This is a paper I presented at IoTBDS 2017, proposing new approaches to improving security and privacy with blockchains

1. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Enhancing IoT Security and
Privacy with Distributed Ledgers
Paul Fremantle[1], Benjamin Aziz[1], Tom Kirkham[2]
[1]School of Computing, University of Portsmouth
{paul.fremantle, benjamin.aziz}@port.ac.uk,
[2] Science and Technology Facilities Council
tom.kirkham@stfc.ac.uk

2. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
One Minute Overview
Problem:
The Internet of Things is insecure
Mirai
620+Gbps attack
Devices are tied to vendors,
No heterogeneous interop,
No shared governance
New
Transaction
Le
d
g
er
Le
d
g
er
Le
d
g
er
Le
d
g
er
Le
d
g
er
Entered into
Block Consensus
Ledgers
are updated
Next Block
Distributed Ledgers provide
shared governance
Typical IoT devices are too small
to run consensus algorithms
Intel SGX enclave!
!
!
!
!
!
!
!
Blockchain!
processor!
Pythia API!
OpenSourcecode
IoT!
Devic
e!
Attestation
Interaction
withBlockchain
We propose a new
model called Pythia
that enables IoT devices
to trust Dist Ledgers

3. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Challenges for IoT Security and
Privacy
• October 2016 Mirai Botnet
– 100,000 devices compromised
– 620Gbps DDOS attack
– In reality there are millions of compromisable
devices (Checkpoint study 2014)
– Mirai was based on a dictionary attack and weak
passwords
• Also attacks on cars, houses, medical
devices, etc
– A survey of secure middleware for the Internet of Things,
Fremantle and Scott, PeerJ, accepted for publication

4. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
IoT security and privacy
• Updates are difficult and there is no
economic incentive for manufacturers
• Lack of clear ownership and registration
models
• Poor identity models
• Leakage of data and metadata
• Use of IoT devices as attack vectors

5. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
The real challenge
IoT is not heterogeneous, hence no choices for users
Low economic and evolutionary pressures
Chrome
Firefox
Safari
Internet Explorer
Dropbox
Google Drive
FTP, NAS,
etc
HTTP, TLS
HTTP/2
UDP, DTLS,
FTPS, XMPP,
etc
Fitbit Server
Fitbit

6. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Distributed Ledger Technologies
N1 N2 Nn
New
Transaction
Ledger Ledger Ledger Ledger Ledger
Entered
into
Block
Consensus
Ledgers
are
updated
Next Block
Ledger uses a Merkle Tree to ensure that each record guarantees all previous records
to create an immutable chain

7. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Consensus algorithms
• Bitcoin: Proof of Work
– Miners perform hashing, competing to be
the first to finalise the block, with a reward
– The longest chain becomes the master
– No requirement to know or trust the other
participants
– Expensive, low transaction rate, slow to
come to consensus
– Proven to be resilient at global scale

8. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Alternative consensus models
• Arbitrary participants
– Proof of storage
• Calculations based on stored data
– Proof of stake
• Based on ownership of existing coins
• Known participants
– Byzantine Failure Tolerant algorithms
– E.g. Paxos

9. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
What can DLT do for IoT
• Three main concepts
– Distributed Ledger
• A single, agreed source of truth
– Cryptocurrency
• Economic models to create value for security and privacy
– Smart Contracts
• Flexible transaction models that allow new transactions to
be scripted
• An environment where there can be trust,
privacy and effective contracts between parties
without reliance on a single vendor.

10. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
User Sphere:
Fully in control
of user
e.g. Laptop
Joint Sphere:
Appears to
be in user control
e.g. GMail
Three Tier Privacy Model
Spierkermann and Cranor
Spiekermann, Sarah, and Lorrie Faith Cranor. "Engineering privacy." IEEE
Transactions on software engineering 35.1 (2009): 67-82.
Recipient Sphere:
Fully in control of
Data recipient

11. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Approaches / Use cases
Identity
Ownership
Registration
Updates
Consent Contracts
Consent Logs
Data Revocation Contracts
Policies
Policy enforcement contracts

12. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
User Sphere:
Device Identity
Device Ownership
and Registration
Device Updates
Joint Sphere:
Consent Management
Policies
Recipient Sphere:
Consent Tracking
Policy Enforcement
Data Revocation
Three tier privacy model for IoT

13. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Typical IoT footprints
ESP8266 – 32bit controller,
1Mb program, 80k RAM ~ $2 each

14. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Uh oh
• How does an IoT system participate and
trust in a DLT?
– Full participation is expensive
• Bitcoin database >80Gb
• 512MB of RAM, 1Ghz CPU minimum
– Simple Payment Verification (SPV) smaller
but still beyond IoT devices
– Fundamentally, consensus algorithms are
beyond the CPU, network, power and
memory of IoT

15. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Oracles
• In blockchains, an Oracle is a system that
truthfully informs the blockchain about
events outside the ledger
Zhang, F., Cecchetti, E., Croman, K., Juels, A., and Shi, E. (2016). Town crier: An
authenticated data feed for smart contracts. In Proceedings of the 2016 ACM
SIGSAC Conference on Computer and Communications Security, pages 270–282.
ACM.

16. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Pythia
Lycurgus Consulting the Pythia (1835/1845), Delacroix

17. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
New concept - Pythia
• We define a Pythia as the “inverse” of an
Oracle
• Informs the outside world truthfully
about the distributed ledger
– In our case, the IoT device needs to be able
to interact with the ledger:
• Without participating in consensus directly
• With trust

18. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Intel SGX extensions
• Provide a secure enclave
– Compare with Sandbox
• The code within the enclave is protected
from the rest of the system
• Remote attestation can guarantee the
codebase running is a known codebase

19. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Pythia
• A proposed model to
allow IoT devices to trust
DLTs
• An attested proxy for the
ledger
• The Pythia truthfully
informs the world (IoT)
about the ledger
– Without the IoT needing to
participate in consensus
Intel SGX enclave!
!
!
!
!
!
!
!
Blockchain!
processor!
Pythia API!
OpenSourcecode
IoT!
Device!
Attestation
Interaction
withBlockchain

20. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
OAuthing
• Previous work on IoT privacy and security:
– Secure device registration
– Pseudonymous Data Sharing
– Personal IoT middleware
– But without DLT (so far)
• OAuthing + DLT + Pythia:
– Shared governance and an approach based on smart
contracts
Fremantle, P. and Aziz, B. (2016): OAuthing: privacy-enhancing
federation for the Internet of Things, 2nd International
Conference on the Cloudification of the Internet of Things

21. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Related Work
• Tindall, K. (2015)
– Bitcoin payments for IoT updates
• Christidis and Devetsikiotis (2016)
– Discuss IoT and Blockchains, but not specifically
privacy and security
• Proof of Luck
– Milutinovic et al. (2016) provide an alternative
consensus model based on SGX enclaves
• Frey et al (2016)
– Have demonstrated trust in Bitcoin on a mobile
phone

22. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Conclusions and further work
• Position paper: still plenty of work to do
• This is a serious issue:
– How does the IoT trust the Blockchain without
significant overhead?
• Pythia is one potential approach
• Need to validate:
– Blockchain running within SGX (128Mb
limitation)
– Remote attestation costs on IoT devices
– SGX challenges

23. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Contributions
• A model for reasoning about how
blockchains can improve privacy and
security in IoT
• A set of approaches for improving
security and privacy of IoT with
blockchains
• A proposed architecture (Pythia) for
creating distributed trust in a blockchain
on low- power devices.

24. Enhancing IoT Privacy and Security with Distributed Ledgers, Fremantle, Aziz, Kirkham
Thank you & Questions