internet of Things II. Data Confidentiality and Integrity Standards and Regulations IV. Applications VI. Summary Best Practices, Roadmap, and Vision Trends, Innovation, and Evolution Hybrid Cloud , CASB and SASE Appendix A B C D E I. Introduction and Vision Section Access Control Zero Trust Architecture Trusted Execution Environments III. Users and Authorization Governance, Guidance, and Frameworks V. Platforms Data User App Innovation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Chapter Discovery and Search Glossary
qubit-conference-new-york-2021: https://nyc.qubitconference.com/
Cybersecurity: Get ready for the unpredictable
Create a sound cybersecurity strategy based on the right technology & budgetary insights, proven practices, and processes for SMEs.
This virtual event will equip CxOs and cybersecurity teams with the right intel to create a sound cybersecurity strategy based on the right technology & budgetary insights, proven practices, and processes specially tailored for SMEs.
Find out how to bring the smart design of cybersecurity architecture and processes, what to automate & how to properly set up internal and external ownership.
The proven cybersecurity strategy fit for your environment can go a long way. Know what to do in-house, what to outsource, set up your budgets right, and get help from the right cybersecurity specialists.
Secure analytics and machine learning in cloud use casesUlf Mattsson
Table of Contents:
Secure Analytics and Machine Learning in Cloud ......................................................................................... 2
Use case #1 in Financial Industry .............................................................................................................. 2
Data Flow .............................................................................................................................................. 2
The approach can be used for other Use-cases .................................................................................... 2
Homomorphic Encryption for Secure Machine Learning in Cloud ............................................................... 3
Evolving Homomorphic Encryption .......................................................................................................... 3
Performance Examples – HE, RSA and AES ........................................................................................... 3
Performance Examples – FHE, NTRU, ECC, RSA and AES ...................................................................... 3
Some popular HE schemes .................................................................................................................... 4
Examples of HE Libraries used by IBM, Duality, and Microsoft ............................................................ 4
Fast Homomorphic Encryption for Secure Analytics in Cloud ...................................................................... 4
Use case #2 in Health Care ........................................................................................................................ 5
Provable security for untrusted environments ..................................................................................... 5
Comparison to multiparty computation and trusted execution environments ................................... 5
Time and memory requirements of HE ................................................................................................ 5
Managing Data Security in Hybrid Cloud ...................................................................................................... 8
Data Security Policy and Zero Trust Architecture ..................................................................................... 8
The future of encryption will change in the Post-Quantum Era: .............................................................. 8
Managing Data Security in a Hybrid World ................................................................................................... 9
Evolving Privacy Regulations ....................................................................................................................... 10
New Ruling in GDPR under "Schrems II" ................................................................................................. 10
The new California Privacy Rights Act (CPRA)
Evolving international privacy regulations and cross border data transfer - g...Ulf Mattsson
We will discuss the Evolving International Privacy Regulations. Cross Border Data Transfer for GDPR under Schrems II is now ruled by an EU court that defined what is required. This ruling can be far reaching for many businesses.
Data encryption and tokenization for international unicodeUlf Mattsson
Unicode is an information technology standard for the consistent encoding, representation, and handling of text expressed in most of the world's writing systems. The standard is maintained by the Unicode Consortium, and as of March 2020, it has a total of 143,859 characters, with Unicode 13.0 (these characters consist of 143,696 graphic characters and 163 format characters) covering 154 modern and historic scripts, as well as multiple symbol sets and emoji. The character repertoire of the Unicode Standard is synchronized with ISO/IEC 10646, each being code-for-code identical with the other.
The Unicode Standard consists of a set of code charts for visual reference, an encoding method and set of standard character encodings, a set of reference data files, and a number of related items, such as character properties, rules for normalization, decomposition, collation, rendering, and bidirectional text display order (for the correct display of text containing both right-to-left scripts, such as Arabic and Hebrew, and left-to-right scripts). Unicode's success at unifying character sets has led to its widespread and predominant use in the internationalization and localization of computer software. The standard has been implemented in many recent technologies, including modern operating systems, XML, Java (and other programming languages), and the .NET Framework.
