IoT Edge Intelligence - The need for new software development approachesBart Jonkers
CeBIT 2016 talk on "IoT Edge Intelligence - The need for new software development approaches".
In order to bridge the 'IoT skills gap' or solve the 'IT vs OT' divide, the IoT market needs to enable traditional IT developers to move into the OT (operational technology) world. In the OT world, devices, gateways and machines run embedded software on proprietary operating systems, using unfamiliar communications protocols in resource constraint environments. To enable a large community of developers to build intelligent IoT edge applications, abstraction from these domain specific technologies and complexities is required. Bitreactive offers visual developer tooling to highly simplify the application development on devices and the way edge devices integrate to IoT sensors, cloud services, analytics, visualization services etc.
(Some technologies supported: MQTT, AMQP, BLE, Zigbee, OPC-UA, Paho, Californium, Kura, Coap, JSON-RPC, LoRA, Bluetooth, IBM Bluemix, IBM IoT Foundation, Microsoft Azure, AWS, Oracle IoT Cloud Service, GE Predix, GE Predix machine, Xively, Solair, Geofencing, Modbus, GPIO, RaspberryPI, XMPP, Eurotech Reliagate, Eurotech ESF, PLC, SCADA, DELL 5000, Intel IoT gateway, Multitech conduit, Java SE, openJDK, OSGi, Kura, Eclipse IoT, Embedded Java, Oauth 2.0, alternative to Node Red)
Solving Industrial Data Integration with Machine IntelligenceBit Stew Systems
Bit Stew Systems offers the premier platform that is leveraging machine intelligence to solve the data integration challenge in the Industrial Internet of Things (IIoT).
Analytics is becoming increasingly important for industrial companies. Solving the data integration challenge is the foundation of an analytics strategy and platform. The integration platform must be versatile in ingesting any data type from any data source of any quality level.
At WomenWhoCode, 2019 https://india.womenwhocode.dev/agenda/
Edge Computing: What, Why, How and Where
Edge Analytics: What, Why, benefits, limitations
Edge computing vs Edge Analytics
Edge Analytics use-cases
If you are looking for any company having professional guides who helps you in research topics in IOT then contact with us-Techsparks. Our professors will assist you on various master thesis topics in industrial IoT offers top demanding research ideas for scholars. For more information call us at-91-9465330425 and visit us at: https://bit.ly/3gPmEtb.
A Survey on Security and Privacy Issues in Edge Computing-Assisted Internet o...DESMOND YUEN
Internet of Things (IoT) is an innovative paradigm
envisioned to provide massive applications that are now part of
our daily lives. Millions of smart devices are deployed within
complex networks to provide vibrant functionalities including
communications, monitoring, and controlling of critical infrastructures. However, this massive growth of IoT devices and the corresponding huge data traffic generated at the edge of the network created additional burdens on the state-of-the-art
centralized cloud computing paradigm due to the bandwidth and
resources scarcity. Hence, edge computing (EC) is emerging as
an innovative strategy that brings data processing and storage
near to the end users, leading to what is called EC-assisted IoT.
Although this paradigm provides unique features and enhanced
quality of service (QoS), it also introduces huge risks in data security and privacy aspects. This paper conducts a comprehensive survey on security and privacy issues in the context of EC-assisted IoT. In particular, we first present an overview of EC-assisted IoT including definitions, applications, architecture, advantages, and challenges. Second, we define security and privacy in the context of EC-assisted IoT. Then, we extensively discuss the major classifications of attacks in EC-assisted IoT and provide possible solutions and countermeasures along with the related research efforts. After that, we further classify some security and privacy issues as discussed in the literature based on security services and based on security objectives and functions. Finally, several open challenges and future research directions for secure EC-assisted IoT paradigm are also extensively provided.
IoT Edge Intelligence - The need for new software development approachesBart Jonkers
CeBIT 2016 talk on "IoT Edge Intelligence - The need for new software development approaches".
In order to bridge the 'IoT skills gap' or solve the 'IT vs OT' divide, the IoT market needs to enable traditional IT developers to move into the OT (operational technology) world. In the OT world, devices, gateways and machines run embedded software on proprietary operating systems, using unfamiliar communications protocols in resource constraint environments. To enable a large community of developers to build intelligent IoT edge applications, abstraction from these domain specific technologies and complexities is required. Bitreactive offers visual developer tooling to highly simplify the application development on devices and the way edge devices integrate to IoT sensors, cloud services, analytics, visualization services etc.
