This document discusses self-sovereign identity management using zero-knowledge proofs and blockchain technology. It proposes a scheme where individuals own and control their personal data through a decentralized identity system. Intermediaries could verify relationships and attributes about an identity through zero-knowledge proofs without learning the underlying data. Blockchain consensus protocols and smart contracts would enforce accountability and transparency around data access and usage according to individuals' preferences. This framework aims to give individuals sovereignty over their digital identities and personal data.

1. © Hitachi, Ltd. 2020. All rights reserved.
A Secure Decision-Support Scheme for
Self-Sovereign Identity Management
SCIS 2020, Kochi, Japan – Session: 4E2 認証・ID管理
January 31st, 2020
Dr. Sven Wohlgemuth Hitachi, Ltd. R&D Group
Prof. Dr. Katsuyuki Umezawa Shonan Institute of Technology
Dr. Yusuke Mishina AIST CPSEC
Dr. Kazuo Takaragi AIST CPSEC

2. 1© Hitachi, Ltd. 2020. All rights reserved.
Data Protection: From Login to Usage of Data
Productivity
Amount of data
PC Era
Web 1.0
Web 2.0
Web 3.0
Web 4.0
Desktop
The World Wide Web
The Social Web
The Semantic Web
The Intelligent Web
Transparency
Compliance
to contracts
Human-machine interaction
Machine-machine interaction
One-factor
identification
Multi-factor
identification
Reputation
Centralized data processing
Ubiquitous data processing
Client/Server data processing
... with automatic
decision support
Putting humans
back in control
In following Radar Networks & Nova Spivack, 2007; E. Brynjolfsson and A. McAfee, Race against the Machine, 2011.

3. 2© Hitachi, Ltd. 2020. All rights reserved.
Data Protection: Chance and Risk for Intermediary
Data
provider
Data
consumer
Data
provider
Data
consumer
Decision on transaction depends on
data aggregation / inference of information
Problem: No control on data usage
dAlice
dAlice, d*Alice
SOX
eIDAS
Regulation
Accountability &
Transparency
on access to data
Identity
Master
identity
private
public
Qualification
Friends
Finance
Health
...
Alice

4. 3© Hitachi, Ltd. 2020. All rights reserved.
MIT / W3C: Data Ownership & Data Portability
Data
provider
Data
consumer
Data
provider
Alice
Delegation of accountability
Personal Online Datastore
(POD) server
Guard (Enforcement of access rights)
Social graph
POD Charlie
https://charlie.incrupt.n
et/...
POD Bob
https://bob.incrupt.net/.
..POD Alice
https://alice.incrupt.net
Master identity
Qualification
Finance
Health
Friends
If “friend” then delegate rights on dAlice
Data ownership:
Accountability to
data provider
Alice: Master
identity
Bob: Master
identity
Required: Digital evidence about data usage
Data ownership:
Accountability to
data provider
d*Alice
data breach/
misuse?

5. 4© Hitachi, Ltd. 2020. All rights reserved.
Digital Evidence: Entscheidungsproblem
Theory of computation
Predicate logic
of 2nd order
Predicate logic
of 1st order
Propositional
logic
Relationship
No relation 1:n
Knowledge
Information
Data
Is claimed “friend” = defender or attacker?
1:n:m
Security language?
Undecidable
• Goedel: Incompleteness
theorems
• Turing: Halting problem
DBMS
Typed access matrix with ORCON language
Access matrix /
NP-complete
problem
Proof-carrying code
Zero-knowledge proof
Language-based
security
Transform to
Mathematical induction
Equality: Identity relation F
𝑎 = 𝑏 ≡ ∀𝐹 𝐹 𝑎 = 𝐹 𝑏

6. 5© Hitachi, Ltd. 2020. All rights reserved.
Mathematical Induction: Entscheidungsproblem
1. Basis step n=1: Secure database
2. Induction hypothesis for n:
Friend = True identity and policy enforcement
3. Inductive step n → n+1: Friend = Linked user
Dolev-Yao security model: Assume data breach/misuse (“You’re not a friend”)
Security mechanisms:
• Typed access control with mutual exclusion
• Byzantine Fault Tolerance with hash chain
• Certification with digital signature
Security mechanisms:
• (Sub) Graph isomorphism for equality
• Data Provenance
• Zero-Knowledge Proof Data
provider
Data
consumer
Data
provider
(dAlice, EncAlice) (dBob, EncBob)
dAlice, enc(dAlice,,
DecAlice)
Is data to be proven
true?
Zero-
knowledge
proof
Delega
tion of
rights
Access
history
Equality of graphs
Data
consumer
Entscheidungsproblem

7. 6© Hitachi, Ltd. 2020. All rights reserved.
Interim Result: We have a Byzantine Consensus Problem
Data
provider
Data
consumer
Data
provider
Data
consumer
Data
provider
Data
consumer
Data
provider
Data
consumer
Goal: Majority of computations agrees on information
Case 1: Intermediary fails Case 2: A user fails
Assumption:
Bob is not a friend
Bob is not a
friend
Faked dBob
Bob is not a
friend
Is Bob a friend? Is Bob a friend?
System Risk: False Negative and False Positive → Other consensus required
dBob: Bob is a
friend
Claim:
Bob is a friend
Assumption:
Bob is not a friend
Claim:
Bob is a friend