Unicode can be implemented by different character encodings. The Unicode standard defines Unicode Transformation Formats (UTF) UTF-8, UTF-16, and UTF-32, and several other encodings. The most commonly used encodings are UTF-8, UTF-16, and UCS-2 (a precursor of UTF-16 without full support for Unicode)
The future of data security and blockchainUlf Mattsson
Discussion of Post-Quantum Cryptography and other technologies:
Data Security Techniques
Secure Multi-Party Computation (SMPC)
Homomorphic encryption (HE)
Differential Privacy (DP) and K-Anonymity
Pseudonymization and Anonymization
Synthetic Data
Zero trust architecture (ZTA)
Zero-knowledge proofs (ZKP)
Private Set Intersection (PSI)
Trusted execution environments (TEE)
Post-Quantum Cryptography
Blockchain
Regulations and Standards in Data Privacy
GDPR and evolving international privacy regulationsUlf Mattsson
Convergence of data privacy principles, standards and regulations
General Data Protection Regulation (GDPR)
GDPR and California Consumer Privacy Act (CCPA)
What role does technologies play in compliance
Use Cases
Privacy preserving computing and secure multi-party computation ISACA AtlantaUlf Mattsson
A major challenge that many organizations faces, is how to address data privacy regulations such as CCPA, GDPR and other emerging regulations around the world, including data residency controls as well as enable data sharing in a secure and private fashion. We will present solutions that can reduce and remove the legal, risk and compliance processes normally associated with data sharing projects by allowing organizations to collaborate across divisions, with other organizations and across jurisdictions where data cannot be relocated or shared.
We will discuss secure multi-party computation where organizations want to securely share sensitive data without revealing their private inputs. We will review solutions that are driving faster time to insight by the use of different techniques for privacy-preserving computing including homomorphic encryption, k-anonymity and differential privacy. We will present best practices and how to control privacy and security throughout the data life cycle. We will also review industry standards, implementations, policy management and case studies for hybrid cloud and on-premises.
Safeguarding customer and financial data in analytics and machine learningUlf Mattsson
Digital Transformation and the opportunities to use data in Analytics and Machine Learning are growing exponentially, but so too are the business and financial risks in Data Privacy. The increasing number of privacy incidents and data breaches are destroying brands and customer trust, and we will discuss how business prioritization can be benefit from a finance-based data risk assessment (FinDRA).
More than 60 countries have introduced privacy laws and by 2023, 65% of the world’s population will have its personal information covered under modern privacy regulations. We will discuss use cases in financial services that are finding a balance between new technology impact, regulatory compliance, and commercial business opportunity. Several privacy-preserving and privacy-enhanced techniques can provide practical security for data in use and data sharing, but none universally cover all use cases. We will discuss what tools can we use mitigate business risks caused by security threats, data residency and privacy issues. We will discuss how technologies like pseudonymization, anonymization, tokenization, encryption, masking and privacy preservation in analytics and business intelligence are used in Analytics and Machine Learning.
Organizations are increasingly concerned about data security in processing personal information in external environments, such as the cloud; and information sharing. Data is spreading across hybrid IT infrastructure on-premises and multi-cloud services and we will discuss how to enforce consistent and holistic data security and privacy policies. Increasing numbers of data security, privacy and identity access management products are in use, but they do not integrate, do not share common policies, and we will discuss use cases in financial services of different techniques to protect and manage data security and privacy.
Protecting data privacy in analytics and machine learning ISACA London UKUlf Mattsson
ISACA London Chapter webinar, Feb 16th 2021
Topic: “Protecting Data Privacy in Analytics and Machine Learning”
Abstract:
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 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.
This session also discusses international standards and emerging privacy-enhanced computation techniques, secure multiparty computation, zero trust, cloud and trusted execution environments. We will 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.
New opportunities and business risks with evolving privacy regulationsUlf Mattsson
In the shadow of the global pandemic and the associated economic downturn, organizations are focused on cost optimization, which often leads to impulsive decisions to deprioritize compliance with all nonrevenue programs.
Regulators have evolved to adapt with the notable increase in data subject complaints and are getting more serious about organizations that don’t properly protect consumer data. Marriott was hit with a $124 million fine while Equifax agreed to pay a minimum of $575 million for its breach. The US Federal Trade Commission, the US Consumer Financial Protection Bureau (CFPB), and all 50 U.S. states and territories sued over the company’s failure to take “reasonable steps” to secure its sensitive personal data.