(Some technologies supported: MQTT, AMQP, BLE, Zigbee, OPC-UA, Paho, Californium, Kura, Coap, JSON-RPC, LoRA, Bluetooth, IBM Bluemix, IBM IoT Foundation, Microsoft Azure, AWS, Oracle IoT Cloud Service, GE Predix, GE Predix machine, Xively, Solair, Geofencing, Modbus, GPIO, RaspberryPI, XMPP, Eurotech Reliagate, Eurotech ESF, PLC, SCADA, DELL 5000, Intel IoT gateway, Multitech conduit, Java SE, openJDK, OSGi, Kura, Eclipse IoT, Embedded Java, Oauth 2.0, alternative to Node Red)
Solving Industrial Data Integration with Machine IntelligenceBit Stew Systems
Bit Stew Systems offers the premier platform that is leveraging machine intelligence to solve the data integration challenge in the Industrial Internet of Things (IIoT).
Analytics is becoming increasingly important for industrial companies. Solving the data integration challenge is the foundation of an analytics strategy and platform. The integration platform must be versatile in ingesting any data type from any data source of any quality level.
At WomenWhoCode, 2019 https://india.womenwhocode.dev/agenda/
Edge Computing: What, Why, How and Where
Edge Analytics: What, Why, benefits, limitations
Edge computing vs Edge Analytics
Edge Analytics use-cases
If you are looking for any company having professional guides who helps you in research topics in IOT then contact with us-Techsparks. Our professors will assist you on various master thesis topics in industrial IoT offers top demanding research ideas for scholars. For more information call us at-91-9465330425 and visit us at: https://bit.ly/3gPmEtb.
A Survey on Security and Privacy Issues in Edge Computing-Assisted Internet o...DESMOND YUEN
Internet of Things (IoT) is an innovative paradigm
envisioned to provide massive applications that are now part of
our daily lives. Millions of smart devices are deployed within
complex networks to provide vibrant functionalities including
communications, monitoring, and controlling of critical infrastructures. However, this massive growth of IoT devices and the corresponding huge data traffic generated at the edge of the network created additional burdens on the state-of-the-art
centralized cloud computing paradigm due to the bandwidth and
resources scarcity. Hence, edge computing (EC) is emerging as
an innovative strategy that brings data processing and storage
near to the end users, leading to what is called EC-assisted IoT.
Although this paradigm provides unique features and enhanced
quality of service (QoS), it also introduces huge risks in data security and privacy aspects. This paper conducts a comprehensive survey on security and privacy issues in the context of EC-assisted IoT. In particular, we first present an overview of EC-assisted IoT including definitions, applications, architecture, advantages, and challenges. Second, we define security and privacy in the context of EC-assisted IoT. Then, we extensively discuss the major classifications of attacks in EC-assisted IoT and provide possible solutions and countermeasures along with the related research efforts. After that, we further classify some security and privacy issues as discussed in the literature based on security services and based on security objectives and functions. Finally, several open challenges and future research directions for secure EC-assisted IoT paradigm are also extensively provided.
Fog computing security and privacy issues, open challenges, and blockchain so...IJECEIAES
Due to the expansion growth of the IoT devices, Fog computing was proposed to enhance the low latency IoT applications and meet the distribution nature of these devices. However, Fog computing was criticized for several privacy and security vulnerabilities. This paper aims to identify and discuss the security challenges for Fog computing. It also discusses blockchain technology as a complementary mechanism associated with Fog computing to mitigate the impact of these issues. The findings of this paper reveal that blockchain can meet the privacy and security requirements of fog computing; however, there are several limitations of blockchain that should be further investigated in the context of Fog computing.
DeviceHive is an open-source machine to machine (M2M) communication framework, which helps to resolve IoT project problems. We will be talking about the experience we've gathered in DataArt related to the technical issues taking place on different IoT project stages and how we have used this experience to implement the platform useful for both start-ups and enterprise companies.
