Internet DRAFT - draft-yang-teep-tee-dp
draft-yang-teep-tee-dp
TEEP P. Yang
Internet-Draft China Mobile
Intended status: Informational T. Pang
Expires: 5 October 2023 Huawei Technology Co.,Ltd.
X. Zhang
AntGroup
3 April 2023
Trusted Execution Environment Distributed Provisioning Protocol
draft-yang-teep-tee-dp-00
Abstract
In big data area, computing resource manager like MESOS[MESOS],
YARM[YARN], kubernets[Kubernetes] or computing framework like
Spark[Spark], use Master-Worker structure to split computing task.
In the master component, the computing task will be splited into
different child tasks. Each of thess child tasks will be loaded to a
executor which is managed by Worker. The Master and Worker are
usually exist as cluster, cloud or other distributed framework. When
the big data tasks needs to be processed in TEE in lifecycle, this
document could be used for Master to provision child tasks in
distributed TEEs.
Status of This Memo
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This Internet-Draft will expire on 5 October 2023.
Copyright Notice
Copyright (c) 2023 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 2
3. Use cases . . . . . . . . . . . . . . . . . . . . . . . . . . 3
4. Architecture . . . . . . . . . . . . . . . . . . . . . . . . 3
5. TEE Distributed Provisioning Protocol . . . . . . . . . . . . 4
5.1. TEE Resource Request/Response . . . . . . . . . . . . . . 5
5.2. TEE Secure Channel Request/Response . . . . . . . . . . . 7
6. Security Considerations . . . . . . . . . . . . . . . . . . . 8
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 8
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 8
8.1. Normative References . . . . . . . . . . . . . . . . . . 8
8.2. Informative References . . . . . . . . . . . . . . . . . 9
Appendix A. Appendix 1 Full CDDL of TEE DP protocol . . . . . . 9
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 12
1. Introduction
In big data area, different from stand-alone applications, big data
application always need to be splitted into different child tasks by
Master in big data computing framework. Then these tasks will be
deployed to executors in local or remote by Workers. TEE could be
used to protect the application and its secret data during the
process, if only the whole process lifecycle is covered by TEE.
Before running big data application, it is hard to predict how many
computing resources are needed. Similarly, TEE resource also needs
to be provisioned during the application process lifecycle. This
document specifies the architecture and protocol of how big data
computing framework provision and use TEE during application process
lifecycle. The Trusted Execution Environment Provisioning (TEEP)
architecture document [I-D.ietf-teep-architecture] provides design
guidance and introduces the necessary terminology.
2. Terminology
The following terms are used:
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* Big Data Computing Framework: An framework that is responsible for
managing and spliting big data computing task, like Spark,
MapReduce[MapReduce], etc. Usually, Big Data Computing Framework
has its own Computing Resource Manage Framework. Like Spark
supports standalone deploy mode.
* Computing Resource Manage Framework: An framework that is
responsible for managing and scheduling computing resource in
cluster, like YARN, MESOS and Kubernetes.
* Master: The entity in Computing Resource Manage Framework that is
responsible for splitting computing task into different child
tasks, and allocating computing resource to those child tasks.
* Executor: The executing entity that is responsible for executing
child tasks in Worker. The current executor includes process,
container and VM.
* Worker: The entity that is responsible for undertaking child tasks
and manage Executors. Other terms like TAM, TEE, REE, TA will
reuse the term definition defined in [I-D.ietf-teep-architecture].
3. Use cases
In federated machine learning, participants want to create a unified
machine learning model without leaking private data owned by each
other. TEE as a hardware based technology could make sure data
inside this environment is integrated and confidential. If the
federated machine learning participants trust this TEE and its TA,
they could gather their data in that TEE and generate the final
machine learning model. The architecture and protocol described in
this document could be used in the federated machine learning
scenario, and make sure the lifecycle of machine learning process is
protected by TEE.
4. Architecture
The following figure shows the architecture of TEE distributed
provisioning. In this architecture, Master is the management center
of big data Computing Resource Management Framework. it also plays
the role of TAM in TEEP architecture. When Master starts running big
data applications, it forwards TEE computing resource request to
Worker by TEE-DP protocol. Worker then occupies TEE computing
resource and generate Executor which is running inside TEE.
