This document discusses cloud computing and related security issues. It provides background on cloud computing models and services. It discusses how cloud computing impacts enterprise security lifecycle management and control. Current trends of increasing cloud services adoption and consumerization of enterprise IT are described. Requirements for cloud computing like identity management, assurance, compliance and privacy are outlined. Initiatives to develop best practices for cloud security are also mentioned. Potential future research directions around trusted infrastructure, security analytics, economics of cloud stewardship and privacy management are proposed.
The document provides an overview of a project using big data analytics to detect security threats from DNS data. It describes collecting massive amounts of DNS logs, analyzing them to detect malware and attacks, and developing solutions to transfer the technology to HPE security products and services. Key points include analyzing over 16 billion DNS packets per day, detecting threats from compromised or botnet-controlled DNS servers, and developing DNS malware analytics as a cloud-based security solution.
Edge computing and the Internet of Things bring great promise, but often just getting data from the edge requires moving mountains. Let's learn how to make edge data ingestion and analytics easier using StreamSets Data Collector edge, an ultralight, platform independent and small-footprint Open Source solution written in Go for streaming data from resource-constrained sensors and personal devices (like medical equipment or smartphones) to Apache Kafka, Amazon Kinesis and many others. This talk includes an overview of the SDC Edge main features, supported protocols and available processors for data transformation, insights on how it solves some challenges of traditional approaches to data ingestion, pipeline design basics, a walk-through some practical applications (Android devices and Raspberry Pi) and its integration with other technologies such as Streamsets Data Collector, Apache Kafka, Apache Hadoop, InfluxDB and Grafana. The goal here is to make attendees ready to quickly become IoT data intake and SDC Edge Ninjas.
Speaker
Guglielmo Iozzia, Big Data Delivery Manager, Optum (United Health)
Operating a secure big data platform in a multi-cloud environmentDataWorks Summit
The Health Cyberinfrastructure Division at the San Diego Supercomputer Center (SDSC) at the University of California, San Diego has been deploying and managing a number of big data platforms ranging from the traditional data warehouse to the more recent big data platforms leveraging Hadoop in a secure cloud platform, Sherlock Cloud, for nearly a decade. We understand the necessity to remain agile and visionary in this arena to grow with the ever-changing technological and customer requirements while simultaneously ensuring a compliant environment to secure data.
As such, during our presentation, we will speak to our more recent deployment, namely a multi-cloud, Hadoop-based data management platform and the mechanisms employed to marry best-of-breed big data technology solutions and cloud platforms to support large-scale data management and analytics within the highly secure and compliant (U.S. HIPAA-compliant) boundaries of our hybrid cloud that spans an on-premises cloud running at UC San Diego and another operating in AWS Cloud. We will further identify the challenges and lessons learned from deploying, and securely operating, a big data platform offering capabilities that include disaster recovery and business continuity across a hybrid cloud setup.
Speaker
Sandeep Chandra, Division Director, San Diego Supercomputer Center
This document outlines security issues associated with big data in cloud computing. It begins with introductions to big data, cloud computing, and Hadoop. It describes how big data is related to cloud computing and discusses advantages and applications of big data. The document then discusses security issues at the network, authentication, and data levels. It proposes several approaches to address these security issues, such as file encryption, network encryption, and access control. Finally, it discusses conclusions and opportunities for future work.
Not Just a necessary evil, it’s good for business: implementing PCI DSS contr...DataWorks Summit
For firms in the financial industry, especially within regulated organizations such as credit card processors and banks, PCI DSS compliance has become a business and operational necessity. Although the blueprint of a PCI-compliant architecture varies from organization to organization, the mixture of modern Hadoop-based data lakes and legacy systems are a common theme.
In this talk, we will discuss recent updates to PCI DSS and how significant portions of PCI DSS compliance controls can be achieved using open source Hadoop security stack and technologies for the Hadoop ecosystem. We will provide a broad overview of implementing key aspects of PCI DSS standards at WorldPay such as encryption management, data protection with anonymization, separation of duties, and deployment considerations regarding securing the Hadoop clusters at the network layer from a practitioner’s perspective. The talk will provide patterns and practices map current Hadoop security capabilities to security controls that a PCI-compliant environment requires.
Speaker
David Walker, Enterprise Data Platform Programme Director, Worldpay
Srikanth Venkat, Senior Director Product Management, Hortonworks
A Trusted TPA Model, to Improve Security & Reliability for Cloud StorageIRJET Journal
This document presents a proposed Trusted Third Party Auditing (TPA) model called the Trusted TPA Model (TTM) to improve security and reliability for cloud storage. The TTM uses AES-256 encryption and SHA-1 hashing to provide two-way security by maintaining both data security and integrity. It aims to improve over existing methods by providing more efficient encryption/decryption, better computation times, optimal storage costs, and stronger privacy and integrity. The TTM uses AES-256 and SHA-1, Diffie-Hellman key exchange, and involves modules for data upload, key generation/exchange, encryption/hashing, and TPA verification. An evaluation shows the TTM provides better results than
Data analytics, Spark, Hadoop and AI have become fundamental tools to drive digital transformation. A critical challenge is moving from isolated experiments to an organizational or enterprise production infrastructure. In this talk, we break apart the modern data analytics workflow to focus on the data challenges across different phases of the analytics and AI life cycle. By presenting a unified approach to data storage for AI and Analytics, organizations can reduce costs, modernize their data strategy and build a sustainable enterprise data lake. By anticipating how Hadoop, Spark, Tensorflow, Caffe and traditional analytics like SAS, HPC can share data, IT departments and data science practitioners can not only co-exist, but speed time to insight. We will present the tangible benefits of a Reference Architecture using real-world installations that span proprietary and open-source frameworks. Using intelligent software-defined shared storage, users are able to eliminate silos, reduce multiple data copies, and improve time to insight.PALLAVI GALGALI, Offering Manager,IBM and DOUGLAS O'FLAHERTY, Portfolio Product Manager, IBM
The document provides an overview of a project using big data analytics to detect security threats from DNS data. It describes collecting massive amounts of DNS logs, analyzing them to detect malware and attacks, and developing solutions to transfer the technology to HPE security products and services. Key points include analyzing over 16 billion DNS packets per day, detecting threats from compromised or botnet-controlled DNS servers, and developing DNS malware analytics as a cloud-based security solution.
Edge computing and the Internet of Things bring great promise, but often just getting data from the edge requires moving mountains. Let's learn how to make edge data ingestion and analytics easier using StreamSets Data Collector edge, an ultralight, platform independent and small-footprint Open Source solution written in Go for streaming data from resource-constrained sensors and personal devices (like medical equipment or smartphones) to Apache Kafka, Amazon Kinesis and many others. This talk includes an overview of the SDC Edge main features, supported protocols and available processors for data transformation, insights on how it solves some challenges of traditional approaches to data ingestion, pipeline design basics, a walk-through some practical applications (Android devices and Raspberry Pi) and its integration with other technologies such as Streamsets Data Collector, Apache Kafka, Apache Hadoop, InfluxDB and Grafana. The goal here is to make attendees ready to quickly become IoT data intake and SDC Edge Ninjas.