VMworld vBrownBag vmtn5534e - placement of iot workload operations within a c...Kenneth Moore
The Internet of Things (IoT) represents a disruptive technology that has the potential of changing the way we live in this world forever. Gartner predicts that by the end of 2020, there will be approx. 20 billion Internet-connected things, from smartwatches to smart offices generating traffic to communicate. Central to facilitating communication between these things are the Data-Center’s required to store and process the data that IoT devices will generate. The DC infrastructure facilitates applications such as analytics and customer-oriented applications allowing companies to extract value from data that is produced by IoT devices. While DCs provide an essential part of the jigsaw in supporting IoT, Gartner reported that current DC architectures are not prepared to deal with the scale, volume and heterogeneous nature of data that IoT will bring and will face as a result significant challenges in dealing with workload demands in terms of the storage, compute and network requirements to support IoT. Given this challenge, DCs in the future need to be designed and developed bearing IoT in mind. However, the design of a DC is a non-trivial task, and a thorough understanding of the workload demand of IoT applications is required to build a workload model that describes how the DC performs at its busiest time under load. Such models are essential to: design and optimise the management of resources in the DC; and facilitate performance analysis and simulation allowing DC providers to evaluate the impact that configuration changes have on QoS requirements.
Assisting IoT Projects and Developers in Designing Interoperable Semantic Web...Amélie Gyrard
Assisting IoT Projects and Developers in Designing Interoperable Semantic Web of Things Applications
The 8th IEEE International Conference on Internet of Things (iThings 2015), 11-13 December 2015, Sydney, Australia
Amelie Gyrard, Christian Bonnet, Karima Boudaoud, Martin Serrano
20 Latest Computer Science Seminar Topics on Emerging TechnologiesSeminar Links
A list of Top 20 technical seminar topics for computer science engineering (CSE) you should choose for seminars and presentations in 2019. The list also contains related seminar topics on the emerging technologies in computer science, IT, Networking, software branch. To download PDF, PPT Seminar Reports check the links.
Will Edge Computing IoT Solutions be a Real Trend in 2019?Tyrone Systems
Edge computing is a method of optimizing Internet of Things applications by performing data processing at the edge of the network, near the source of the data. Edge computing IoT technology is attracting huge investments, to ensure security, ruggedness and establish ROI driven use cases.
Minggle Labs is a global software development and service provider.An efficient training will be provided on latest technologies in software and automation products.
What the IoT should learn from the life sciencesBoris Adryan
What the Internet of Things should learn from the life sciences. About the utility of open data, ontologies and public repositories as routinely used in the academic life science, but rarely in the IoT.
DIsampaikan dalam seminar IoT, UPN Veteran Jakarta, 29 September 2018
IoT merupakan salah satu ciri dari revolusi industri 4.0. Definisi, studi kasus IoT di pertanian, energy, building management dan perikanan diberikan contoh. Device dan protocol juga disingung.
MIT Enterprise Forum of Cambridge Connected Things 2017 panel discussion on "IoT Analytics: Using Analytics to Generate High Value from IoT in the Real World"
In this session, we will explore what IoT is and will explore the basics of edge and fog computing.
We will also explore the layered architecture of a standard IoT model in detail, followed by data processing models in IoT. We will also explore what should be the final outcome of an IoT based application.
Data Science London - Meetup, 28/05/15Boris Adryan
Slides from my @ds_ldn talk about Ontologies in the Internet of Things. Note that this is a short version of a talk that I presented earlier this month on O'Reilly Webcasts, still viewable for a while at: http://www.oreilly.com/pub/e/3365
In this presentation, kartik introduces cloud computing and associated trends. In his own words Kartik would like to "work with developing powerful & efficient cryptographic methods or techniques to ensure data integrity , confidentiality & anonymity among the organizations."
Fog computing security and privacy issues, open challenges, and blockchain so...IJECEIAES
Due to the expansion growth of the IoT devices, Fog computing was proposed to enhance the low latency IoT applications and meet the distribution nature of these devices. However, Fog computing was criticized for several privacy and security vulnerabilities. This paper aims to identify and discuss the security challenges for Fog computing. It also discusses blockchain technology as a complementary mechanism associated with Fog computing to mitigate the impact of these issues. The findings of this paper reveal that blockchain can meet the privacy and security requirements of fog computing; however, there are several limitations of blockchain that should be further investigated in the context of Fog computing.
DeviceHive is an open-source machine to machine (M2M) communication framework, which helps to resolve IoT project problems. We will be talking about the experience we've gathered in DataArt related to the technical issues taking place on different IoT project stages and how we have used this experience to implement the platform useful for both start-ups and enterprise companies.