Meanwhile, TEE-DP protocol also includes secure channel negotiation
message. Based on the secure channel between TAM and Executor, TEEP
protocol could provision child tasks generated by Master securely.
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+--------+
+----------------->| Master |<------------------+
| | /TAM | |
| +--------+ |
| ^ |
| | |
|TEE-DP +-------+ TEE-DP|
|protocol |TEEP protocol protocol|
| | |
v v v
+---------+ +----------+ +----------+ +--------+
| Worker |<-->| Executor | | Executor |<-->| Worker |
+---------+ +----------+ +----------+ +--------+
| TEE | | TEE |
+----------+ +----------+
Figure 1: TEEP Broker Models
5. TEE Distributed Provisioning Protocol
As described in architecture section, TEE distributed provisioning
protocol has two message packages: TEE resource request/responses,
TEE secure channel request/response. The message framework is shown
below in CDDL format.
tee-dp-message = $tee-dp-message-type .within tee-dp-message-framework
tee-dp-message-framework = [
type: $tee-dp-type,
optionis: { * tee-dp-option}
]
tee-dp-option = (uint =>any)
$tee-dp-message-type /= tee-resource-request
$tee-dp-message-type /= tee-resource-response
$tee-dp-message-type /= tee-secure-channel-resquest
$tee-dp-message-type /= tee-secure-channel-response-direct
$tee-dp-message-type /= tee-secure-channel-response-indirect
$tee-dp-type = uint .size 1
TEE-resource-request = 1
TEE-resource-response = 2
TEE-secure-channel-request = 3
TEE-secure-channel-response-direct = 4
TEE-secure-channel-response-indirect = 5
Figure 2: TEE DP Message Framework
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5.1. TEE Resource Request/Response
TEE resource request/response message is used by Master/TAM and
Worker to negotiate TEE computing resource. The resource request
message is sent by Master/TAM, then the Worker response this message.
The only mandantory option in request message is MEMORY-size. Other
items like CPU core number, CPU frequency, CPU architecture, memory
encryption method and memory isolation method are optional. Another
message that is mandantory in response message is TOKEN-tee-instance,
which represents the identity of selected TEE instance. This token
could be public key of AIK(attestation identity key) or otehr
identity information. The relevant CDDL fragment is shown below.
The complete CDDL structure is shown in Appendix.
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memory-encryption-method = &(
hardware-based: 0,
software-based: 1,
none: 2
)
memory-isolation-method = &(
hardware-based: 0,
software-based: 1,
none: 2,
)
cpu-architecture = &(
sgx-based: 0,
sev-based: 1,
trustzone-based: 2,
other: 3,
)
tee-resource-request = [
type: TEE-resource-request
options:{
? CPU-core-number: uint .size 1
? CPU-frequency: unit .size 2
? CPU-arch: uint .bits cpu-architecture
;the cpu frequency unit is MHZ
MEMORY-size: uint .size 4
;the memory size unit is MB
? Requested-memory-encryption-method: uint .bits memory-encryption-method
? Requested-memory-isolation-method: uint .bits memory-isolation-method
}
]
tee-resource-response = [
type: TEE-resource-response
options:{
? CPU-core-number: uint .size 1
? CPU-frequency: unit .size 2
? MEMORY-size: uint .size 4
? TOKEN-tee-instance: bstr .size 4
;this token represents the identity of TEE, it could be a public key of AIK
? Requested-memory-encryption-method: uint .bits memory-encryption-method
? Requested-memory-isolation-method: uint .bits memory-isolation-method
}
]
{：#res-req title="TEE DP Resource Request Response " }
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5.2. TEE Secure Channel Request/Response
Before executing TEEP protocol between Master/TAM and Executor in TEE
DP architecutre, secure channel needs to be established first. There
are two kinds of secure channel in TEE DP architecture, direct and
indirect. Direct means Master/TAM direct connect with Executor by
network, which also means the TEE of Executor support network
communication, like TLS. Indirect means the Master/TAM and Executor
connect with each other by other components like TEEP broker, or
Worker. Master/TAM and Executor could transfer encrypted packages
like COSE, JWE, by that component. The CDDL fragment is shown below.