Speaker
Guglielmo Iozzia, Big Data Delivery Manager, Optum (United Health)
Operating a secure big data platform in a multi-cloud environmentDataWorks Summit
The Health Cyberinfrastructure Division at the San Diego Supercomputer Center (SDSC) at the University of California, San Diego has been deploying and managing a number of big data platforms ranging from the traditional data warehouse to the more recent big data platforms leveraging Hadoop in a secure cloud platform, Sherlock Cloud, for nearly a decade. We understand the necessity to remain agile and visionary in this arena to grow with the ever-changing technological and customer requirements while simultaneously ensuring a compliant environment to secure data.
As such, during our presentation, we will speak to our more recent deployment, namely a multi-cloud, Hadoop-based data management platform and the mechanisms employed to marry best-of-breed big data technology solutions and cloud platforms to support large-scale data management and analytics within the highly secure and compliant (U.S. HIPAA-compliant) boundaries of our hybrid cloud that spans an on-premises cloud running at UC San Diego and another operating in AWS Cloud. We will further identify the challenges and lessons learned from deploying, and securely operating, a big data platform offering capabilities that include disaster recovery and business continuity across a hybrid cloud setup.
Speaker
Sandeep Chandra, Division Director, San Diego Supercomputer Center
This document outlines security issues associated with big data in cloud computing. It begins with introductions to big data, cloud computing, and Hadoop. It describes how big data is related to cloud computing and discusses advantages and applications of big data. The document then discusses security issues at the network, authentication, and data levels. It proposes several approaches to address these security issues, such as file encryption, network encryption, and access control. Finally, it discusses conclusions and opportunities for future work.
Not Just a necessary evil, it’s good for business: implementing PCI DSS contr...DataWorks Summit
For firms in the financial industry, especially within regulated organizations such as credit card processors and banks, PCI DSS compliance has become a business and operational necessity. Although the blueprint of a PCI-compliant architecture varies from organization to organization, the mixture of modern Hadoop-based data lakes and legacy systems are a common theme.
In this talk, we will discuss recent updates to PCI DSS and how significant portions of PCI DSS compliance controls can be achieved using open source Hadoop security stack and technologies for the Hadoop ecosystem. We will provide a broad overview of implementing key aspects of PCI DSS standards at WorldPay such as encryption management, data protection with anonymization, separation of duties, and deployment considerations regarding securing the Hadoop clusters at the network layer from a practitioner’s perspective. The talk will provide patterns and practices map current Hadoop security capabilities to security controls that a PCI-compliant environment requires.
Speaker
David Walker, Enterprise Data Platform Programme Director, Worldpay
Srikanth Venkat, Senior Director Product Management, Hortonworks
A Trusted TPA Model, to Improve Security & Reliability for Cloud StorageIRJET Journal
This document presents a proposed Trusted Third Party Auditing (TPA) model called the Trusted TPA Model (TTM) to improve security and reliability for cloud storage. The TTM uses AES-256 encryption and SHA-1 hashing to provide two-way security by maintaining both data security and integrity. It aims to improve over existing methods by providing more efficient encryption/decryption, better computation times, optimal storage costs, and stronger privacy and integrity. The TTM uses AES-256 and SHA-1, Diffie-Hellman key exchange, and involves modules for data upload, key generation/exchange, encryption/hashing, and TPA verification. An evaluation shows the TTM provides better results than
Data analytics, Spark, Hadoop and AI have become fundamental tools to drive digital transformation. A critical challenge is moving from isolated experiments to an organizational or enterprise production infrastructure. In this talk, we break apart the modern data analytics workflow to focus on the data challenges across different phases of the analytics and AI life cycle. By presenting a unified approach to data storage for AI and Analytics, organizations can reduce costs, modernize their data strategy and build a sustainable enterprise data lake. By anticipating how Hadoop, Spark, Tensorflow, Caffe and traditional analytics like SAS, HPC can share data, IT departments and data science practitioners can not only co-exist, but speed time to insight. We will present the tangible benefits of a Reference Architecture using real-world installations that span proprietary and open-source frameworks. Using intelligent software-defined shared storage, users are able to eliminate silos, reduce multiple data copies, and improve time to insight.PALLAVI GALGALI, Offering Manager,IBM and DOUGLAS O'FLAHERTY, Portfolio Product Manager, IBM
Undertaking a digital journey starts with clearly articulating the success factors for the entire digital journey, and our experience from the field has shown it to be an Achilles heel for most CXOs, across Fortune 500 organizations. Our findings were corroborated when a Mckinsey study reported that only 15% of the organizations are able to calculate the ROI of a digital initiative.
In this talk we will deliberate on demonstrated examples from multi-billion dollar businesses around proven methodologies to measure the value of a digital enterprise. The panel will share experiences as well as provide actionable advice for immediate next steps around the following:
Successful metrics for measuring the value for Digital / IoT / AI/ Machine learning engagements
How can 'Digital Traction Metrics' help with actionable insights even before the Financial Metrics have been reported
What are the best in-class organizational constructs and futuristic employee engagement methods to facilitate the digital revolution
Panelists for this session include:
• Christian Bilien - Head of Global Data at Societe Generale
• Pierre Alexandre Pautrat – Head of Big Data at BPCE/Nattixis
• Ronny Fehling – VP , Airbus
• Juergen Urbanski – Silicon Valley Data Science
• Abhas Ricky - EMEA Lead, Innovation & Strategy, Hortonworks
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help boost feelings of calmness, happiness and focus.
Continuous Data Ingestion pipeline for the EnterpriseDataWorks Summit
Continuous Data ingestion platform built on NIFI and Spark that integrates variety of data sources including real-time events, data from external sources , structured and unstructured data with in-flight governance providing a real-time pipeline moving data from source to consumption in minutes. The next-gen data pipeline has helped eliminate the legacy batch latency and improve data quality and governance by designing custom NIFI processors and embedded Spark code. To meet the stringent regulatory requirements the data pipeline is being augmented with features to do in-flight ETL , DQ checks that enables a continuous workflow enhancing the Raw / unclassified data to Enriched / classified data available for consumption by users and production processes.
How big data and AI saved the day: critical IP almost walked out the doorDataWorks Summit
Cybersecurity threats have evolved beyond what traditional SIEMs and firewalls can detect. We present case studies highlighting how:
•An advanced manufacturer was able to identify new insider threats, enabling them to protect their IP
•A media company’s security operations center was able to verify they weren’t the source of a high-profile media leak.
The common thread across these real-world case studies is how businesses can expand their threat analysis using security analytics powered by artificial intelligence in a big data environment.
Cybersecurity threats increasingly require the aggregation and analysis of multiple data sources. Siloed tools and technologies serve their purpose, but can’t be applied to look across the ever-growing variety and volume of traffic. Big data technologies are a proven solution to aggregating and analysing data across enormous volumes and varieties of data in a scalable way. However, as security professionals well know, more data doesn’t mean more leads or detection. In fact, all too often more data means slower threat hunting and more missed incidents. The solution is to leverage advanced analytical methods like machine learning.
