Decentralized Public Key Infrastructure with Identity Management
using Hyperledger Fabric
Amisha Sinha and Debanjan Sadhya
ABV-Indian Institute of Information Technology and Management Gwalior, India
Public Key Infrastructure, Certificate Authority, Hyperledger Fabric, Decentralized Identifier.
Public key infrastructure (PKI) is one of the most effective ways to protect confidential electronic data on
the internet. In centralized PKIs, the identity is defined by trusted third parties, specifically the Certificate
Authority (CA). However, the security of the end-users becomes jeopardized if the CA gets compromised.
To tackle this problem, the decentralized nature of the system can be used to eliminate a single point of
failure. However, the lack of real-time support, the block complexity, and strict implementation are drawbacks
that burden the practicality of these approaches. This study tries to evaluate the Decentralized Public Key
Infrastructure (DPKI) framework based on a permission-less model. The model itself is constructed over the
decentralized identifier to manage the identity of users. We use the Hyperledger Fabric based blockchain
network to create a hierarchy Certificate Authority, where each CA is a peer in a decentralized distributed
network. Hence, each peer owns a separate database validated by the blockchain. We have evaluated the
model efficacy in terms of the network latency and throughput, which were all found to be acceptable.
Public Key Infrastructures (PKI) rely on digital sig-
nature technology to establish trust and security asso-
ciation parameters between entities. It allows entities
to interoperate with authentication proofs using stan-
dardized digital certificates. Even though many ap-
plications use PKI technology for their security foun-
dations, there are several concerns about their inher-
ent design assumptions based on its centralized trust
model. There have been instances where CAs have is-
sued rogue certificates, or the CAs have been hacked
to issue malicious certificates. Traditional PKIs also
encounter several versions of the Man-in-the-Middle
Attacks (Dacosta et al., 2012). Due to such issues,
there remains a requirement for forgery-proof identity
verification techniques (Salman et al., 2019).
Unlike the traditional approach, Decentralized
Public Key Infrastructure (DPKI) ensures no single
third party can compromise the integrity and secu-
rity of the system as a whole. In blockchain-powered
DPKIs, the new third parties become miners or val-
idators (Isirova and Potii, 2018). The trust is estab-
lished and maintained based on the consensus pro-
tocols. The miners or validators follow the protocol
rules that would financially reward and punish these
third parties, thereby preventing misbehavior in the
blockchain and limiting their roles effectively.
1.1 Contributions
This study aims to build a secure DPKI that im-
proves the existing infrastructures for user privacy
and identity management. Specifically, our frame-
work attempts to solve usability issues like identify-
ing malicious certificates. These certificates can be
consequently used to perform MITM attacks by re-
voking and blacklisting CAs so that no other domain
owner can request certificates from it. We utilize the
blockchain technology over the Hyperledger fabric to
build a web of trust model. This model allows any en-
tity on the network to verify attributes about any other
entity through a trusted network.
The proposed model guarantees security by con-
stantly validating intermediate signing CAs through
other peers. This process enables the certificates to be
produced in a legitimate and unaltered manner. Fur-
thermore, this framework provides a hierarchy Cer-
tificate Authority, in which each CA owns a sepa-
rate database validated by a decentralized-distributed
blockchain. The entities will have unique DIDs, at-
tach their public keys, and write them to the public
ledger. Any person or organization that can discover
these DIDs will be able to access the associated pub-
Sinha, A. and Sadhya, D.
Decentralized Public Key Infrastructure with Identity Management using Hyperledger Fabric.
DOI: 10.5220/0011273000003283
In Proceedings of the 19th International Conference on Security and Cryptography (SECRYPT 2022), pages 554-559
ISBN: 978-989-758-590-6; ISSN: 2184-7711
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
lic keys for verification purposes. Hence, this work
provides an alternative to the conventional CA-based
identity verification model. The efficiency of the so-
lution is measured by the variation in the latency of
requests due to the blockchain transaction flow.
This section briefly discusses solutions based on
DPKI for identity management. Noticeably, the need
for DPKIs and how it can address the usability and
security challenges that plague traditional PKIs has
been extensively reported.
