Enhancing IoT Security and Privacy with Distributed Ledgers -
A Position Paper
Paul Fremantle
, Benjamin Aziz
and Tom Kirkham
School of Computing, University of Portsmouth, Portsmouth, U.K.
Science and Technology Funding Council, Harwell, U.K.
Internet of Things, Blockchain, Distributed Ledgers, Security, Privacy, Blockchains.
The Internet of Things has a number of well-publicised security flaws, resulting in numerous recent attacks.
In this paper we lay out a framework for looking at how distributed ledgers and Blockchain technology can be
used to enhance the security, privacy and manageability of IoT devices and networks. A significant concern is
the inability to process blockchains on small devices. We propose an architecture for IoT security and privacy
based on blockchains that addresses this and other issues. We look at related work and propose areas of further
The Internet of Things (IoT) consists of the set of
Internet-connected devices that collect sensor data
and allow control of actuators to measure and affect
the physical world.
Concerns over the security and privacy of the In-
ternet of Things reached a new high when the Mi-
rai botnet caused massive disruption to the Internet
in September 2016. In Fremantle and Scott (2015),
a number of issues are identified for security of IoT.
The direct cause of the Mirai attack was the use of
a dictionary password attack on devices connected to
the Internet that offered direct access. Other security
concerns about IoT devices include significant chal-
lenges in updating devices; lack of clear and effective
registration processes; lack of well defined identity
models; use of IoT devices as attack vectors into more
secure systems; and attacks on physical systems such
as Stuxnet (Langner, 2011).
Distributed Ledger technology, which is based on
the Blockchain (Nakamoto, 2008) construct, provides
a new class of distributed technologies. These sys-
tems are famous for being the basis of cryptocur-
rencies, where there is a fully decentralised system
with no central bank. Such systems are charac-
terised by a distributed, secure, ledger that provides
an immutable, assured record of a set of transactions.
While some blockchains such as Bitcoin have re-
stricted transaction models, others, such as Ethereum,
support more complex transaction models. Effec-
tively, each transaction recorded in the blockchain
can support arbitrary logic which is coded in a script-
ing language, which is Turing complete. This ability
to create new transactions through the use of script-
ing languages is commonly known as Smart Con-
tracts. Together these three constructs Distributed
Ledger, Cryptocurrency and Smart Contracts cre-
ate an environment where a set of parties can share in
the governance of the system, even when the identi-
ties and reputation of the parties is not known. Each
party participates in guaranteeing the good behaviour
of the others and of the set of transactions. The bene-
fit of this is that it provides a fair and unbiased system
whereby users can trust in the integrity of the system
independent of any single parties’ overall behaviour.
We propose that this shared governance model has
significant benefits for the security and privacy of the
Internet of Things. In this work, we argue that the spe-
cific characteristics of the blockchain provide unique
approaches to solving problems in the IoT.
The contributions of this paper are: a model for
reasoning about how blockchains can improve pri-
vacy and security in IoT; a set of approaches for im-
proving security and privacy of IoT with blockchains,
derived from the model; and a proposed architecture
for creating distributed trust in a blockchain on low-
power devices.
The rest of the paper is laid out as follows. In
Section 2 we propose reasons why distributed ledger
technologies can help with IoT privacy and security.
In Section 3 we outline a model for reasoning about
Fremantle, P., Aziz, B. and Kirkham, T.
Enhancing IoT Security and Privacy with Distributed Ledgers - A Position Paper.
DOI: 10.5220/0006353903440349
In Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security (IoTBDS 2017), pages 344-349
ISBN: 978-989-758-245-5
Copyright © 2017 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
security and privacy for IoT, and use that model to
identify areas where distributed ledgers can assist. In
Section 4, we propose an implementation plan that
addresses these issues. In particular we aim to solve
the problem of how to provide trust in a blockchain
from a device that lacks the power to participate in the
blockchain. In Section 5 we compare this approach to
related work, and outline a plan of further work in this
Because of the widespread deployment of IoT to-
gether with the use in many areas where personal in-
formation can be collected or deduced including
smart homes, health monitoring, smart cars, and fit-
ness tracking there are ongoing major concerns
about privacy. These include: lack of informed con-
sent for publishing data; fingerprinting of hardware;
and de-anonymisation, amongst others.
The Web and Internet have been driven by hetero-
geneity of clients and services: any browser will work
with any website; any FTP client with any FTP server.