Privacy and data protection are enforced by a growing number of regulations around the world and people are actively demanding privacy protection — and legislators are reacting. More than 60 countries have introduced privacy laws in response to citizens’ cry for transparency and control. By 2023, 65% of the world’s population will have its personal information covered under modern privacy regulations, up from 10% today, according to Gartner. There is a convergence of data privacy principles, standards and regulations on a common set of fundamental principles.
The opportunities to use data are growing exponentially, but so too are the business and financial risks as the number of data protection and privacy regulations grows internationally.
Join this webinar to learn more about:
- Trends in modern privacy regulations
- The impact on organizations to protect and use sensitive data
- Data privacy principles
- The impact of General Data Protection Regulation (GDPR) and data transfer between US and EU
- The evolving CCPA, the new PCI DSS version 4 and new international data privacy laws or regulations
- Data privacy best practices, use cases and how to control sensitive personal data throughout the data life cycle
What is tokenization in blockchain - BCS LondonUlf Mattsson
BCS North London Branch in association with Central London Branch webinar (by GoToWebinar) Date: 2nd December 2020 Time: 18.00 to 19.30 Event title: Blockchain tokenization “What is tokenization in Blockchain?”
Agenda
Blockchain
What is Blockchain?
Use cases, trends and risks
Vendors and platforms
Data protection techniques and scalability
Tokenization
Digital business
Convert a digital value into a digital token
Local and central models
Cloud
Tokenization in Hybrid cloud
Protecting data privacy in analytics and machine learning - ISACAUlf Mattsson
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 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.
This session also discusses international standards and emerging privacy-enhanced computation techniques, secure multiparty computation, zero trust, cloud and trusted execution environments. We will 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.
Nov 2 security for blockchain and analytics ulf mattsson 2020 nov 2bUlf Mattsson
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 2020Ulf Mattsson
Explore challenges of managing and protecting data. We'll share best practices on establishing the right balance between privacy, security, and compliance
ISACA New York Metro, Developing, Deploying and Managing a Risk-Adjusted Data Security Plan
1. Developing, Deploying and Managing a Risk-
Adjusted Data Security Plan
Ulf Mattsson
CTO
Protegrity
Not too long ago, many security experts believed that the best way to defend data was to
apply the strongest possible technological protections to all of the data, all of the time. While
that plan may work perfectly in theory, in the real world of business this model creates
unacceptable costs, performance and availability problems.
What works from both IT and management standpoints? Risk-adjusted data security.
Protecting data according to risk enables organizations to determine their most significant
security exposures, target their budgets towards addressing the most critical issues,
strengthen their security and compliance profile, and achieve the right balance between
business needs and security demands.
Other issues that risk-adjusted security addresses are the unnecessary expenses,
availability problems and system performance lags that result when data is over-protected.
And cloud-based technologies, mobile devices and the distributed enterprise require a risk-
mitigation approach to security, focused on securing mission critical data, rather than the
now-unachievable ‘protect all the data at all costs’ model of years past.
Here’s how to develop and deploy a risk-adjusted data protection plan:
Step1: Know Your Data
Begin by determining the risk profile of all relevant data collected and stored by the
enterprise, and then classify that data according to its designated risk level. Data that is
resalable for a profit -- typically financial, personally identifiable and confidential information -
- is high risk data and requires the most rigorous protection; other data protection levels
should be determined according to the value of the information to your organization and the
anticipated cost of its exposure -- would your business be impacted? Would it be difficult to
manage media coverage and public response to the breach?
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2. There are several models that a business can use to classify data. Larger enterprises will
likely want to rely on policy-driven automated tools. Smaller businesses can use the simplest
model: assign a numeric value for each class of data; high risk = 5, low risk = 1.
Step 2: Find Your Data
Data flows through a company, into and out of numerous applications and systems. A
complete understanding of the high risk data flow is essential to the risk-adjusted process.
You can’t protect data if you don’t know where it is, and assigned risk levels will change
depending on how data is being collected, used and stored. High risk data residing in places
where many people have access is obviously data that needs the strongest possible
protection.
Locate all of the places that data resides including applications, databases, files, and all the
systems that connect these destinations such as data transfers across internal and external
networks, etc. and determine where the highest-risks reside and who has or can gain access
to data (see “Understand your Enemy” below).