VMworld vBrownBag vmtn5534e - placement of iot workload operations within a c...Kenneth Moore
The Internet of Things (IoT) represents a disruptive technology that has the potential of changing the way we live in this world forever. Gartner predicts that by the end of 2020, there will be approx. 20 billion Internet-connected things, from smartwatches to smart offices generating traffic to communicate. Central to facilitating communication between these things are the Data-Center’s required to store and process the data that IoT devices will generate. The DC infrastructure facilitates applications such as analytics and customer-oriented applications allowing companies to extract value from data that is produced by IoT devices. While DCs provide an essential part of the jigsaw in supporting IoT, Gartner reported that current DC architectures are not prepared to deal with the scale, volume and heterogeneous nature of data that IoT will bring and will face as a result significant challenges in dealing with workload demands in terms of the storage, compute and network requirements to support IoT. Given this challenge, DCs in the future need to be designed and developed bearing IoT in mind. However, the design of a DC is a non-trivial task, and a thorough understanding of the workload demand of IoT applications is required to build a workload model that describes how the DC performs at its busiest time under load. Such models are essential to: design and optimise the management of resources in the DC; and facilitate performance analysis and simulation allowing DC providers to evaluate the impact that configuration changes have on QoS requirements.
Assisting IoT Projects and Developers in Designing Interoperable Semantic Web...Amélie Gyrard
Assisting IoT Projects and Developers in Designing Interoperable Semantic Web of Things Applications
The 8th IEEE International Conference on Internet of Things (iThings 2015), 11-13 December 2015, Sydney, Australia
Amelie Gyrard, Christian Bonnet, Karima Boudaoud, Martin Serrano
20 Latest Computer Science Seminar Topics on Emerging TechnologiesSeminar Links
A list of Top 20 technical seminar topics for computer science engineering (CSE) you should choose for seminars and presentations in 2019. The list also contains related seminar topics on the emerging technologies in computer science, IT, Networking, software branch. To download PDF, PPT Seminar Reports check the links.
Will Edge Computing IoT Solutions be a Real Trend in 2019?Tyrone Systems
Edge computing is a method of optimizing Internet of Things applications by performing data processing at the edge of the network, near the source of the data. Edge computing IoT technology is attracting huge investments, to ensure security, ruggedness and establish ROI driven use cases.
Minggle Labs is a global software development and service provider.An efficient training will be provided on latest technologies in software and automation products.
What the IoT should learn from the life sciencesBoris Adryan
What the Internet of Things should learn from the life sciences. About the utility of open data, ontologies and public repositories as routinely used in the academic life science, but rarely in the IoT.
DIsampaikan dalam seminar IoT, UPN Veteran Jakarta, 29 September 2018
IoT merupakan salah satu ciri dari revolusi industri 4.0. Definisi, studi kasus IoT di pertanian, energy, building management dan perikanan diberikan contoh. Device dan protocol juga disingung.
MIT Enterprise Forum of Cambridge Connected Things 2017 panel discussion on "IoT Analytics: Using Analytics to Generate High Value from IoT in the Real World"
In this session, we will explore what IoT is and will explore the basics of edge and fog computing.
We will also explore the layered architecture of a standard IoT model in detail, followed by data processing models in IoT. We will also explore what should be the final outcome of an IoT based application.
Data Science London - Meetup, 28/05/15Boris Adryan
Slides from my @ds_ldn talk about Ontologies in the Internet of Things. Note that this is a short version of a talk that I presented earlier this month on O'Reilly Webcasts, still viewable for a while at: http://www.oreilly.com/pub/e/3365
In this presentation, kartik introduces cloud computing and associated trends. In his own words Kartik would like to "work with developing powerful & efficient cryptographic methods or techniques to ensure data integrity , confidentiality & anonymity among the organizations."
Insurtech, Cloud and Cybersecurity - Chartered Insurance InstituteHenrique Centieiro
Nov. 2020 presentation on Insurtech, how cloud is enabling insurtech and cybersecurity for cloud and insurtech.
Prepared by Henrique Centieiro for CII - Chartered Insurance Institute Hong Kong
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.