This choice enables several security and privacy bene-
fits. Users can migrate away from insecure or privacy-
leaking systems and services. It also encourages both
client and service providers to produce security up-
dates and improvements to the core protocols and
to the websites and services provided. While there
are problems, this has led to incremental improve-
ments and choices. For example, users concerned
about email integrity and spamming can adopt anti-
spam measures such as the Domain Key Identified
Mail standard (Crocker et al., 2011). Users concerned
with confidentiality can encrypt email. Users con-
cerned about insecure messaging systems can choose
more secure instant messaging systems such as Sig-
and Threema
. In contrast, the Internet of Things
is fundamentally controlled by the manufacturers of
devices, and does not offer choice for users to migrate
to more secure services. IoT devices are hard-coded
with firmware that typically connects to a single ser-
vice. In many cases the only true privacy control a
user has is to completely disable a device. Even when
systems use standard protocols, they may not docu-
ment the usage.
As discussed above, blockchains create a dis-
tributed ledger that creates a shared governance.
Blockchains rely on proof that the parties are behav-
ing in a consistent and correct manner, since the par-
ties are not known and are assumed to be inherently
untrustworthy. Bitcoin, the most famous blockchain-
based system, relies on a concept called Proof of Work
to ensure that parties are behaving properly. Other
blockchain systems rely on differing proofs, includ-
ing proof of stake, proof of storage, or combinations
of different proof types. The proof is used to guar-
antee the immutability of an block and each block
guarantees the previous blocks (typically using a con-
struct known as a Merkle Tree) creating a chain
of blocks known as a blockchain. Because the proof
requires some form of value (whether it is ownership
of a cryptocurrency, expended work, storage of data,
etc), the system can provide rewards for those who
participate. This is the basis of cryptocurrencies. For
example, Bitcoin issues new coins to the participat-
ing system that first correctly produces the work that
verifies the latest block.
Therefore, the distributed ledger offers the
promise of creating an environment for IoT networks
where there can be trust, anonymity, and effective
contracts between parties without any single vendor
being in charge, and without requiring any party to
trusted above any other.
However, there remains a major concern. The
processing, memory and code requirements of
blockchains makes them inappropriate to run on IoT
devices and gateways. For example, the current Bit-
coin database is around 80Gb and it takes at least
512MB of RAM and a 1Ghz processor to partici-
. The Simple Payment Verification (SPV) model
in Bitcoin supports lighterweight clients that can con-
nect to a random sample of servers, but this is sus-
ceptible to Sybil attacks. Recent work in Frey et al.
(2016) has made it feasible to participate in the Bit-
coin network with a smartphone, but to have an effec-
tive approach for IoT the system must support com-
mon cheap IoT devices. For example, the ESP8266
device is a common device target that offers 1Mb
of program memory and 80Kb of variable memory.
Even with the improvements from Frey et al, this
is still insufficient even to validate the Bitcoin sys-
tem. As a result, we consider this a significant is-
sue that needs addressing before the vision of using
blockchains as the basis of IoT security and privacy
can be achieved. To solve this problem, we propose
an avenue of research that can provide trust between
IoT devices and blockchains without requiring the de-
vice to actively participate in the blockchain.
Enhancing IoT Security and Privacy with Distributed Ledgers - A Position Paper
Spiekermann and Cranor (2009) offer a model for
looking at user privacy. In their model, they identify
three spheres: the User Sphere, the Joint Sphere and
the Recipient Sphere. The User Sphere is completely
in the control of the user (e.g. a laptop). The Joint
Sphere refers to areas that may seem to be in the user’s
control, but may have some significant control by a
third-party. For example, a cloud email account may
seem like the user can delete emails, but the cloud
provider may in fact back these up and keep a copy.
Finally, once data has been transferred to a third-party,
it is assumed to be in the Recipient Sphere, where the
only controls are legal and contractual.
In the model, a device that offers the user full con-
trol is firmly in the User Sphere. However, we would
argue that many current devices are actually in the
Joint Sphere. This is where the device appears to be in
the control of the user but in fact is in the control of a
third-party. To give an example, the Google Nest de-
vice offers users the opportunity to apply smart heat-
ing controls to their house. While a number of user-
centred controls give the user the impression that it
is in the User Sphere, there are two key reasons to
counter this: firstly, the data logged by the device is
extensive and cannot be controlled by the user; sec-
ondly, the device auto-updates itself based on com-
mands from Google rather than based on user input.
Using this model, we can propose clear ap-
proaches that strengthen each of the privacy and se-
curity controls available in each sphere. Figure 1 pro-
vides an overview of this model.
Figure 1: IoT Blockchain applied to Privacy Model.
3.1 User Sphere
Moving privacy and security controls back to the
users inherently strengthens the User Sphere and pro-
vides greater choice, thereby allowing more secure
approaches to flourish. We have identified a number
of controls which can be managed by a distributed
Devices need to have secure identities (Fremantle
et al., 2014), and currently these are either not pro-
vided, or provided by the device manufacturer. Sys-
tems such as NameID
provide a model whereby
secure Web identities can be provided with no cen-
tral trusted system. Instead a distributed ledger (in
this case Namecoin) provides a neutral shared system.