The study by (Salman et al., 2019) compares the
existing DPKI approaches from different perspec-
tives. Even though these systems exist and are open-
source, the authors noted that only a few are utilized
in real-world applications. This study also gives in-
sights into the use of security services for current
applications and highlights the state-of-the-art mech-
anisms that currently provide these services. This
study is concluded by describing the associated chal-
lenges and discussing how the blockchain technology
can resolve them. A public and decentralized PKI
system termed SS-DPKI was proposed by (Chu et al.,
2020). This solution enables a user to utilize public
keys of multiple devices in a single ID.
A ChainPKI system was proposed by (Chiu et al.,
2021), which still had some issues. For instance, the
system uses an IP address as the ID for the relay nodes
(intermediates). Though a user can change their IP
address, it might still reveal some information relat-
ing to the user, like the geographic location. The sys-
tem developed by (Garba et al., 2021) records a set of
trusted CAs, each associated with a specific domain
in the blockchain. A limitation of blockchain-based
PKIs is storing a vast amount of data in the form of
certificates, as well as large handshake message sizes.
The listed works have played an important role
in developing meaningful solutions for replacing cen-
tralized PKIs. However, they do not claim satisfac-
tory results for identity maintenance. Although few
studies have reported promising results (Salman et al.,
2019), they are quite complex and costly to be in-
tegrated into industrial domains. In this regard, our
framework provides an efficient DPKI solution based
on the Hyperledger fabric.
Now we detail some of the technological concepts re-
lated to our study. These preliminaries would facili-
tate in better understanding of our work.
3.1 Public Key Infrastructure
Centralized PKI relies on a trusted third party
called Certificate Authority in the current standard
X.509 (Burr et al., 1996). PKI uses a public and
private key combination to encrypt and decrypt data.
The X.509 certificate has a tree-like structure; it has
a root node and is connected with various branches.
The standard fields in X.509 certificates include the
version number, algorithmic information, validity pe-
riod, name of the CA and name of the subject to
whom the certificate is issued to.
3.2 Decentralized Public Key
A decentralized Public-key Infrastructure is an ap-
proach that removes and separates the power of the
CA. DPKI is a protocol for securely accessing decen-
tralized consensus systems. DPKI changes the web’s
security model from single points of failure to de-
centralized consensus groups that create namespaces.
DPKIs can provide a way to manage attributes for the
web of trust. However, it does not specify what kind
of identifiers should be used. Alternatively, it accepts
different approaches that vary in terms of ease-of-use,
permanence, uniqueness, security, and other proper-
ties. There are four types of identifiers:
Centralized: Controlled by single entity
Federated: Controlled by multiple entity
User-centric: Individual/administrative control
Self-sovereign: Individual control
The Self Sovereign Identity (SSI)
movement uses
a blockchain to address several solution requirements.
The most basic one is for the secure and authentic ex-
change of keys, which was not possible using PKIs.
3.3 Decentralized Identifiers
Decentralized identifiers (DID) are used to globally
identify people and things over the internet. Previous
global unique identifiers mostly include UUIDs and
URNs. However, UUIDs are not globally resolvable
and URNs require a centralized registration authority.
Furthermore, none of these schemes is able to ver-
ify the ownership of the identifier in a cryptographic
manner. In this regard, DIDs are the core component
Decentralized Public Key Infrastructure with Identity Management using Hyperledger Fabric
of an entirely new layer of decentralized digital iden-
tity. The format of DID is presented in Figure 1
Figure 1: The format of DID.
In Figure 1, DID Method is the namespace com-
ponent identifier, and DID Method-Specific Identifier
is the format of the method-specific identifier. In
essence, DID is like a key-value database, where DID
is the key and DID-document is the value. Inter-
estingly, the DID document is a JSON-LD Data (a
JSON-based serialization for Linked Data). The ar-
chitecture of the DID is presented in Figure 2.
Figure 2: An overview of the DID architecture.
3.4 Blockchain
Blockchain is an emerging technology that demon-
strates increased safety and confidentiality through
decentralized, distributed and immutable characteris-
tics. The blockchain is analogous to a digital ledger
that stores transaction data in a distributed and peer-
to-peer model. The data entered into the blockchain
network is arranged in the form of blocks (Yaga et al.,
2018). These blocks are immutable and hold the
timestamp and the cryptographic hash of the previous
block. This mechanism ensures a backward linkage
between successive blocks. The hash generated by
the cryptographic algorithm is foreordained. A slight
modification in the data will change the hash values,
which helps to resist any changes in the blockchain.
Hence, this property allows having data in an open,
public and immutable storage.
