Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Leveraging AI, Machine Learning and Virtualization to build a chain of trust from the device to the cloud in 5G

With the emergence of Multi-Access (formerly Mobile) Edge Computing and (for example) smart city type use cases, the role of a data broker can emerge at the mobile edge whereby data will be collectively analysed based upon its sensitivity. For example, a temperature at a given location could be used by different entities hosting applications at the mobile edge and this could automatically be used as part of their analytics to anticipate an increase/decrease in energy usage needs, a need to grit the roads etc. The characteristics of a data set (e.g. is it public/private/confidential, the service providing the data…) as well as the integrity protection of the data and metadata itself (for verification purposes) will need to be made available securely to the applications at the Multi-Access edge which may need to leverage it. The true promise of 5G and Multi-Access Edge Computing will only be fulfilled if collected data can be shared for analysis and a chain of trust must be assured around this process.
The IoT revolution brings extreme diversity around use cases, with a broad range of new devices which have different security needs, capabilities and price-points. A single one-size-fits-all solution for security will not work in this space and the requirements for security will need to be customised from end-to-end per segment around the sensitivity of the data and the automated decisions that will be based upon it.

Security is like an insurance policy which provides a suitable level of assurance against attacks and their business consequences.
Finding the right security combination for a given segment is a balancing act between the security in the device and security at the core.

Related Books

Free with a 30 day trial from Scribd

See all
  • Be the first to comment

Leveraging AI, Machine Learning and Virtualization to build a chain of trust from the device to the cloud in 5G

  1. 1. Paul Bradley – Head of 5G Strategy 29th of June 2017 Building a chain of trust from the device to the cloud
  2. 2. Trust is vital – and it’s what we provide… …enabling our clients to deliver a vast range of trusted digital services for billions of individuals and things. 2
  3. 3. Gemalto’s role in Network Security & Software Licensing 3 Gemalto secures the device and enhances security of the virtualized network whilst guaranteeing licensing management OUR SOLUTIONS User authentication and trusted identities Data encryption and key management Cloud and virtualization security Monetization Solutions
  4. 4. Insights are the new oil of 5G 4
  5. 5. 5 The capacity to gain an accurate and deep intuitive understanding of a person or thing Insights = +
  6. 6. 6 Insights = THE MORE DATA, THE BETTER ALGORITHMS, THE MORE INSIGHTS +
  7. 7. INSIGHTS IMPROVE INSIGHTS 7 MULTI-ACCESS EDGE AND VIRTUAL CORE MACHINE LEARNING AI
  8. 8. Requirements 8 DATA COLLECTION DATA PROTECTION
  9. 9. 9
  10. 10. Apps at the edge individually consolidate useful data and send it to the core cloud or directly to the SP cloud 10 How do we exchange data between apps hosted in isolated network slices to improve our insights? VNFVNFAPP VNFVNFAPP VNFVNFAPP
  11. 11. Welcome to B2B Data Brokerage 11
  12. 12. Welcome to B2B Data Brokerage 11 METADATA MAY DESCRIBE SOME OF THE THINGS BELOW: - Type - Description - Location - Structure - Price / Subscription - Source device - Date / time (past or forecast) - Trusted seller METADATA 110011010010010001110 000111101011100110100 100100011100001111001 010100011100001111001 001100011100001111010 100011100001111001101 001001000111000011110 101110011010010010001 PORTABLE DATA
  13. 13. Welcome to B2B Data Brokerage 11
  14. 14. data value 12 RISK END-TO-END MOBILE NETWORK + SERVICE PROVIDER SECURITY FRAMEWORK security
  15. 15. data value 12 RISK END-TO-END MOBILE NETWORK + SERVICE PROVIDER SECURITY FRAMEWORK What automated actions will be triggered on the basis of the insights from the data? Authenticity Privacy Confidentiality Integrity
  16. 16. To conclude… 13 Data and insight brokerage opens new opportunities for the industry to cross-monetize data and improve everyone’s insights by leveraging machine learning and AI. Establish trust between entities, encrypt all data at rest or in transit. Choose your end-to-end data and metadata security architecture wisely based upon the value of the data being transmitted or exchanged and don’t only consider the device bill of materials. Gemalto is focused on security at the device, multi- access edge and the core with an appropriate footprint per 5G segment meeting both MNO and Service Provider requirements. We’re working with the entire industry to continue to secure next generation mobile communications.
  17. 17. Thank you Come and see us at Booth W4.D56 You can find me on 14

    Be the first to comment

    Login to see the comments

  • SebastienViolette1

    Jun. 30, 2017

With the emergence of Multi-Access (formerly Mobile) Edge Computing and (for example) smart city type use cases, the role of a data broker can emerge at the mobile edge whereby data will be collectively analysed based upon its sensitivity. For example, a temperature at a given location could be used by different entities hosting applications at the mobile edge and this could automatically be used as part of their analytics to anticipate an increase/decrease in energy usage needs, a need to grit the roads etc. The characteristics of a data set (e.g. is it public/private/confidential, the service providing the data…) as well as the integrity protection of the data and metadata itself (for verification purposes) will need to be made available securely to the applications at the Multi-Access edge which may need to leverage it. The true promise of 5G and Multi-Access Edge Computing will only be fulfilled if collected data can be shared for analysis and a chain of trust must be assured around this process. The IoT revolution brings extreme diversity around use cases, with a broad range of new devices which have different security needs, capabilities and price-points. A single one-size-fits-all solution for security will not work in this space and the requirements for security will need to be customised from end-to-end per segment around the sensitivity of the data and the automated decisions that will be based upon it. Security is like an insurance policy which provides a suitable level of assurance against attacks and their business consequences. Finding the right security combination for a given segment is a balancing act between the security in the device and security at the core.

Views

Total views

674

On Slideshare

0

From embeds

0

Number of embeds

3

Actions

Downloads

25

Shares

0

Comments

0

Likes

1

×