This approach can be extended to IoT to issue each
device with a secure identity based on a distributed
A second, related issue, is the ownership of de-
vices. The Mirai botnet spread because dictionary
attacks allowed attackers to take ownership of de-
vices. Some systems offer models of taking owner-
ship securely (e.g. Bluetooth, NFC). In (Fremantle
and Aziz, 2016), a QR code is used in conjunction
with a Web-based system. We propose that the cryp-
tocurrency model of blockchains provides a safer and
clearer model of ownership. Distributed ledgers im-
plicitly support ownership: a Bitcoin transaction is
the transfer of some bitcoins from own owner to an-
other. Similarly, a blockchain for IoT could support
the transfer of ownership of a device from the manu-
facturer to the user, and from one user to another. The
security of this is therefore based on the security of
the blockchain.
A third issue within the User Sphere is updating
the device firmware. A number of attacks have orig-
inated in lack of updates. One issue is that device
manufacturers are incentivised to create new products
but not to update old products. In (Tindall, 2015), a
model is proposed whereby devices can pay for up-
dates in a cryptocurrency. In addition, blockchains
could be used as the basis for building trust in updates
and also in validating updates.
3.2 Joint Sphere
Recall that the Joint Sphere is the parts of the system
where the user has some form of control over their
data and systems, but the provider also shares con-
trol. For example, a health-monitoring device may
upload data to an Internet-based system and then may
offer users controls on how they share data. A ma-
jor change in legislation around this is the European
Union’s General Data Protection Regulation (GDPR)
which requires much stronger consent controls. Many
systems offer forms of user consent for sharing data
with third parties, but these lack significant require-
ments. For example, many users are not aware of how
to revoke consent. Similarly, there is no clear place a
user can identify all the consents they have approved
IoTBDS 2017 - 2nd International Conference on Internet of Things, Big Data and Security
across different devices. Consent is not just about pri-
vacy. IoT devices often include actuators that can act
based on Commands, and the security of a device in-
cludes ensuring that only authorised systems can issue
commands to devices.
We propose that consent be treated as a contract
in a distributed ledger system. This has several ben-
efits. Firstly, this creates a clear ledger of all issued
consents. Secondly, this creates a clear contractual
obligation on the recipient of the consent to behave
according to the contract, which could (for example)
specify penalties for breaking the contract. Finally,
this model creates a clear opportunity for revocation
of consent, giving a single place to do so.
A related area is that of policies. In this meaning
a policy is a computer-readable expression of rights
and obligations. For example, a consent approval
may refer to a policy: the user might approve sharing
of data to a website based on the fact that the web-
site promises not to share the data to any other body.
Languages such as XACML (Godik et al., 2002) al-
low complex access control policies to be encoded in
XML or JSON. We propose that a distributed ledger
could be used to store and validate policies in an im-
mutable model that could be then used by IoT net-
works and consent models. In addition, the policies
could themselves refer to transactions in a distributed
ledger. We will describe this in the Recipient Sphere.
3.3 Recipient Sphere
The Recipient Sphere is the area where the user’s data
is now out of their control. Ultimately, the user must
rely on legislation or legal contracts in order to main-
tain control of this data. However, we propose that
distributed ledgers can offer a significant benefit in
this space. For example, suppose that a user shares
data with a third-party using a smart contract to en-
able consent. The contract refers to a policy that says
the third-party can only share that data with others
(on-bound sharing) if they inform the user of that
on-bound sharing. This policy could point to a new
smart contract that must be executed at the point of
on-bound sharing. By executing this second contract,
the on-bound sharing is logged immutably into a dis-
tributed ledger. Of course, it is hard to police this re-
cipient sphere: it is possible that the third-party web-
site will share data without executing the contract.
There are two defences against this. The first is that
they are explicitly breaking a contract and penalties
can occur. In fact, we can envision that these penal-
ties could be implemented directly in the ledger by
smart contracts. If the user can prove data was shared
illicitly, the payment would be automatic.
Spotting these illicit data shares can possibly be
done using a concept of a Trap Street. This is the habit
that map-makers have of including incorrect data to
see if others copy it. Similarly, IoT devices could de-
liberately share incorrect data to specific parties to see
if it leaks out without a ledger entry to record it.
A similar capability that could be implemented us-
ing distributed ledgers and smart contracts is that of
Data revocation. This would be a situation where a
smart contract is used to trigger the secure deletion of
specific data.
In summary, we have seen a number of ways
where distributed ledgers can enhance privacy and se-
curity of IoT. We now look at a proposed implemen-
The biggest concern we have regarding the imple-
mentability is the inability of small devices to par-
ticipate in blockchains. Many blockchains provide
lighter-weight models of validation such as the Bit-
coin SPV
and the Ethereum Light Client Protocol
However, even these may require more processing
than an IoT device can provide, and this requirement
may also increase in the future with the growth in the
blockchain ledger.