The design of the proposed system can be divided into
two parts. Initially, a DPKI framework based on a per-
mission oriented collaborative consortium model us-
ing the Hyperledger Fabric (Androulaki et al., 2018)
is developed. In this framework, all different DPKI
entities and chaincode functions are created. Once a
basic DPKI framework is setup, we integrate it with
DID. We have decided to use the Hyperledger Fabric
since it has a concept of channels and is open-source.
4.1 Chaincode Creation
The Hyperledger Fabric has a smart contract named
chaincode, in which we can define our rules and func-
tions for revocation and management of certificates.
The chaincode can be used to create custom permis-
sioned public or private blockchain. Chaincode ex-
tended attributes are constructed on the basis of the
current PKI system. Interestingly, different features
can be incorporated into different chaincodes as per
the requirement. The most significant property re-
quired is the signature mechanism that is used for
signing certificates. Noticeably, it can be different
from the one used in transaction signing, nodes in the
cooperative CA and others.
It is possible to insert consensus protocols in the
Hyperledger Fabric (Vukolic, 2017). It also has a
novel architecture for transactions, executing order,
and validating. These functions are further explained
as follows:
Execute: The endorser executes the transaction
and verifies its correctness.
Order: Ordering of transactions through the
pluggable consensus protocols.
Validate: Validate transactions through endorse-
ment policies before committing them into the
4.2 Identity Verification Model
DIDs are only the base layer of the decentralized iden-
tity infrastructure. Verifiable Credentials is the next
higher layer where most of the value is unlocked.
DIDs can identify various entities in the Verifiable
Credentials ecosystem, such as issuers, holders, sub-
jects and verifiers. Figure 3 is a visual representation
of the identity credentials verification ecosystem. The
functions of the various sub-modules are:
Issuer: Issues verifiable credentials about a spe-
cific subject.
SECRYPT 2022 - 19th International Conference on Security and Cryptography
Holder: Stores credentials on the behalf of a sub-
Verifier: Requests a profile of the subject.
Identifier Registry: Issues identifiers for sub-
Figure 3: Flowchart of the identity verification model.
For the implementation of the DPKI, the main
changes were made for the signing of DPKI content
in the Endorsement System Chaincode component.
Proxies act as the gateway between external clients
and the DPKI network. A REST API gets exposed
by the Proxy, which enables the clients in issuing and
managing the certificates. The function Cert() that
is used for creating the self signed Root certificate is
presented as follows.
Cert() {
var cert = forge.pki.createCertificate();
cert.publicKey = this.keys.publicKey;
cert.serialNumber = ’01’;
cert.validity.notBefore = new Date();
cert.validity.notAfter = new Date();
validity.notBefore.getFullYear() + 1);
name: ’commonName’,
value: ’CA’
}, {
name: ’organizationName’,
value: "CertificateAuthority"
}, {
shortName: ’C’,
value: ’UK’
name: ’commonName’,
value: ’CA’
}, {
name: ’organizationName’,
value: "CertificateAuthority"
}, {
shortName: ’C’,
value: ’UK’
this.CA = {
privateKey: forge.pki.
return this.CA;
4.3 Certificate Verification Model
In the developed system, it is possible to request sig-
natures from the endorsing peers (seen as a coopera-
tive CA) through a chaincode. A Certificate Signing
Request (CSR) or X.509-v3 certificate is given as the
input for this purpose. Figure 4 is a visual representa-
tion of this model.
Figure 4: The certificate verification signature model.
This section presents a set of experimental evaluations
performed to support the developed framework. We
specifically evaluate the framework performance over
the latency and throughput of the network over var-
ious tasks. Noticeably, latency is defined as the re-
sponse time per transaction, whereas throughput rep-
resents the number of successful transactions per sec-
ond (Kuzlu et al., 2019).
5.1 Evaluation Environment
We used a local server to run the Hyperledger Fabric
based blockchain network and Proxy. Each peer of
this network is a docker container, and we have an-
other dedicated container for its local ledger. There-
fore, two docker containers are allotted to each peer.
Furthermore, we have used a single proxy in the eval-
uations. In all assessments, four orderers were used
Decentralized Public Key Infrastructure with Identity Management using Hyperledger Fabric
in the Byzantine Fault Tolerance (BFT) ordering ser-
vice of the blockchain network (Sousa et al., 2018).
The requests were made through the Proxy REST API
with HTTP.