Machine learning is a powerful mathematical approach that can learn patterns in data to identify relevant areas to focus. By applying these methods, we can automatically learn baseline activity and detect deviations across all data sources to flag high-risk entities that behave differently from their peers or past activity. ROY WILDS, Principal Data Scientist, Interset
This document discusses cloud computing and proposes a scheme for proof of data integrity in the cloud. It begins by defining cloud computing and describing the infrastructure needed to run applications over the internet. It then discusses security issues with cloud storage, where users do not have control over remotely stored data. The proposed scheme generates encrypted metadata for files and allows users to verify integrity by challenging the data center to provide specific bits, proving the file was not illegally modified. The scheme is best suited for encrypted static files stored in the cloud.
In the healthcare sector, data security, governance, and quality are crucial for maintaining patient privacy and ensuring the highest standards of care. At Florida Blue, the leading health insurer of Florida serving over five million members, there is a multifaceted network of care providers, business users, sales agents, and other divisions relying on the same datasets to derive critical information for multiple applications across the enterprise. However, maintaining consistent data governance and security for protected health information and other extended data attributes has always been a complex challenge that did not easily accommodate the wide range of needs for Florida Blue’s many business units. Using Apache Ranger, we developed a federated Identity & Access Management (IAM) approach that allows each tenant to have their own IAM mechanism. All user groups and roles are propagated across the federation in order to determine users’ data entitlement and access authorization; this applies to all stages of the system, from the broadest tenant levels down to specific data rows and columns. We also enabled audit attributes to ensure data quality by documenting data sources, reasons for data collection, date and time of data collection, and more. In this discussion, we will outline our implementation approach, review the results, and highlight our “lessons learned.”
The value of the fast growing class of big data technologies is the ability to handle high velocity and volumes of data. However, a lack of robust security and auditing capabilities are holding organizations back from fully using the potential of these systems. Learn how you can use Big Data technologies to help you meet this compliance and data protection challenge head on so you can return to innovating for competitive advantage.
Using InfoSphere Guardium and BigInsights, we'll show you how you can meet your Hadoop security, compliance and audit requirements.
On the Application of AI for Failure Management: Problems, Solutions and Algo...Jorge Cardoso
Artificial Intelligence for IT Operations (AIOps) is a class of software which targets the automation of operational tasks through machine learning technologies. ML algorithms are typically used to support tasks such as anomaly detection, root-causes analysis, failure prevention, failure prediction, and system remediation. AIOps is gaining an increasing interest from the industry due to the exponential growth of IT operations and the complexity of new technology. Modern applications are assembled from hundreds of dependent microservices distributed across many cloud platforms, leading to extremely complex software systems. Studies show that cloud environments are now too complex to be managed solely by humans. This talk discusses various AIOps problems we have addressed over the years and gives a sketch of the solutions and algorithms we have implemented. Interesting problems include hypervisor anomaly detection, root-cause analysis of software service failures using application logs, multi-modal anomaly detection, root-cause analysis using distributed traces, and verification of virtual private cloud networks.
This document presents a high-level data warehouse, business intelligence, and reporting strategy for CDCR. It defines key terms, lists references and sources of information, and scopes the project. The strategy will define a lifecycle for a DW implementation, leverage industry best practices, and align with CDCR's existing systems and strategic needs over three phases. It seeks to improve data quality, governance, and performance metrics for decision making.
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFiDataWorks Summit
This document discusses using Apache NiFi to build a high-speed cyber security data pipeline. It outlines the challenges of ingesting, transforming, and routing large volumes of security data from various sources to stakeholders like security operations centers, data scientists, and executives. It proposes using NiFi as a centralized data gateway to ingest data from multiple sources using a single entry point, transform the data according to destination needs, and reliably deliver the data while avoiding issues like network traffic and data duplication. The document provides an example NiFi flow and discusses metrics from processing over 20 billion events through 100+ production flows and 1000+ transformations.
Multi-tenant Hadoop - the challenge of maintaining high SLASDataWorks Summit
In shared configuration, the same Hadoop environment supports many applications. Each has
specific requirements and criticality (SLA). Yet they all rely on an assembly of shared application
bricks.
At the same time, the life cycle of a cluster is not static in time. It evolves horizontally, with the
arrival of new applications, but also vertically, as the applications grow in load or evolve in
terms of functionality.
With this in mind, a multi-tenant production cluster presents several challenges including and
not limited to:
- Maintain a high level of SLA for a set of use cases with heterogeneous needs
- Plan and implement the architecture evolution of a cluster in production to ensure the
maintenance of SLA throughout the integration of new use cases on it
EDF will present how it manages this heterogeneity of SLA inherent of any Big Data cluster. EDF
is focusing on how it is renovating its cluster, its organization, its processes and its approach in
order to deliver a platform with strong SLA throughout its life cycle.
Speaker
Edouard Rousseaux, Tech Lead, EDF
Enabling data dynamic and indirect mutual trust for cloud computing storage s...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
3 guiding priciples to improve data securityKeith Braswell
This document discusses the need for organizations to adopt a holistic approach to data security and compliance. It outlines three guiding principles: 1) Understand and define where sensitive data resides across the enterprise. 2) Secure and protect enterprise databases and monitor and audit data access. 3) Continuously monitor systems to demonstrate compliance to auditors. The document argues that a systematic, proactive approach is needed to address the growing threats to data security from sophisticated hackers, increased regulations, and the explosion of data sources and types in today's complex IT environments.
Ciso round table on effective implementation of dlp & data securityPriyanka Aash
The document discusses an effective implementation of data loss prevention (DLP) and data security. It covers key factors like the evolving threat landscape, business drivers for DLP, common challenges, and approaches to solve data security issues. An effective methodology is proposed, including identifying critical data and channels, deploying suitable policies, monitoring incidents, and establishing governance through continuous review and improvement. Critical success factors include business involvement, a phased implementation approach, and repeating the plan-do-check-act cycle periodically. The expected project outcomes are protection of critical channels, improved data tracking and awareness, and happier customers and auditors.
Lessons learned from over 25 Data Virtualization implementationsDenodo
Watch full webinar here: https://bit.ly/327fzQ0
If you have been part of the Denodo community for a while, you likely have heard of SimplicityBI (now part of the BDO family). This expert firm located in Canada has done over 25 implementations of Denodo across North America in over 10 different industries.
The document discusses cloud computing risks and mitigation strategies. It provides an overview of cloud computing definitions and models. It then discusses several key risks to cloud computing like privileged user access, data segregation, regulatory compliance, and the physical location of data. For each risk, it proposes potential mitigation strategies to evaluate like access controls, encryption, understanding regulatory obligations, and considering data location.
Digital transformations require a new hybrid cloud—one that’s open by design, and frees clients to choose and change environments, data and services as needed. This approach allows cloud apps and services to be rapidly composed using the best relevant data and insights available, while maintaining clear visibility, control and security—everywhere. How do you decide where to put data on a hybrid cloud and how to use it? What’s the best hybrid cloud strategy in terms of data and workload? How should you leverage a 50/50 rule or a 80/20 rule and user interaction to evaluate which data/workload to move to the cloud and which data/workload to keep on-premise? Hybrid cloud provides an open platform for innovation, including cognitive computing. Organizations are looking for taking shadow IT out of the shadows by providing a self-service way to the information and a hybrid cloud strategy is allowing that. Also, how to use hybrid cloud for better manage data sovereignty & compliance?