There already exists a concept in the blockchain
system of an Oracle. An oracle is a system that re-
ports on the world to the blockchain in a reliable fash-
ion. For example, a smart contract may require pay-
ment when a certain condition is met, and the oracle
is used to report to the blockchain when that condi-
tion exists. We propose that the IoT and Blockchain
require the exact opposite - a trusted intermediary that
reports on the state of the blockchain on behalf of the
IoT device. Such an entity, which we call a Pythia,
could interact with the blockchain on behalf of IoT
devices and do so in a trusted fashion. Therefore, it
would act both as an oracle to the device, as well as
an oracle to the blockchain.
In order to allow the Pythia to be trusted, we
propose creating an Open Source codebase that
would be run using Intel Secure Guard eXtensions
(SGX) (Costan and Devadas, 2016). SGX provides
a secure enclave within modern Intel processors that
provides two key benefits that are required by the
Pythia model. Firstly, the code is sealed and pro-
https://en.bitcoin.it/wiki/Thin Client Security
Enhancing IoT Security and Privacy with Distributed Ledgers - A Position Paper
tected from attack from other code running in the
same processor. Secondly, the code can be validated
using Remote Attestation, which allows code exter-
nal to the processor to verify the specific codebase
running within the enclave. This verification still re-
quires some processing power as it is based on Diffie-
Hellman Key Exchange (DHKE). Many devices do
perform aspects of Public Key Cryptography, but we
have not yet assessed the ability of typical devices to
perform DHKE, and that is one of our ongoing goals.
The remote attestation is then used to validate that
the Pythia is indeed running a specific version of the
open source codebase. In turn, this allows the device
to trust that the Pythia will act as intended with the
blockchain. This model is shown in Figure 2.
The Pythia model is that it offers a set of APIs
to IoT devices, and that these APIs offer capabilities
around device identity, ownership, data sharing con-
sent, etc. A number of these APIs are already in place
in systems such as OAuthing (Fremantle and Aziz,
2016), which utilises the OAuth2 APIs to provision
identities, consent scopes and ownership tokens to de-
vices. We believe that this model can be extended to
interface with blockchain smart contracts. One chal-
lenge is that code running within an SGX enclave only
runs efficiently when it fits into 128Mb, which may
prove to be a challenge when building the Pythia.
Figure 2: Proposed Pythia Model.
Given this infrastructure, we propose building a
set of smart contracts that implement the flows iden-
tified in Section 3. These are:
Secure Device Identity
Device Ownership
Device Updates
Data sharing and command consent
Consent logging
Policy sharing and validation
Data revocation
We intend to use the Ethereum blockchain as the
basis for this work.
In Christidis and Devetsikiotis (2016) there is consid-
erable discussion of using blockchains together with
IoT, but this does not focus specifically on the pri-
vacy and security challenges of IoT. In Milutinovic
et al. (2016), an innovative blockchain is proposed
based on running within an SGX enclave. In Freman-
tle and Aziz (2016) there is a framework for device
identity, registration and consent that is independent
of vendors. However, this still relies on trust in the
central party, which can be obviated with the use of
blockchains and smart contracts. Town Crier (Zhang
et al., 2016) proposes an approach where SGX ex-
tensions are used to feed data into a blockchain in a
trusted manner, acting as an oracle. This does not pro-
pose the opposite flow where the SGX enclave pro-
vides verified data from the blockchain as in the pro-
posed Pythia.
5.1 Conclusions and Further Work
At the moment, this vision of a blockchain-based IoT
is just a preliminary proposal. Clearly, implement-
ing such a blockchain based on existing distributed
ledgers that enable Smart Contracts such as Hyper-
Ledger or Ethereum is possible. Implementing an
SGX-based blockchain client to provide trusted data
from the blockchain is also clearly possible, although
given the limitations on SGX memory, this may need
significant tuning to be effective and efficient. At this
point, we have not evaluated the ability of a device
to perform remote attestation of an SGX enclave, nor
the complexities of the key distribution requirements
to make this possible. We see this as the first step
in the ongoing research plan, together with evaluating
the possibilities of running an Ethereum node in an
SGX enclave.
In this paper we have proposed using a distributed
ledger to provide a shared governance model for IoT
devices, networks and cloud systems. Using Spiek-
ermann and Cranor’s Three Layer Privacy model, we
have outlined an approach for evaluating the use of
IoTBDS 2017 - 2nd International Conference on Internet of Things, Big Data and Security
blockchains in IoT. We have identified a number of
key areas where blockchains could be used to improve
privacy and security. We have proposed an system
that we call a Pythia whereby IoT devices can trust
the transactions of a blockchain without requiring the
memory and processor capabilities to actively partic-
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Enhancing IoT Security and Privacy with Distributed Ledgers - A Position Paper