secure-channel-negotiation-type= &(
direct: 0;
indirect: 1;
)
tee-secure-channel-resquest = [
type: TEE-secure-channel-request
options:{
TOKEN-tee-instance:
Secure-channel-negotiation-type: $$negotiation-type
}
]
$$negotiation-type //= {
direct: bool
ip-type: bool ;true is ipv4, false is ipv6
}
$$negotiation-type //= {
indirect: bool
Protocol-name => uint .bits protocol-name
}
$$ipaddr //= (
ipv4: bstr .size 4
)
$$ipaddr //= (
ipv6: bstr .size 16
)
direct-extensions = (uint => any)
tee-secure-channel-response-direct = [
type: TEE-secure-channel-response-direct
options:{
$$ipaddr
port => uint .size 1
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*direct-extensions
}
]
&protocol-name &= (
cose: 0,
jwe: 1,
others: 2,
)
indirect-extentions = (uint => any)
tee-secure-channel-response-indirect = [
type: TEE-channel-response-indirect
options:{
Protocol-name => uint .bits protocol-name
*indirect-extensions
}
Figure 3: TEE DP Secure Channel Negotiation
6. Security Considerations
The trust domain of TEE DP architecture is Master/TAM and Executor
running in TEE. The Worker component do not have to be trusted by
Master/TAM since it is only used for creating Executor and monitoring
runtime status. The security of secure channel based on the secure
channel negotiation mechanism which is out of the scope of this
document.
7. IANA Considerations
TBD.
8. References
8.1. Normative References
[I-D.ietf-teep-architecture]
Pei, M., Tschofenig, H., Thaler, D., and D. M. Wheeler,
"Trusted Execution Environment Provisioning (TEEP)
Architecture", Work in Progress, Internet-Draft, draft-
ietf-teep-architecture-19, 24 October 2022,
<https://datatracker.ietf.org/doc/html/draft-ietf-teep-
architecture-19>.
[I-D.ietf-teep-protocol]
Tschofenig, H., Pei, M., Wheeler, D. M., Thaler, D., and
A. Tsukamoto, "Trusted Execution Environment Provisioning
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(TEEP) Protocol", Work in Progress, Internet-Draft, draft-
ietf-teep-protocol-12, 13 March 2023,
<https://datatracker.ietf.org/doc/html/draft-ietf-teep-
protocol-12>.
[I-D.ietf-teep-usecase-for-cc-in-network]
Yang, P., chenmeiling, Su, L., and T. Pang, "TEEP Usecase
for Confidential Computing in Network", Work in Progress,
Internet-Draft, draft-ietf-teep-usecase-for-cc-in-network-
02, 20 October 2022,
<https://datatracker.ietf.org/doc/html/draft-ietf-teep-
usecase-for-cc-in-network-02>.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/rfc/rfc2119>.
8.2. Informative References
[Kubernetes]
Community, K., "Kubernetes Cloud Controller Manager", 17
December 2022,
<https://kubernetes.io/docs/concepts/architecture/cloud-
controller/>.
[MapReduce]
Community, A. M., "MapReduce Overview", 27 July 2022,
<https://hadoop.apache.org/docs/current/hadoop-mapreduce-
client/hadoop-mapreduce-client-core/
MapReduceTutorial.html#Overview>.
[MESOS] Community, A. M., "MESOS Architecture", 2 March 2023,
<https://mesos.apache.org/documentation/latest/
architecture/>.
[Spark] Community, S., "Spark Overview", 2 March 2023,
<https://spark.apache.org/docs/3.3.2/cluster-
overview.html>.
[YARN] Community, A. H., "Apache Hadoop YARN", 29 July 2022,
<https://hadoop.apache.org/docs/current/hadoop-yarn/
hadoop-yarn-site/YARN.html>.