8. 7© Hitachi, Ltd. 2020. All rights reserved.
From now on: Humans as Oracle
Data
consumer
Data
provider
Oracle
Data
consumer
Data
provider
Computation: Turing Machine Enhanced by Oracle Realized by Humans
• Complete solution of decidable problems
• Reasoning with data provenance
• Solves decision and functional problems
• Used in security proof with attacker
• Expert decision-making
• Providing personal data
Qualification
Contract: Institution of open market economy
• Property rights and competition
• Consensus: Declaration of intent (e.g. NDA)
• Freedom to enter
• Adaptable to changes
dAlice,
d*Alice
Rights
Required: Protection against (IT) system risks

9. 8© Hitachi, Ltd. 2020. All rights reserved.
From now on: Assume You’re a Friend
Verifier Prover
Alice
Challenge: You’re a friend
Challenge: Show relation of master identity to
a) Equality of some data sharing OR
b) All of Alice’s credentials
Response: Digital evidence on
contract-compliant use of data
Response: Contract-related knowledge on
a) Sub graph isomorphism to master identity
b) Relations of master identity
Anonymized observations
Zero-
knowledge
proof
In following: M. Blum, “How to Prove a Theorem So No One Else Can Claim It”, Proc. Int. Congress of Mathematics, 1986.
Attacker has to solve
NP-complete problem
Entscheidungsproblem
Delegated rights & use

10. 9© Hitachi, Ltd. 2020. All rights reserved.
From now on: Secure Search by Reasoning
Search for “friend”
PoW by
Auditors …
Public ledgers Anonymized
data
provenance
Search result:
Base security score by Social
Graph on Bob’s data processing
Search result:
Base security score by Social
Graph on Bob’s data processing
Hyperledger
Data
provider
Data
consumer
BobAlice
Accountability &
Transparency on use of data
dAlice,
d*Alice
Rights
Decision:
If “friend” then
Secure Kernel 4 Supply
Chains (SK4SC)
by ZKP, Hysteresis Digital
Signature, and competition for
royalties on using identity
S. Wohlgemuth, K. Takaragi, I. Echizen,
Privacy with Secondary Use of Personal Information, 2016.
K. Takaragi, S. Wohlgemuth, 暗号技術と量子コン
ピュータ開発・「現状と課題」を考える, 久保田隆 (編
集), ブロックチェーンをめぐる実務・政策と法, 2018.
S. Wohlgemuth, K. Umezawa, Y. Mishina, K. Takaragi.
Competitive Compliance with Blockchain, 2019.
S. Wohlgemuth, K. Umezawa, K. Takaragi,
Secure Sharing of Design Information, 2018.

11. 10© Hitachi, Ltd. 2020. All rights reserved.
From now on: Chance for Intermediaries by Privacy
Alice
Financial auditors, …
Physicians, …
Advisors, …
Economy
Energy
Healthcare
Control on data usage by compliance to contracts
Royalties for rights on using authentic information
Data
provider
dAlice
nym1
nym2
nym3
nym1
nym2
nym3
宝木 和夫、ウォルゲムト スベン、久保田 隆、三科 雄介、梅澤 克之、
渡邊 創, ブロックチェーンを用いた規制克服技術の考察 – A Study
of RegTech with blockchain, SCIS 2020.
CA
Auditor
Master identity
Qualification

12. 11© Hitachi, Ltd. 2020. All rights reserved.
Conclusion for Self-Sovereign Identity Management
• Usage control enhances identity management for the Web
• By Byzantine consensus with contracts on data use and sharing with royalties
• By Transparency of secure delegation of rights with Zero-Knowledge Proof and SK4SC
• So that an attacker must solve the Entscheidungsproblem and NP-complete problem
• Without digital evidence on compliance for data originating from data breach/misuse
Data
provider
Data
consumer
Data
provider
Data
consumer
dAlice dAlice, d*Alice

15. 14© Hitachi, Ltd. 2020. All rights reserved.
Zero-Knowledge Proof (ZKP)
• Proof of language membership & proof of knowledge of information
• Probabilistic proof system between 2 parties on graph isomorphism
• Prover is scalable in computing and can show only true statement
• Verifier gets no additional knowledge on original graph
U. Feige, A. Fiat, A. Shamir, “Zero-Knowledge Proofs of Identity”, 1998.
S. Goldwasser, S. Micali, C. Rackoff, “The Knowledge Complexity of Interactive Proof Systems”, 1989
O. Goldreich, S. Micali, A. Widgerson, “Proofs that Yield Nothing But Their Validity or All Languages in NP Have Zero-Knowledge Proof Systems”, 1991.
Verifier
2. a
3. c random out of {0,1}
4. c
5. r:= t + cm mod q
6. r
7. Check if gr = ahc
pkVerifier := (p, q, g, h)
ChallengeResponse
Prover
1. t random, a:=gt
pkVerifier := (p, q, g, h)
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