Other areas to examine for data stores include your outsourcing partnerships as well as data
that is being used for nonproduction purposes such as third-party marketing analysis or in
test and engineering environments. It's not uncommon for organizations to invest in
protecting production systems and data centers yet have live data sitting unprotected on the
systems of application developers and other outsourced parties. If live production data is
being used in a less controlled environment there has to be attention paid to regulatory
compliance and security threats. Here, too, data de-identification technologies like Format-
Controlling Encryption and tokenization can help.
Step 3: Understand Your Enemy
The next step is conducting an end-to-end risk analysis on the high risk data flow to identify
the highest risk areas in the enterprise ecosystem and the points where data might be
exposed to unauthorized users.
Currently web services, databases and data-in-transit are at high risk. The type of asset
compromised most frequently is online data. Exploiting programming code vulnerabilities,
subverting authorized user credentials and malware targeting the application layer and data
(rather than the operating system) are the attack methods that are being utilized most
frequently. These vectors change so keep an eye on security news sites to stay abreast of
current threats.
Most data breaches are caused by external sources but breaches attributed to insiders,
though fewer in number, typically have more impact than those caused by outsiders. Nearly
three-quarters of the breaches examined in the Verizon Report were instigated by external
sources. Unauthorized access via default credentials (usually third-party remote access) and
SQL injection (against web applications) were the top types of hacking, access to a network
was often followed by malware being planted on the system.
Step 4: Choose Your Defenses
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3. Look for multi-tasking solutions that protect data according to its risk classification levels,
supports business processes, and is able to be change with the environment so that you can
easily add new defenses for future threats and integrate it with other systems as necessary.
High risk data is best secured using end-to-end encryption or tokenization of individual data
fields. Tokenization removes sensitive data from the information flow at the earliest possible
point in the process, replacing it with a token that acts as an alias for the protected data. By
associating original data with an alias, high-risk data can systematically be removed and
protected from malicious hackers over its lifecycle under a fully auditable and controllable
process. This practical protection method is perfectly suited for securing high risk data like
payment card information and social security numbers.
Newer solutions provide targeted protection for data in use and doesn’t interfere with
business processes. For example, Data Format Controlling Encryption retains the original
format, on a character-by-character basis, of encrypted data, putting an end to the data re-
formatting and database schema changes required by other encryption techniques. It’s
especially well-suited to protect data that’s being used for testing or development in a less-
controlled environment. Partial encryption can then be applied to provide the ability to
encrypt selected parts of a sensitive data field based on policy rules.
Policy-Based Masking provides the ability to mask selected parts of a sensitive data field.
Implemented at the database level rather than application level, policy-based Data Masking
provides a consistent level of security across the enterprise without interfering with business
operations and greatly simplifies data security management chores.
Step 5: Deployment
Risk-Adjusted data protection enables enterprises to stage their security roll-out. Focus your
initial efforts on hardening the areas that handle critical data and are a high-risk target for
attacks. Then continue to work your way down the risk-prioritized list, securing less critical
data and systems with appropriate levels of protection.
Security is an ongoing process not a series of events. The level of protection required by
data may change according to how it is being collected, transmitted, used and stored.
Reevaluate risk levels annually and on an as-needed basis if business processes change.
Step 6: Crunch the Numbers
Risk-adjusted data security plans are cost effective. Among the typical benefits of a risk-
adjusted plan is the elimination of the all too common and costly triage security model which
is ineffective whether you’re triaging based on compliance needs or the security threat of the
moment. Replacing triage with a well thought-out logical plan that takes into account long-
range costs and benefits enables enterprises to target their budgets toward addressing the
most critical issues.
By switching focus to a holistic view rather than the all too common security silo
methodology, an enterprise will also naturally move away from deploying a series of point
solutions at each protection point, which results in redundant costs, invariably leaves holes
in the process, and introduces complexity that will ultimately cause significant and costly
rework.
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4. Additionally, an understanding of where data resides usually results in a project to reduce
the number of places where sensitive data is stored. Once the number of protection points
has been reduced, a project to encrypt the remaining sensitive data with a comprehensive
data protection solution provides the best protection while also giving the business the
flexibility it needs.
To learn more about Risk-Adjusted Data Security visit www.protegrity.com or call
203.326.7200. Protegrity’s free webcast on risk will be presented on 11/17/09, 12:00 PM to 1
PM. To register for the webinar please visit
https://www2.gotomeeting.com/register/531171195
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