Making Actionable Decisions at the Network's EdgeCognizant
With the vast analytical power unleashed by the Internet of Things (IoT) ecosystem, IT organizations must be able to apply both cloud analytics and edge analytics - cloud for strategic decision-making and edge for more instantaneous response based on local sensors and other technology.
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.
Group 5:
Reymart John Aguho
Lawrence Valdez
Trishia Mae Salazar
Gayle Allyson Guitones
Dempster Winston Corpuz
Matthew Erickson Quinto
Marc Vincent Maneja
Meet up Milano 14 _ Axpo Italia_ Migration from Mule3 (On-prem) to.pdfFlorence Consulting
Quattordicesimo Meetup di Milano, tenutosi a Milano il 23 Maggio 2024 dalle ore 17:00 alle ore 18:30 in presenza e da remoto.
Abbiamo parlato di come Axpo Italia S.p.A. ha ridotto il technical debt migrando le proprie APIs da Mule 3.9 a Mule 4.4 passando anche da on-premises a CloudHub 1.0.
Instagram has become one of the most popular social media platforms, allowing people to share photos, videos, and stories with their followers. Sometimes, though, you might want to view someone's story without them knowing.
2.Cellular Networks_The final stage of connectivity is achieved by segmenting...JeyaPerumal1
A cellular network, frequently referred to as a mobile network, is a type of communication system that enables wireless communication between mobile devices. The final stage of connectivity is achieved by segmenting the comprehensive service area into several compact zones, each called a cell.
Italy Agriculture Equipment Market Outlook to 2027harveenkaur52
Agriculture and Animal Care
Ken Research has an expertise in Agriculture and Animal Care sector and offer vast collection of information related to all major aspects such as Agriculture equipment, Crop Protection, Seed, Agriculture Chemical, Fertilizers, Protected Cultivators, Palm Oil, Hybrid Seed, Animal Feed additives and many more.
Our continuous study and findings in agriculture sector provide better insights to companies dealing with related product and services, government and agriculture associations, researchers and students to well understand the present and expected scenario.
Our Animal care category provides solutions on Animal Healthcare and related products and services, including, animal feed additives, vaccination
Bridging the Digital Gap Brad Spiegel Macon, GA Initiative.pptxBrad Spiegel Macon GA
Brad Spiegel Macon GA’s journey exemplifies the profound impact that one individual can have on their community. Through his unwavering dedication to digital inclusion, he’s not only bridging the gap in Macon but also setting an example for others to follow.
APNIC Foundation, presented by Ellisha Heppner at the PNG DNS Forum 2024APNIC
Ellisha Heppner, Grant Management Lead, presented an update on APNIC Foundation to the PNG DNS Forum held from 6 to 10 May, 2024 in Port Moresby, Papua New Guinea.
Understanding User Behavior with Google Analytics.pdfSEO Article Boost
Unlocking the full potential of Google Analytics is crucial for understanding and optimizing your website’s performance. This guide dives deep into the essential aspects of Google Analytics, from analyzing traffic sources to understanding user demographics and tracking user engagement.
Traffic Sources Analysis:
Discover where your website traffic originates. By examining the Acquisition section, you can identify whether visitors come from organic search, paid campaigns, direct visits, social media, or referral links. This knowledge helps in refining marketing strategies and optimizing resource allocation.
User Demographics Insights:
Gain a comprehensive view of your audience by exploring demographic data in the Audience section. Understand age, gender, and interests to tailor your marketing strategies effectively. Leverage this information to create personalized content and improve user engagement and conversion rates.
Tracking User Engagement:
Learn how to measure user interaction with your site through key metrics like bounce rate, average session duration, and pages per session. Enhance user experience by analyzing engagement metrics and implementing strategies to keep visitors engaged.
Conversion Rate Optimization:
Understand the importance of conversion rates and how to track them using Google Analytics. Set up Goals, analyze conversion funnels, segment your audience, and employ A/B testing to optimize your website for higher conversions. Utilize ecommerce tracking and multi-channel funnels for a detailed view of your sales performance and marketing channel contributions.
Custom Reports and Dashboards:
Create custom reports and dashboards to visualize and interpret data relevant to your business goals. Use advanced filters, segments, and visualization options to gain deeper insights. Incorporate custom dimensions and metrics for tailored data analysis. Integrate external data sources to enrich your analytics and make well-informed decisions.