Appendix A. Appendix 1 Full CDDL of TEE DP protocol
The full CDDL of TEE distributed provisioning protocol is shown
below.
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tee-dp-message = $tee-dp-message-type .within tee-dp-message-framework
tee-dp-message-framework = [
type: $tee-dp-type,
optionis: { * tee-dp-option}
]
tee-dp-option = (uint =>any)
$tee-dp-message-type /= tee-resource-request
$tee-dp-message-type /= tee-resource-response
$tee-dp-message-type /= tee-secure-channel-resquest
$tee-dp-message-type /= tee-secure-channel-response-direct
$tee-dp-message-type /= tee-secure-channel-response-indirect
$tee-dp-type = uint .size 1
TEE-resource-request = 1
TEE-resource-response = 2
TEE-secure-channel-request = 3
TEE-secure-channel-response-direct = 4
TEE-secure-channel-response-indirect = 5
memory-encryption-method = &(
hardware-based: 0,
software-based: 1,
none: 2
)
memory-isolation-method = &(
hardware-based: 0,
software-based: 1,
none: 2,
)
tee-resource-request = [
type: TEE-resource-request
options:{
CPU-core-number: uint .size 1
CPU-frequency: unit .size 2
;the cpu frequency unit is MHZ
MEMORY-size: uint .size 4
;the memory size unit is MB
? Requested-memory-encryption-method: uint .bits memory-encryption-method
? Requested-memory-isolation-method: uint .bits memory-isolation-method
}
]
tee-resource-response = [
type: TEE-resource-response
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options:{
CPU-core-number: uint .size 1
CPU-frequency: unit .size 2
MEMORY-size: uint .size 4
TOKEN-tee-instance: bstr .size 4
;this token represents the identity of TEE, it could be a public key of AIK
? Requested-memory-encryption-method: uint .bits memory-encryption-method
? Requested-memory-isolation-method: uint .bits memory-isolation-method
}
]
secure-channel-negotiation-type= &(
direct: 0;
indirect: 1;
)
tee-secure-channel-resquest = [
type: TEE-secure-channel-request
options:{
TOKEN-tee-instance:
Secure-channel-negotiation-type: $$negotiation-type
}
]
$$negotiation-type //= {
direct: bool
ip-type: bool ;true is ipv4, false is ipv6
}
$$negotiation-type //= {
indirect: bool
Protocol-name => uint .bits protocol-name
}
$$ipaddr //= (
ipv4: bstr .size 4
)
$$ipaddr //= (
ipv6: bstr .size 16
)
direct-extensions = (uint => any)
tee-secure-channel-response-direct = [
type: TEE-secure-channel-response-direct
options:{
$$ipaddr
port => uint .size 1
*direct-extensions
}
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]
&protocol-name &= (
cose: 0,
jwe: 1,
others: 2,
)
indirect-extentions = (uint => any)
tee-secure-channel-response-indirect = [
type: TEE-channel-response-indirect
options:{
Protocol-name => uint .bits protocol-name
*indirect-extensions
}
]
; labels of mapkey for tee dp message parameters, uint (0..15)
CPU-core-number = 0
CPU-frequency = 1
MEMORY-size = 2
Requested-memory-encryption-method = 3
Requested-memory-isolation-method = 4
TOKEN-tee-instance = 5
Secure-channel-negotiation-type = 6
direct = 7
indirect = 8
ip-type = 9
Protocol-name = 10
ipaddr = 11
port = 12
direct-extensions = 13
indirect-extensions = 14
Figure 4: Full CDDL of TEE Distributed Provisioning Protocol
Authors' Addresses
Penglin Yang
China Mobile
No.32 Xuanwumen West Street
Beijing
China
Email: yangpenglin@chinamobile.com
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Ting Pang
Huawei Technology Co.,Ltd.
127 Jinye Road, Yanta District
Xi'an
China
Email: pangting@huawei.com
Xiaomeng Zhang
AntGroup
World Financial Center, No.1 East 3rd Ring Middle Road, Chaoyang District
Beijing
China
Email: zhangxiaomeng.zxm@antgroup.com
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