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P.Missier2017
SystemsResearchChallenges
Towards an authority-free marketplace for
personal IoT data (Personal Data from Things)
Paolo Missier
Jan 16th, 2017
Systems Research Challenges in the Internet of
Things Workshop
Ack: Dr. Michele Nati, DE Catapult

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About a year ago,
in a fancy Northumberland country house, ...

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IoT ∩ People  Personal Data from Things (PDT)
IoT vision: personal devices will make our lives better
They often also produce data that is also personal
As per the Data Protection Act 1998
• Are people aware of the trade-offs between privacy and benefits?
1. Ownership:
• What is “my” data? Who else has access to it? To what extent?
2. Awareness of third party use of personal data:
• Who has been doing what with my data?
3. Control.
• How much control can I have on the data that devices produce on my behalf?
Ownership + awareness + control  Trust

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Activity detection pattern
Accelerometry data
Indoor location data
Activity
Detection
Accelerometry data
Indoor location data
Activity
Detection
Aggregate
Analytics
03 January 2016 10:16

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Moving forward: brokered Personal Data exchanges
Working assumption: Personal data are assets with a value
fitness / health monitoring, energy metering, …
PDT: Control  trading
Primary
producers
(wearables…)
Value Added Services /
aggregators
Topics (minimal
data semantics)
What would an infrastructure for a PDT marketplace look like?
Sensor data streams,
batched into windows

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Baseline (personal) data marketplace scenario
1-hop Contract model between Primary producers PP and Primary
Consumers PC:
Each topic has an associated unit value: T  val(T)
For each batch of N messages from PPi, to PCj about Tk:
(PPi, PCj, Tk, N)  PCj owes (N . val(Tk)) coins to PPi

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Raw message logging, baseline

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Count cubes from messages, 1-hop

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Using count cubes to enforce contracts

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Baseline scenario, realisation – broker-based tracking

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Baseline scenario, realization - unilateral tracking

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Moving forward
Two directions for a more interesting marketplace:
1. Fully decentralised / unilateral message tracking without trusted authority
2. Multi-hop contracts:
Primary Consumer PC-VAS  [resell]  Secondary Consumer SC-VAS  …

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Decentralising and removing trust

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What does the authority do?
1. Control the Tracker DB
1. Prevent fraud:
• Producers have an incentive to over-claim data production
• VAS have an incentive to deny receiving some of the data
• (Data ownership / data theft / Replay attack)
• A third party will have an interest in claiming ownership of messages sent by
others
• For instance, by copying data (possibly encrypted) and replaying it on the
channel, publishing it as its own

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Approach
Blockchain + smart contracts technology, used to:
1. Associate identity to marketplace participants
2. Agree on contract specification
3. Settlement of contractual disputes given unilaterally generated
count cubes
Concrete prototyping [in progress]: the Ethereum platform
“A blockchain is a globally shared, transactional database”

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Basic BitCoin protocol(*)
(*) Source:
A Next-Generation Smart Contract and Decentralized Application Platform
https://github.com/ethereum/wiki/wiki/White-Paper
State S: {<owner, balance>}
Transactions transfer ownership of (unspent) coins
APPLY(S,TX)  S' or ERROR
APPLY({ Alice: $50, Bob: $50 },"send $20 from Alice to Bob") =
{ Alice: $30, Bob: $70 }

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Ethereum transactions and smart contracts
external
accounts are
asset owners
contract accounts
also contain:
• contract code
• storage
BitCoin Transactions:
{ <owner, balance> } —> { <owner’, balance’> }
TX-eth: Transactions become messages
Messages carry arbitrary data
APPLY(S,TX-eth):
run the code associated with the destination (contract) account

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Smart contracts in the Ethereum Virtual Machine
http://solidity.readthedocs.io/en/develop/index.html
runtime environment
for smart contracts in
Ethereum

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Contracts for device registration / identity management