It's All about Insight: Unlocking Effective Risk Management for Your Unstruct...Veritas Technologies LLC
Ransomware, data breaches, and credential hi-jacking can all initiate severe information crises--and put your unstructured data at serious risk. Vision is not a security conference, but that doesn't change the fact that you must monitor data at rest to keep your organization safe. This session will show you how Veritas Data Insight delivers the risk intelligence you need to keep all of your information safe--and make your CISO friends jealous.
Continuously improving factory operations is of critical importance to manufacturers. Consider the facts: the total cost of poor quality amounts to a staggering 20% of sales (American Society of Quality), and unplanned downtime costs plants approximately $50 billion per year (Deloitte).
The most pressing questions are: which process variables effect quality and yield and which process variables predict equipment failure? Getting to those answers is providing forward thinking manufacturers a leg up over competitors.
The speakers address the data management challenges facing today's manufacturers, including proprietary systems and siloed data sources, as well as an inability to make sensor-based data usable.
Integrating enterprise data from ERP, MES, maintenance systems, and other sources with real-time operations data from sensors, PLCs, SCADA systems, and historians represents a major first step. But how to get started? What is the value of a data lake? How are AI/ML being applied to enable real time action?
Join us for this educational session, which includes a view into a roadmap for an open source industrial IoT data management platform.
Key Takeaways:
• Understand key use cases commonly undertaken by manufacturing enterprises
• Understand the value of using multivariate manufacturing data sources, as opposed to a single sensor on a piece of equipment
• Understand advances in big data management and streaming analytics that are paving the way to next-generation factory performance
IRJET-Auditing and Resisting Key Exposure on Cloud StorageIRJET Journal
1. The document discusses auditing and resisting key exposure in cloud storage. It proposes a new framework called an auditing protocol with key-exposure resilience that allows integrity of stored data to still be verified even if the client's current secret key is exposed.
2. It formalizes the definition and security model for such a protocol and proposes an efficient practical construction. The security proof and asymptotic performance analysis show the proposed protocol is secure and efficient.
3. Key techniques used include periodic key updates, homomorphic linear authenticators, and a novel authenticator construction to boost forward security and provide proof of retrievability with the current design.
IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)Denny Muktar
This is the slide for IBM Partner Event, November 2015.
Digital Transformation, Innovation, and Industry Transformer through Hybrid Cloud. IBM Scenarios of Hybrid Cloud and Roadmap .An example of how Enterprise can get into Hybrid Cloud through simple Dev/Test Private Cloud as the start.
EMEA10: Trepidation in Moving to the CloudCompTIA UK
Today’s buzz centres on cloud computing. What is it exactly? Will it dent your revenues or does it have potential to add capabilities to your business? How do you deliver value when you don’t “install” anything? Learn how to use this new approach to delivering IT services in your business, what to consider and where it makes sense – and where it doesn’t! Dave Sobel, CEO of Evolve Technologies, talks to you about how to develop cloud offerings and how you position your business for growth around online services. Strategies come from real life experience, industry data, and collaboration with other solution providers to give you the best way to take on the big, bad cloud.
Undertaking a digital journey starts with clearly articulating the success factors for the entire digital journey, and our experience from the field has shown it to be an Achilles heel for most CXOs, across Fortune 500 organizations. Our findings were corroborated when a Mckinsey study reported that only 15% of the organizations are able to calculate the ROI of a digital initiative.
In this talk we will deliberate on demonstrated examples from multi-billion dollar businesses around proven methodologies to measure the value of a digital enterprise. The panel will share experiences as well as provide actionable advice for immediate next steps around the following:
Successful metrics for measuring the value for Digital / IoT / AI/ Machine learning engagements
How can 'Digital Traction Metrics' help with actionable insights even before the Financial Metrics have been reported
What are the best in-class organizational constructs and futuristic employee engagement methods to facilitate the digital revolution
Panelists for this session include:
• Christian Bilien - Head of Global Data at Societe Generale
• Pierre Alexandre Pautrat – Head of Big Data at BPCE/Nattixis
• Ronny Fehling – VP , Airbus
• Juergen Urbanski – Silicon Valley Data Science
• Abhas Ricky - EMEA Lead, Innovation & Strategy, Hortonworks
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help boost feelings of calmness, happiness and focus.
Continuous Data Ingestion pipeline for the EnterpriseDataWorks Summit
Continuous Data ingestion platform built on NIFI and Spark that integrates variety of data sources including real-time events, data from external sources , structured and unstructured data with in-flight governance providing a real-time pipeline moving data from source to consumption in minutes. The next-gen data pipeline has helped eliminate the legacy batch latency and improve data quality and governance by designing custom NIFI processors and embedded Spark code. To meet the stringent regulatory requirements the data pipeline is being augmented with features to do in-flight ETL , DQ checks that enables a continuous workflow enhancing the Raw / unclassified data to Enriched / classified data available for consumption by users and production processes.
How big data and AI saved the day: critical IP almost walked out the doorDataWorks Summit
Cybersecurity threats have evolved beyond what traditional SIEMs and firewalls can detect. We present case studies highlighting how:
•An advanced manufacturer was able to identify new insider threats, enabling them to protect their IP
•A media company’s security operations center was able to verify they weren’t the source of a high-profile media leak.
The common thread across these real-world case studies is how businesses can expand their threat analysis using security analytics powered by artificial intelligence in a big data environment.
Cybersecurity threats increasingly require the aggregation and analysis of multiple data sources. Siloed tools and technologies serve their purpose, but can’t be applied to look across the ever-growing variety and volume of traffic. Big data technologies are a proven solution to aggregating and analysing data across enormous volumes and varieties of data in a scalable way. However, as security professionals well know, more data doesn’t mean more leads or detection. In fact, all too often more data means slower threat hunting and more missed incidents. The solution is to leverage advanced analytical methods like machine learning.
Machine learning is a powerful mathematical approach that can learn patterns in data to identify relevant areas to focus. By applying these methods, we can automatically learn baseline activity and detect deviations across all data sources to flag high-risk entities that behave differently from their peers or past activity. ROY WILDS, Principal Data Scientist, Interset
This document discusses cloud computing and proposes a scheme for proof of data integrity in the cloud. It begins by defining cloud computing and describing the infrastructure needed to run applications over the internet. It then discusses security issues with cloud storage, where users do not have control over remotely stored data. The proposed scheme generates encrypted metadata for files and allows users to verify integrity by challenging the data center to provide specific bits, proving the file was not illegally modified. The scheme is best suited for encrypted static files stored in the cloud.
