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docs: update ccc whitepaper link
The link to the previous version was broken. Replacing with the latest version v1.3 of the whitepaper. Signed-off-by: Paul Meyer <49727155+katexochen@users.noreply.github.com>
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committed by
Tobin Feldman-Fitzthum
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a5f8b349a1
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@@ -48,7 +48,7 @@ therefore refer to and build on trust and security models already defined.
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For example:
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- Confidential Computing Consortium (CCC) published
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"[A Technical Analysis of Confidential Computing](https://confidentialcomputing.io/wp-content/uploads/sites/85/2021/03/CCC-Tech-Analysis-Confidential-Computing-V1.pdf)"
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"[A Technical Analysis of Confidential Computing](https://confidentialcomputing.io/wp-content/uploads/sites/10/2023/03/CCC-A-Technical-Analysis-of-Confidential-Computing-v1.3_unlocked.pdf)"
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section 5 of which defines the threat model for confidential computing.
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- CNCF Security Technical Advisory Group published
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"[Cloud Native Security Whitepaper](https://github.com/cncf/tag-security/blob/main/security-whitepaper/v2/CNCF_cloud-native-security-whitepaper-May2022-v2.pdf)"
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@@ -61,7 +61,7 @@ The commonality between confidential containers project and confidential computi
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the ability for unauthorised access to data and code inside TEEs sufficiently such that this path
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is not an economically or logically viable attack during execution (5.1 Goal within the CCC
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publication
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[A Technical Analysis of Confidential Computing](https://confidentialcomputing.io/wp-content/uploads/sites/85/2021/03/CCC-Tech-Analysis-Confidential-Computing-V1.pdf)).
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[A Technical Analysis of Confidential Computing](https://confidentialcomputing.io/wp-content/uploads/sites/10/2023/03/CCC-A-Technical-Analysis-of-Confidential-Computing-v1.3_unlocked.pdf)).
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This means our trust and threat modelling should
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- Focus on which aspects of code and data have integrity and/or confidentiality protections.
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@@ -13,7 +13,7 @@ In identifying personas we consider :
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Security as Cloud, Cluster, Container and Code. However data is core to confidential
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containers rather than code.
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- The Confidential Computing Consortium paper
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[A Technical Analysis of Confidential Computing v1.1](https://confidentialcomputing.io/wp-content/uploads/sites/85/2021/03/CCC-Tech-Analysis-Confidential-Computing-V1.pdf)
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[A Technical Analysis of Confidential Computing](https://confidentialcomputing.io/wp-content/uploads/sites/10/2023/03/CCC-A-Technical-Analysis-of-Confidential-Computing-v1.3_unlocked.pdf)
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defines Confidential Computing as the protection of data in use by performing computations in a
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hardware-based Trusted Execution Environment (TEE).
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@@ -163,7 +163,7 @@ the same workload (or parts such as logging/monitoring etc) can be re-used with
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sets to provide a service/solution. In the case of bespoke workload, the workload provider and
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Data Owner may be the same persona. As mentioned the Data Owner must have a level of
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trust in the Workload Provider to use and expose the data provided in an expected and approved
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manner. Page 10 of [A Technical Analysis of Confidential Computing v1.1](https://confidentialcomputing.io/wp-content/uploads/sites/85/2021/03/CCC-Tech-Analysis-Confidential-Computing-V1.pdf)
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manner. Page 10 of [A Technical Analysis of Confidential Computing](https://confidentialcomputing.io/wp-content/uploads/sites/10/2023/03/CCC-A-Technical-Analysis-of-Confidential-Computing-v1.3_unlocked.pdf)
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, suggests some approaches to establish trust between them.
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The TEE boundary allows the introduction of secrets but just as we recognised the
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@@ -197,4 +197,3 @@ some cases these may not be identical. For example data may be provided to a wor
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analysis and results to be made available to an end user. The original data is never provided
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directly to the end user but the derived data is, in this case the data owner can be different
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from the end user and may wish to protect this data from the end user.
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