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Contracts for formalising agreements between parties
Note: this sets the list of topics st(PC) to which each PC subscribes

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Contracts used for reputation management

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Using smart contracts for unilateral reporting verification
Given N PP, M PC,
and R topics T1, T2, …, TR:
Each PPi and each PCj all report their unilateral count cubes for each window w
They all agree on the time interval that defines W (magic, to be dealt with later)
1) No trouble: 1. All PPi and / all PCj report independently and accurately
2. Some do not report, but reports are accurate
2) Trouble: 1. The reports from PPi and PCj do not “add up”
2. The reports do not sync on time / windows
Scenarios:

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Publishers transactions
CCs(w,i,k) = ni,k count of messages sent by PPi during w about Tk
Fragment of counts cube viewed by PPi:
This is one row of sender matrix SMw for w:
SMw[i,k] = CCs(w,i,k)

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Publishers transactions
Each of these fragments is sent to the Reconciliation Smart Contract as a
Ethereum blockchain transaction:
- The contract receives N messages associated with w
- For each PCj, the contract has access to the set of topics it subscribes to:
Credit PCj  PPi:

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Subscribers transactions
Fragment of counts cube viewed by PCj:
-- note: include senders as an extra dimension
Credit PCj  PPi:

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Reports propagation
Settlements are straightforward when reports are partial but accurate
Matrices SM, RM, are two views of the same data exchanges:
C1. For each PPi and topic Tk:
SMw(i,k) = RMw(j,i,k) for each j:1..M such that Tk ∈ st(PCj)
C2. for i:1..N:
RMw(j,i,k) = SMw(i,k)
Q. Which subsets of reports are sufficient to complete the matrices?

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Fraud detection
Incentives to behave unfairly:
• Can fraudulent reporting be always detected?
• Can responsibility for the fraudulent reporting be ascribed to one or
more specific participants?
• Publishers: over-report
• Subscribers: under-report
1. Detection:
SMw(i,k) > RMw(j,i,k) for some j (1)
2. Ascribing responsibility:
Case 1: PC fraud
Case 2: PP fraud

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Fraud detection – initial thoughts on responsibilities
Case 1: PC fraud
It follows from C1, C2 (above) that:
If Tk ∈ PCj ∩ PCj then RMw(j,i,k) = RMw(j’,i,k) for i:1..N
let j’ such that Tk ∈ PCj ∩ PCj:
Suppose SMw(i,k) = RMw(j’,i,k)
This suggests that (1) may be due to PCj under-reporting on Tk, and
PPi reporting correctly
- The more topics the PCs share, the stronger the evidence...
Case 2: PP fraud
Suppose RMw(j,i,k) = RMw(j’,i,k) for all Tk
This suggests that PPi has over-reported
(1) SMw(i,k) > RMw(j,i,k)

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The last slide
Some novel uses for blockchain (amongst many others)
https://solarcoin.org
http://www.electricchain.org
http://www.mediachain.io/
https://www.coalaip.org
…
Personal data in the IoT space:
Mashhadi, Afra, Fahim Kawsar, and Utku Gunay Acer. “Human Data Interaction in IoT:
The Ownership Aspect.” In Internet of Things (WF-IoT), 2014 IEEE World Forum on,
159–162, 2014.
Vescovi, Michele, Corrado Moiso, Fabrizio Antonelli, Mattia Pasolli, and Christos
Perentis. “Building an Eco-System of Trusted Services through User Transparency,
Control and Awareness on Personal Data Privacy.” In Procs. W3C Workshop on
Privacy and User–Centric Controls. Berlin, Germany, 2014.
Multi-hop contracts and transitive credit management:
Missier, Paolo. “Data Trajectories: Tracking Reuse of Published Data for Transitive
Credit Attribution.” International Journal of Digital Curation 11, no. 1 (2016): 1–16.
doi:doi:10.2218/ijdc.v11i1.425.