In the healthcare sector, data security, governance, and quality are crucial for maintaining patient privacy and ensuring the highest standards of care. At Florida Blue, the leading health insurer of Florida serving over five million members, there is a multifaceted network of care providers, business users, sales agents, and other divisions relying on the same datasets to derive critical information for multiple applications across the enterprise. However, maintaining consistent data governance and security for protected health information and other extended data attributes has always been a complex challenge that did not easily accommodate the wide range of needs for Florida Blue’s many business units. Using Apache Ranger, we developed a federated Identity & Access Management (IAM) approach that allows each tenant to have their own IAM mechanism. All user groups and roles are propagated across the federation in order to determine users’ data entitlement and access authorization; this applies to all stages of the system, from the broadest tenant levels down to specific data rows and columns. We also enabled audit attributes to ensure data quality by documenting data sources, reasons for data collection, date and time of data collection, and more. In this discussion, we will outline our implementation approach, review the results, and highlight our “lessons learned.”
The value of the fast growing class of big data technologies is the ability to handle high velocity and volumes of data. However, a lack of robust security and auditing capabilities are holding organizations back from fully using the potential of these systems. Learn how you can use Big Data technologies to help you meet this compliance and data protection challenge head on so you can return to innovating for competitive advantage.
Using InfoSphere Guardium and BigInsights, we'll show you how you can meet your Hadoop security, compliance and audit requirements.
On the Application of AI for Failure Management: Problems, Solutions and Algo...Jorge Cardoso
Artificial Intelligence for IT Operations (AIOps) is a class of software which targets the automation of operational tasks through machine learning technologies. ML algorithms are typically used to support tasks such as anomaly detection, root-causes analysis, failure prevention, failure prediction, and system remediation. AIOps is gaining an increasing interest from the industry due to the exponential growth of IT operations and the complexity of new technology. Modern applications are assembled from hundreds of dependent microservices distributed across many cloud platforms, leading to extremely complex software systems. Studies show that cloud environments are now too complex to be managed solely by humans. This talk discusses various AIOps problems we have addressed over the years and gives a sketch of the solutions and algorithms we have implemented. Interesting problems include hypervisor anomaly detection, root-cause analysis of software service failures using application logs, multi-modal anomaly detection, root-cause analysis using distributed traces, and verification of virtual private cloud networks.
This document presents a high-level data warehouse, business intelligence, and reporting strategy for CDCR. It defines key terms, lists references and sources of information, and scopes the project. The strategy will define a lifecycle for a DW implementation, leverage industry best practices, and align with CDCR's existing systems and strategic needs over three phases. It seeks to improve data quality, governance, and performance metrics for decision making.
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFiDataWorks Summit
This document discusses using Apache NiFi to build a high-speed cyber security data pipeline. It outlines the challenges of ingesting, transforming, and routing large volumes of security data from various sources to stakeholders like security operations centers, data scientists, and executives. It proposes using NiFi as a centralized data gateway to ingest data from multiple sources using a single entry point, transform the data according to destination needs, and reliably deliver the data while avoiding issues like network traffic and data duplication. The document provides an example NiFi flow and discusses metrics from processing over 20 billion events through 100+ production flows and 1000+ transformations.
Multi-tenant Hadoop - the challenge of maintaining high SLASDataWorks Summit
In shared configuration, the same Hadoop environment supports many applications. Each has
specific requirements and criticality (SLA). Yet they all rely on an assembly of shared application
bricks.
At the same time, the life cycle of a cluster is not static in time. It evolves horizontally, with the
arrival of new applications, but also vertically, as the applications grow in load or evolve in
terms of functionality.
With this in mind, a multi-tenant production cluster presents several challenges including and
not limited to:
- Maintain a high level of SLA for a set of use cases with heterogeneous needs
- Plan and implement the architecture evolution of a cluster in production to ensure the
maintenance of SLA throughout the integration of new use cases on it
EDF will present how it manages this heterogeneity of SLA inherent of any Big Data cluster. EDF
is focusing on how it is renovating its cluster, its organization, its processes and its approach in
order to deliver a platform with strong SLA throughout its life cycle.
Speaker
Edouard Rousseaux, Tech Lead, EDF
Enabling data dynamic and indirect mutual trust for cloud computing storage s...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
3 guiding priciples to improve data securityKeith Braswell
This document discusses the need for organizations to adopt a holistic approach to data security and compliance. It outlines three guiding principles: 1) Understand and define where sensitive data resides across the enterprise. 2) Secure and protect enterprise databases and monitor and audit data access. 3) Continuously monitor systems to demonstrate compliance to auditors. The document argues that a systematic, proactive approach is needed to address the growing threats to data security from sophisticated hackers, increased regulations, and the explosion of data sources and types in today's complex IT environments.
Ciso round table on effective implementation of dlp & data securityPriyanka Aash
The document discusses an effective implementation of data loss prevention (DLP) and data security. It covers key factors like the evolving threat landscape, business drivers for DLP, common challenges, and approaches to solve data security issues. An effective methodology is proposed, including identifying critical data and channels, deploying suitable policies, monitoring incidents, and establishing governance through continuous review and improvement. Critical success factors include business involvement, a phased implementation approach, and repeating the plan-do-check-act cycle periodically. The expected project outcomes are protection of critical channels, improved data tracking and awareness, and happier customers and auditors.
Lessons learned from over 25 Data Virtualization implementationsDenodo
Watch full webinar here: https://bit.ly/327fzQ0
If you have been part of the Denodo community for a while, you likely have heard of SimplicityBI (now part of the BDO family). This expert firm located in Canada has done over 25 implementations of Denodo across North America in over 10 different industries.
The document discusses cloud computing risks and mitigation strategies. It provides an overview of cloud computing definitions and models. It then discusses several key risks to cloud computing like privileged user access, data segregation, regulatory compliance, and the physical location of data. For each risk, it proposes potential mitigation strategies to evaluate like access controls, encryption, understanding regulatory obligations, and considering data location.
Digital transformations require a new hybrid cloud—one that’s open by design, and frees clients to choose and change environments, data and services as needed. This approach allows cloud apps and services to be rapidly composed using the best relevant data and insights available, while maintaining clear visibility, control and security—everywhere. How do you decide where to put data on a hybrid cloud and how to use it? What’s the best hybrid cloud strategy in terms of data and workload? How should you leverage a 50/50 rule or a 80/20 rule and user interaction to evaluate which data/workload to move to the cloud and which data/workload to keep on-premise? Hybrid cloud provides an open platform for innovation, including cognitive computing. Organizations are looking for taking shadow IT out of the shadows by providing a self-service way to the information and a hybrid cloud strategy is allowing that. Also, how to use hybrid cloud for better manage data sovereignty & compliance?
It's All about Insight: Unlocking Effective Risk Management for Your Unstruct...Veritas Technologies LLC
Ransomware, data breaches, and credential hi-jacking can all initiate severe information crises--and put your unstructured data at serious risk. Vision is not a security conference, but that doesn't change the fact that you must monitor data at rest to keep your organization safe. This session will show you how Veritas Data Insight delivers the risk intelligence you need to keep all of your information safe--and make your CISO friends jealous.
Continuously improving factory operations is of critical importance to manufacturers. Consider the facts: the total cost of poor quality amounts to a staggering 20% of sales (American Society of Quality), and unplanned downtime costs plants approximately $50 billion per year (Deloitte).
The most pressing questions are: which process variables effect quality and yield and which process variables predict equipment failure? Getting to those answers is providing forward thinking manufacturers a leg up over competitors.