5.2 Performance Results
The primary aspect in all types of requests to the
DPKI is the variation in the latency of request re-
sponses. The first test analyzes the latency of the
certificate issuing process in the DPKI solution. As
presented in Table 1, we can observe that the latency
suffers the most when we increase the number of
endorsers. The signature reconstruction process in-
creases the latency of certificate signatures. Since we
are working with a blockchain network that contains
complex processes, the latency observed in the ex-
ecuted evaluations was expected. We can attribute
these values while validating and committing trans-
action blocks in the Hyperledger Fabric transaction
flow, mainly during ordering.
Table 1: Latency of the certificate issuing process in the
DPKI solution.
No.of Endorsers Latency (ms)
1 2440
2 2768
4 3489
Our second simulation investigates the latency in
the certificate revocation process. Table 2 shows the
results obtained with different numbers of endorser’s
peers while using the revocation process with a key
size of 4096 bits. We can see that the number of en-
dorser does not significantly increase the total latency
of the requests. The latency in this case is caused due
to the proxy running the chaincode algorithm that ob-
tains the new Certificate revocation List (CRL) and
signatures of the endorsers.
Table 2: Latency of the certificate revocation process the in
DPKI solution.
No. of Endorsers Latency (ms)
1 2220
2 3129
4 3564
For comparing the issuing process with the tradi-
tional issuing of X.509 certificates, we ran a docker
container on the same machine where the blockchain
network and Proxy were running. We did a simple
configuration that enables requests for certificate re-
vocation. In this regard, it should be noted that the
time to enroll an entity is not added since it happens
only in a centralized PKI. Table 3 demonstrates the re-
sults obtained while comparing our DPKI model with
the traditional EJBCA PKI
. These results are ex-
pected since our model’s characteristics and improve-
ments have a performance trade-off. The resulting
latency increases due to the ordering process, com-
munication steps between peers in transactions, and
others factors.
Table 3: Comparison of the latency in certificate issuing
process with traditional PKIs.
Model Name No. of Endorsers Latency (ms)
DPKI 1 2462
DPKI 4 3188
Next, we investigate the impact of the blockchain
network throughput on the Hyperledger Fabric per-
formance. We have utilized the Hyperledger Caliper
Benchmark tool
for this purpose. Figure 5 shows the
impact of the number of participants in the network
on the network throughput for both Open Transac-
tions (where one read and one write transactions were
performed) and Query Transactions (where only one
read transaction was performed). The results demon-
strate that the query transactions have higher through-
put than the open transactions since there is only one
read operation in the query transaction.
Figure 5: Impact of the number of participants on the net-
work throughput.
Our final simulation analyzes the size of the issued
certificates for different key sizes. Figure 6 presents
the corresponding results for the RSA 2048 bit and
RSA 4096 bit certificate signatures. Since we are
working with multi-signatures, the issued X.509-v3
certificates contain all the signatures in extensions.
Their size considerably increases due to this addi-
tional information. This entire process facilitates the
validation of the certificate and its signatures by other
SECRYPT 2022 - 19th International Conference on Security and Cryptography
Figure 6: Variation of the size of issued certificates with the
number of endorsers for different key sizes.
When the requests were made through the Proxy
REST API with HTTP, a Round Trip Time of 32ms
was noted with the dedicated server. In this scenario,
the local-host client was used to call the DPKI func-
tions in a local computer. In both the evaluations (i.e.,
latency comparison of certificate issuing and certifi-
cate revocation process), functions write data to the
ledger of the blockchain. The currently stored CRL is
obtained and returned so that the endorsers can sign it
and insert their signatures in the response.
The objective of this work is to provide an effective,
robust and reliable user identity management PKI
using a decentralized approach. This study merges
the concepts of blockchain and decentralized storage
structure with the ability of PKI to generate a certifi-
cate. Each of the peers on the network uses a unique
intermediate certificate authority and validator. Any
peer who joins the network will become an intermedi-
ate signing CA. The guarantee that the produced cer-
tificates are legitimate and unaltered is constantly val-
idated by other peers in the network.
We can optimize the current implementation of
our model to enhance its functioning. Specifically,
we would emphasize on using a blockchain frame-
work that uses DID and DPKI internally. In our
current model, the certificates used in transactions
are still generated by a utility function of the Hyper-
ledger Fabric. Another possible improvement is to
use the same generated key-pairs and certificates for
both DPKI signatures and transaction signatures.
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