This guide is designed to help you harness the power of Google Analytics for making data-driven decisions that enhance website performance and achieve your digital marketing objectives. Whether you are looking to improve SEO, refine your social media strategy, or boost conversion rates, understanding and utilizing Google Analytics is essential for your success.
1. iExec V3: A Decentralized Approach
to Dataset Monetization
Eth. Dev. Conf.
Seoul, Korea, 28 Mai, 2019
Gilles Fedak, Eric Rodriguez,
Victor Bonhomme
gf@iex.ec
5. Preserving Data Ownership and Sovereignty
● Data privacy, ownership, sovereignty
is becoming a main concern
● Web3.0 gives more control over user
data.
● Today we talk about Data Renting
https://101blockchains.com/web-3-0-examples
6. iExec - Timeline
ICO - 04/17
Off-chain computing
SDK, Dapp Store,
Dapp Challenge
87M RLC issued
10k BTC raised
V1 - 11/17Background
15 years
in cloud
computing
& HPC
V2 - 05/18 V5V3- 05/19
Data Store
Data Renting
-
Lightweight
workers
-
Mainnet
Marketplace
fog/edge
computing
for IoT
GPU
Bags
of Task
Side chain
V4 -end 19
8. Blockchain-based Decentralized
Cloud Computing
● Decentralized marketplace for computing resources (servers, applications,
datasets)
● Use Ethereum to advertise/provision computing resources
● Providers can interact in a P2P way, without central authority
DATA PROVIDERS
SERVER PROVIDERS
APPLICATION PROVIDERS
Why Does it Matter ?
● Decentralized applications need
an infrastructure
● Cheaper, greener, more efficient
than traditional centralized Cloud
9. The iExec Token: RLC
Token usage
● The RLC Token is the only way to access the iExec decentralized cloud
● Providers are paid with RLC
● Allows to build incentives in the network.
● Issued on main net on April 2017
11. Proof-of-Contribution
staking + reputation + result certification:
• A confidence threshold is associated with each requested execution
• Workers have a reputation
• Before executing a task, workers commit a security deposit (stake)
• The execution confidence threshold is computed by comparing results and computing a
function of the credibility and stake
• Task is duplicated as long as the confidence threshold is not met
• Workers who computed an erroneous results loose their stake
• Workers who correctly compute gains the payments + the losers’ stake
• Reputation is adjusted
12. iExec End-to-End Trusted Execution with Intel SGX
Enclaves: Confines execution and data within a encrypted environment: no
one can access/tamper the execution
● SDK that provides full end-to-end privacy preserving computation
○ for application/input/results
○ guarantee execution integrity
○ provide on-chain enclave execution attestation
18. The data renting concept
INPUT OUTPUTPROCESSING
Data
● trained model
● pretrained model?
● dataset
Application
● ML framework
● load model
● call prediction function
Value +++ Value +
19. Monetize AI model in computer vision
a generic framework?
in a web application
https://nsfw.app.iex.ec
make a prediction
run an application
trained model = dataset
get the result
● classification
● score
● object
detection
...
Input data
24. Share your computing resources: dApps or
datasets
Easy build... for awesome features
AUTOMATIC
PAYMENTS
PRIVATE RUN
SERVERLESS
ACCESS CONTROL
FINE TUNE PRICING / PAY PER TASK
Few line of codes
Blockchain
complexity is
hidden
Thank you very much fo the introduction and the invitation. It’s a great honour to be here. in this talk, I will introduce our new vesion 3, with a focus on decenetralized marrketplace for datasets
The amount of data generated by the humnkind is gowong exponentially. That was the web, information published on-line, then social interaction. In the future, we will see more and more devices connected to the Internet that will generate huge amount of data.
So need for decentralization, we cannot store and process everything in the centralized Cloud
Today main problem issue is that our data are handled by centralized authoities: eitheir Cloud poviders, or application: Facebook, Google etc.
And what we want today is to get control over our data again. This is the promise of web3.0. We want decentralized processing for data.
This as business impact. Today, I want to introduce you a new concept: data renting. You keep ownership of your data and you monetize the usage of your data. This is possible thanks to decentralization, because you control your data, and not someone else.
To introduce iExec. I Was researcher with 15 years background in Clould and HPC. Did our ICO. 25 people. 2 weeks ago we released V3. Mainnet