The speakers address the data management challenges facing today's manufacturers, including proprietary systems and siloed data sources, as well as an inability to make sensor-based data usable.
Integrating enterprise data from ERP, MES, maintenance systems, and other sources with real-time operations data from sensors, PLCs, SCADA systems, and historians represents a major first step. But how to get started? What is the value of a data lake? How are AI/ML being applied to enable real time action?
Join us for this educational session, which includes a view into a roadmap for an open source industrial IoT data management platform.
Key Takeaways:
• Understand key use cases commonly undertaken by manufacturing enterprises
• Understand the value of using multivariate manufacturing data sources, as opposed to a single sensor on a piece of equipment
• Understand advances in big data management and streaming analytics that are paving the way to next-generation factory performance
IRJET-Auditing and Resisting Key Exposure on Cloud StorageIRJET Journal
1. The document discusses auditing and resisting key exposure in cloud storage. It proposes a new framework called an auditing protocol with key-exposure resilience that allows integrity of stored data to still be verified even if the client's current secret key is exposed.
2. It formalizes the definition and security model for such a protocol and proposes an efficient practical construction. The security proof and asymptotic performance analysis show the proposed protocol is secure and efficient.
3. Key techniques used include periodic key updates, homomorphic linear authenticators, and a novel authenticator construction to boost forward security and provide proof of retrievability with the current design.
IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)Denny Muktar
This is the slide for IBM Partner Event, November 2015.
Digital Transformation, Innovation, and Industry Transformer through Hybrid Cloud. IBM Scenarios of Hybrid Cloud and Roadmap .An example of how Enterprise can get into Hybrid Cloud through simple Dev/Test Private Cloud as the start.
EMEA10: Trepidation in Moving to the CloudCompTIA UK
Today’s buzz centres on cloud computing. What is it exactly? Will it dent your revenues or does it have potential to add capabilities to your business? How do you deliver value when you don’t “install” anything? Learn how to use this new approach to delivering IT services in your business, what to consider and where it makes sense – and where it doesn’t! Dave Sobel, CEO of Evolve Technologies, talks to you about how to develop cloud offerings and how you position your business for growth around online services. Strategies come from real life experience, industry data, and collaboration with other solution providers to give you the best way to take on the big, bad cloud.
Digital Business Transformation for Energy & Utility companyIlham Ahmed
The document discusses digital business transformation for energy and utilities companies driven by trends like cloud computing, big data, and mobility. It outlines how a digital technology foundation is necessary to achieve benefits like higher revenue, margins, and customer experience through digital operations excellence. Specifically, it recommends developing a strategy and comprehensive technical architecture using cloud, big data, and mobility platforms to drive innovation and shareholder value.
This document provides an outline and overview of cloud computing research conducted by Sand Hill Group. It discusses how cloud computing is a disruptive innovation that levels the playing field for small companies. The document analyzes the current state and future outlook of the cloud market, including predictions that 40% of workloads will be in the cloud within 3 years. It also covers implications of cloud computing for customers and vendors, including how it changes IT operations and business models. Key cloud service models like Infrastructure as a Service, Platform as a Service, and Software as a Service are discussed.
Cover Your Apps! Surviving in the Age of the Hyperscale Public CloudsZenoss
Join guest Forrester Research Analyst Dave Bartoletti, and Zenoss Alliance Strategist Kent Erickson as they discuss the age of hybrid IT, what it means for your IT organization, and how you can build an Intelligent Data Center on top of and despite the major players.
Developing a cloud strategy - Presentation Nexon ABC EventNexon Asia Pacific
This document provides an overview of moving business operations to the cloud. It discusses the benefits of cloud computing including addressing common challenges faced by customers around delivering required services, managing complex infrastructure, and maintaining up-to-date systems. The document also covers cloud transformation patterns, different cloud service models, and how Microsoft Azure can provide availability on demand to empower businesses. Overall, the document promotes cloud computing and Microsoft Azure as ways for businesses to extend their datacenters, achieve true hybrid cloud solutions, and dynamically respond to business needs.
Piloting The Cloud: Acting on OMB's Mandate - RightNow TechnologiesNitin Badjatia
This document discusses piloting cloud computing initiatives within government agencies. It begins by defining cloud computing and outlining its key characteristics. It then discusses the potential benefits to agencies, such as reduced costs, scalability, and focusing on core missions rather than technology. The document recommends agencies start by piloting opportunities in areas like communications, portals, content management, and analytics. It provides examples of cloud-based case studies that delivered savings and efficiencies. It positions RightNow as an experienced provider of cloud-based customer service solutions to over 160 government customers.
Presentation from Chesapeake Regional Tech Council\'s TechFocus Seminar on Cloud Security; Presented by Scott C Sadler, Business Development Executive - Cloud Computing, IBM US East Mid-Market & Channels on Thursday, October 27, 2011. http://www.chesapeaketech.org
This document discusses cloud computing architecture and strategies for digital business transformation. It outlines how cloud computing can help CIOs accelerate innovation, lower costs, and reduce risk to meet business objectives. The document then describes different cloud models (IaaS, PaaS, SaaS) and provides examples of technical architectures for VMware and OpenStack private clouds. It emphasizes that success requires starting with a well-defined cloud strategy and developing a comprehensive technical design.
Aitp presentation ed holub - october 23 2010AITPHouston
This presentation from Gartner discusses 10 top IT infrastructure and operations trends for organizations to watch. The trends covered include virtualization, big data, energy efficiency, unified communications, staff retention, social networks, legacy migrations, compute density, cloud computing, and converged fabrics. For each trend, the presentation provides details on how the trend affects organizations and recommendations on how to prepare and respond. The overall message is that IT leaders need to be aware of these emerging trends and develop strategies to leverage and adapt to them.
The document announces a Neo4j GraphTalks event in February 2016 focusing on semantic networks. The agenda includes an introduction to graph databases and Neo4j, a presentation on semantic product data management at Schleich, and a talk on building semantic networks quickly with Structr and Neo4j. An open discussion period will follow with additional speakers.
There is currently a 30percent/ 70percent split between public and private cloud engagements; however, over the next two years, respondents see the use of data and information produced by cloud customers more than doubling, with a corresponding decrease in exclusive internal use.
Ken Johnson of Red Hat discusses how Red Hat supports the Internet of Things (IoT) through open source solutions. Red Hat participates in upstream open source projects, integrates those projects into community platforms, and commercializes supported products and solutions. Red Hat helps enterprises collect, communicate, transform, store and act on data from IoT devices through open source solutions that provide enterprise-level security, reliability and scalability while avoiding proprietary lock-in.
There has been a lot of talk around the concept of Cloud. However, what is there behind the hype and how can cloud help companies transform to the digital enterprise. Cloud is not just about technology, it's about the transformation of your applications so they take full advantage of the technology they are hosted on. This presentation served as support to a keynote I gave in at the Belnet Networking Conference in Brussels on October 23rd, 2014.
Intel and Cloudera: Accelerating Enterprise Big Data SuccessCloudera, Inc.
The data center has gone through several inflection points in the past decades: adoption of Linux, migration from physical infrastructure to virtualization and Cloud, and now large-scale data analytics with Big Data and Hadoop.
Please join us to learn about how Cloudera and Intel are jointly innovating through open source software to enable Hadoop to run best on IA (Intel Architecture) and to foster the evolution of a vibrant Big Data ecosystem.
Protecting What Matters...An Enterprise Approach to Cloud SecurityInnoTech
This document discusses cloud security from an enterprise perspective. It begins by outlining trends in security threats facing organizations and the challenges of managing risk. It then provides guidance on taking a risk-based approach to cloud security, designing applications securely for the cloud, and conducting ongoing auditing and management. The key recommendations are to understand your risk profile, architect for security in cloud environments, implement robust identity and access management, confirm compliance obligations, and define clear security responsibilities between customers and cloud service providers.
Presentation given at OpexCon in Prague this October, titled Incorporating Cloud Computing for Enhanced Communication. In it I'm discussing how cloud computing and technology can help enterprises build operational excellence
You wouldn't be surprised if i told you that we do live in interesting times. New business models are created at the same pace today at which older ones are being destroyed. Technology is no longer just an enabler for business, it has become the business for most organizations. In this session we will touch upon some of the challenges and opportunities that the cloud has to offer. The cloud (IaaS, PaaS, SaaS) as we know it offers organizations immense opportunity in terms of reducing time to market on delivering engaging customer experiences but with all of that agility a move to the cloud also brings numerous challenges, some obvious and some not very obvious. In this session we will go over challenges engineering systems for the cloud including a case study engineering a complex legacy application for the cloud.
Building and managing secure private and hybrid clouds
HP Helion extends beyond just cloud to become the very fabric of your enterprise. Delivers an extensible and open portfolio to build and manage enterprise grade end-to-end orchestrated cloud services.
Similar to Cloud Computing: Security, Privacy and Trust Aspects across Public and Private Sectors (20)
The document discusses HP's threat analytics and visualization solutions for analyzing big DNS security data. It describes the large volume and scale of DNS data, challenges in analyzing it with traditional tools, and HP's solution to capture, store, filter, analyze and visualize DNS events in real-time and historically. The solution includes pilots with HP to detect bad devices, domain names and threats through techniques like anomaly detection and connection graphing.
The document discusses HP's DNS Malware Analytics solution, which analyzes DNS network traffic to detect malware and security threats. It began as a research project at HP Labs and has grown into a commercial product. The solution captures DNS packets, analyzes them for blacklisted domains and abnormal patterns using security analytics, and provides alerts and visualizations to help security teams detect threats early. It has been piloted with HP IT and customers and is now offered as a software-as-a-service cloud solution to help security operations centers.
Security intelligence using big data presentation (engineering seminar)Marco Casassa Mont
An overview of R&D work in the space of cyber security, focusing on technologies and case studies in the space of cyber security, big data for security, predictive analytics and usage of security intelligence for better situational awareness
The document discusses policies and policy management. It defines a policy as a set of rules that guide decisions and actions. Policy management involves defining, enforcing, and monitoring compliance with policies. The document also describes Hewlett-Packard's research in policy management solutions for enterprise privacy, identity management, and information lifecycle management.
This document discusses using big data analysis of DNS data to improve cybersecurity operations. It describes how DNS data generates terabytes of logs daily that are difficult to analyze due to scale. The document proposes a solution to collect and filter DNS packets directly from network taps, analyze the data in real-time and historically using Hadoop and other tools to detect anomalies and threats, and use the insights to update blacklists and block malicious traffic. Diagrams show how the system would integrate with existing security tools and orchestrate analytical workflows.
Why Psychological Safety Matters for Software Teams - ACE 2024 - Ben Linders.pdfBen Linders
Psychological safety in teams is important; team members must feel safe and able to communicate and collaborate effectively to deliver value. It’s also necessary to build long-lasting teams since things will happen and relationships will be strained.
But, how safe is a team? How can we determine if there are any factors that make the team unsafe or have an impact on the team’s culture?
In this mini-workshop, we’ll play games for psychological safety and team culture utilizing a deck of coaching cards, The Psychological Safety Cards. We will learn how to use gamification to gain a better understanding of what’s going on in teams. Individuals share what they have learned from working in teams, what has impacted the team’s safety and culture, and what has led to positive change.
Different game formats will be played in groups in parallel. Examples are an ice-breaker to get people talking about psychological safety, a constellation where people take positions about aspects of psychological safety in their team or organization, and collaborative card games where people work together to create an environment that fosters psychological safety.
This presentation by OECD, OECD Secretariat, was made during the discussion “Competition and Regulation in Professions and Occupations” held at the 77th meeting of the OECD Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found at oe.cd/crps.
This presentation was uploaded with the author’s consent.
1.) Introduction
Our Movement is not new; it is the same as it was for Freedom, Justice, and Equality since we were labeled as slaves. However, this movement at its core must entail economics.
2.) Historical Context
This is the same movement because none of the previous movements, such as boycotts, were ever completed. For some, maybe, but for the most part, it’s just a place to keep your stable until you’re ready to assimilate them into your system. The rest of the crabs are left in the world’s worst parts, begging for scraps.
3.) Economic Empowerment
Our Movement aims to show that it is indeed possible for the less fortunate to establish their economic system. Everyone else – Caucasian, Asian, Mexican, Israeli, Jews, etc. – has their systems, and they all set up and usurp money from the less fortunate. So, the less fortunate buy from every one of them, yet none of them buy from the less fortunate. Moreover, the less fortunate really don’t have anything to sell.
4.) Collaboration with Organizations
Our Movement will demonstrate how organizations such as the National Association for the Advancement of Colored People, National Urban League, Black Lives Matter, and others can assist in creating a much more indestructible Black Wall Street.
5.) Vision for the Future
Our Movement will not settle for less than those who came before us and stopped before the rights were equal. The economy, jobs, healthcare, education, housing, incarceration – everything is unfair, and what isn’t is rigged for the less fortunate to fail, as evidenced in society.
6.) Call to Action
Our movement has started and implemented everything needed for the advancement of the economic system. There are positions for only those who understand the importance of this movement, as failure to address it will continue the degradation of the people deemed less fortunate.
No, this isn’t Noah’s Ark, nor am I a Prophet. I’m just a man who wrote a couple of books, created a magnificent website: http://www.thearkproject.llc, and who truly hopes to try and initiate a truly sustainable economic system for deprived people. We may not all have the same beliefs, but if our methods are tried, tested, and proven, we can come together and help others. My website: http://www.thearkproject.llc is very informative and considerably controversial. Please check it out, and if you are afraid, leave immediately; it’s no place for cowards. The last Prophet said: “Whoever among you sees an evil action, then let him change it with his hand [by taking action]; if he cannot, then with his tongue [by speaking out]; and if he cannot, then, with his heart – and that is the weakest of faith.” [Sahih Muslim] If we all, or even some of us, did this, there would be significant change. We are able to witness it on small and grand scales, for example, from climate control to business partnerships. I encourage, invite, and challenge you all to support me by visiting my website.
This presentation by OECD, OECD Secretariat, was made during the discussion “Pro-competitive Industrial Policy” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/pcip.
This presentation was uploaded with the author’s consent.
This presentation by OECD, OECD Secretariat, was made during the discussion “The Intersection between Competition and Data Privacy” held at the 143rd meeting of the OECD Competition Committee on 13 June 2024. More papers and presentations on the topic can be found at oe.cd/ibcdp.
This presentation was uploaded with the author’s consent.
This presentation by Professor Giuseppe Colangelo, Jean Monnet Professor of European Innovation Policy, was made during the discussion “The Intersection between Competition and Data Privacy” held at the 143rd meeting of the OECD Competition Committee on 13 June 2024. More papers and presentations on the topic can be found at oe.cd/ibcdp.
This presentation was uploaded with the author’s consent.
This presentation by Nathaniel Lane, Associate Professor in Economics at Oxford University, was made during the discussion “Pro-competitive Industrial Policy” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/pcip.
This presentation was uploaded with the author’s consent.
This presentation by Professor Alex Robson, Deputy Chair of Australia’s Productivity Commission, was made during the discussion “Competition and Regulation in Professions and Occupations” held at the 77th meeting of the OECD Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found at oe.cd/crps.
This presentation was uploaded with the author’s consent.
This presentation by OECD, OECD Secretariat, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Tim Capel, Director of the UK Information Commissioner’s Office Legal Service, was made during the discussion “The Intersection between Competition and Data Privacy” held at the 143rd meeting of the OECD Competition Committee on 13 June 2024. More papers and presentations on the topic can be found at oe.cd/ibcdp.
This presentation was uploaded with the author’s consent.
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This presentation by Juraj Čorba, Chair of OECD Working Party on Artificial Intelligence Governance (AIGO), was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
XP 2024 presentation: A New Look to Leadershipsamililja
Presentation slides from XP2024 conference, Bolzano IT. The slides describe a new view to leadership and combines it with anthro-complexity (aka cynefin).
This presentation by Katharine Kemp, Associate Professor at the Faculty of Law & Justice at UNSW Sydney, was made during the discussion “The Intersection between Competition and Data Privacy” held at the 143rd meeting of the OECD Competition Committee on 13 June 2024. More papers and presentations on the topic can be found at oe.cd/ibcdp.
This presentation was uploaded with the author’s consent.
This presentation by Thibault Schrepel, Associate Professor of Law at Vrije Universiteit Amsterdam University, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Yong Lim, Professor of Economic Law at Seoul National University School of Law, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
Carrer goals.pptx and their importance in real lifeartemacademy2
Career goals serve as a roadmap for individuals, guiding them toward achieving long-term professional aspirations and personal fulfillment. Establishing clear career goals enables professionals to focus their efforts on developing specific skills, gaining relevant experience, and making strategic decisions that align with their desired career trajectory. By setting both short-term and long-term objectives, individuals can systematically track their progress, make necessary adjustments, and stay motivated. Short-term goals often include acquiring new qualifications, mastering particular competencies, or securing a specific role, while long-term goals might encompass reaching executive positions, becoming industry experts, or launching entrepreneurial ventures.
Moreover, having well-defined career goals fosters a sense of purpose and direction, enhancing job satisfaction and overall productivity. It encourages continuous learning and adaptation, as professionals remain attuned to industry trends and evolving job market demands. Career goals also facilitate better time management and resource allocation, as individuals prioritize tasks and opportunities that advance their professional growth. In addition, articulating career goals can aid in networking and mentorship, as it allows individuals to communicate their aspirations clearly to potential mentors, colleagues, and employers, thereby opening doors to valuable guidance and support. Ultimately, career goals are integral to personal and professional development, driving individuals toward sustained success and fulfillment in their chosen fields.
Earlier I said that we want to create a virtualization system that could be attested to, i.e. that we could make a strong statement as to the trustworthiness of it’s current state. So I want to spend a few moments expanding on this.
Explain what a chain of trust is. We want to build systems that are immune from s/w attacks. So we build a chain of trust which is anchored in h/w which gives us a resilience to s/w attacks. It starts with the TPM (crypto device) that is bound to the mother board and we guarantee that this device will be in a known state when initially powered on. Associated with this is a Core Root of Trust for Measurement (CRTM), which is the BIOS boot block code; it can’t itself be measured but it is a piece of code which is considered trustworthy. It reliably measures integrity value of other code, and stays unchanged during the lifetime of the platform. CRTM is an extension of normal BIOS, which will be run first to measure other parts of the BIOS block before passing control. The BIOS then measures hardware, and the bootloader and passes control to the bootloader. The bootloader measures VMM kernel and pass control to the VMM and so on. What you end up with is a chain of trust with a measurement value that can be used for attestation.
TPM stores measurements and can cryptographically report on those measurements to requesting parties (attestation). Essentially, the TPM signs the measurement (which is a cryptographic hash) so that the one asking for the measurement can know that it was measured by a real TPM. The requestor then checks this measurement against a known good value to determine whether or not this system can be trusted.
This is an important feature of these TCG TPMs but one that has yet not been fully exploited. What we are doing within our project is to create an Integrity Measurement and Attestation framework. Specifically designed for measuring the VMM and its supporting security services so that it can attest itself to other platforms that request verification. At its lowest level it will utilize TCG TPM hardware technology and associated CPU / Chipset support such as the Intel (TXT) / AMD (SVM) for DRTM (Dynamic Root of Trust) mechanisms [Grawrock 2006]. Our planned approach diverges from existing integrity measurement systems in regard to its explicit support for the needs of virtualized systems such as chains of trust that can be safely dynamically modified [Cabuk et al. 2008a] and the support for tying the integrity of several VMs together into a single attestable and verifiable entity.
TXT allows us, in combination with the TPM, to ensure that either a Measured Launch Environment or Controlled Launch Environments can be started. MLEs allow any code sequence to run, but generate a launch record which is difficult to forge by an alternative startup sequence. Controlled Launch allows us to refuse to start a particular code image unless the hardware has followed an already approved execution path. We have some functional code which demonstrates MLE, and the functionality to enforce CLE is being developed now.
Most security strategy, policy and investments decisions are based on intuition and best practices.
Security Analytics is about using scientific methods to make security management rigorous and evidence based.
We believe this is more necessary as information security gets harder.
With cloud computing, virtualization, consumerization, more business reliance on IT – and pressure on the IT budget - it gets harder to justify any expenditure, and yet with the burgeoning threat environment this must be done.
Yes, we can continue to try harder, but it feels like a change in approach is needed, one where we get smarter – hence security analytics.
Today most security teams have good knowledge about IT and are working hard to align this with business knowledge.
We are looking to take this further to make business aligned security decisions based on simulation and prediction. To support this we are using appropriate economic and mathematical tools
This is part of an ongoing ambitious research programme, and our first deliverable is to offer a packaged Security Analytics services engagement, together with the tools and methodology, for both Vulnerability and Threat Management, and also for Identity and Access Management.
Starting with an initial workshop to explore your unique security challenges and identify the strategic priorities, appropriate models will be created and explored to determine the possible outcomes of key security decisions which are available to you. At the end of the exercise you will receive a full report documenting the challenges addressed, the options explored and conclusions drawn.