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so during this presentation I'll speak
about the Acolytes Oracle solution and
some of the things that we have in the
workings so
given the circumstances there are many
smart contracts that need to get
external data think about web api's or
from any data source
still decentralized networks like
aetherium i've and the inherent
limitation in not being able to reach
out the internet so the smart contrasts
live like in a walled garden and they
cannot simply open a socket and fetch
external data so this is why there are
many different solutions called as
Oracle's to pull or push data external
data to the blockchain so we'll focus
during this presentation on the first
approach listed in there in this slide
so this is the one used by Oracle eyes
and as we speak this is the most widely
used on the public blockchain so one of
the pros of this approach is that it's
fully transparent in the sense that both
the query and the results are
permanently stored on blockchain another
advantage is that we can use any data
source available on the Internet so any
Web API potentially since there is no
need for them to adapt to the blockchain
they have no knowledge of the blocking
and it doesn't have to and
another advantage is that there is no
trust line open with the Oracle so the
Oracle cannot simply tamper with the
data as with attestation we can move the
trust away from the Oracle to Atta
status we seen a bit who this artist it
was our
so this is the logic flow what you have
is a smart counter sitting on a theorem
that can reach out the Internet via
Oracle eyes the way they do so is simply
by using the
Oracle AERS query function so this
function essentially is an event so our
of train engine can listen to this
events and fulfill the request so
essentially we are the one opening the
connection with the remote web service
we get a result
along with what we call authenticity
proof and we send both of them back to
the contract so this is a synchronous
and
there are different approaches actually
to implement these authenticity proofs
so these authenticity proofs are
cryptographic
signatures that can enable the smart
contracts and any external auditor to
verify that the data being provided by
the Oracle has not been tampered with
and that the result that the smart
contract is receiving is really the one
sent by the external data source so the
first one is based on an external
project called TLS notary this is the
only one available today on the ATM
maenette since September last year and
the way it works just briefly is that
when the client the client being
authorized initiate a TLS session with a
web service the client secret is split
in alpha so that Oracle is just
just as alpha feet and the other valve
the other half is secured by a piece of
code whose correct execution is ensured
via the Amazon Web service sandbox
concept so the way it works is that we
get a cryptographic proof out which
doesn't prove that the data has not been
tampered it just proves that there was
some kind of cooperation between the
notary server running on Amazon Web
service and
Oracle eyes so this means that if you do
trust Amazon being honest then Oracle
eyes is being honest as well so there is
a trust in Amazon with Amazon being an
artist either
another approach that we are presenting
today you can check out the paper that
we are releasing this afternoon it's
based on a different approach so the
first one the TLS not one is essentially
a software attestation this one is an
app door best one we call it Android
proof and essentially it does leverage
through techniques technologies the
first one is Q SE e which is the
Qualcomm te e trusted execution and
viral and solution and Android
safety-net so by using both of them we
can basically verify that there is an
open source piece of code fetching the
data from the web service which is
running in a secured Hardware bad
Android based device
the third one that we are presenting is
slightly different because it doesn't
prove that it has not been tampered with
when fetching data from an external data
source but it's based on Intel SGX so we
have already seen it with a clipless
with a clipless presentation Intel SGX
again is capable of verifying that a
given piece of code a subset of C
essentially is running in a secure
Intel CPU backed sandbox and there is
the inter signature on the correct
execution of the code so this process is
essentially closed called enclaved
remote attestation and works via the
Intel attestation service and we use
this to solve one of the very issue that
we have seen in the last few days in
many talks which is the difficulty of
getting reliable on chain random data
random numbers right so with random data
source that you can use via replies what
you get out is a random number which is
generated by a low-level Intel SGX
backed instruction and you can verify
the correct execution meaning that the
random data was really
random if you do trust the Intel
solution so again here we are we have
just seen two different data Staters so
Google or Qualcomm if you want and Intel
so what we are seeing so far with all
these three different authenticity
proofs is at the station as a service
essentially so different kind of
software and adver attestation that we
can use to move the trust away from the
untrusted a small start-up Oracle to a
trusted entity which is a much bigger
company of course you don't want to
trust a single corporation but the
assumption that we are making here is
that if you
few trusted companies or Atta status in
this case are less likely to
mmm act all aspect actors compared to a
network of untrusted anonymous players
so viralize you can specify the proof
that you want to get out so the kind of
authenticity proof that you want the
Oracle eyes infrastructure to generate
to fetch this kind of data and of course
you can specify more than one proof so
you can get the Android proof DTLS not
reproof etc on the same request meaning
that if all the proofs are valid and the
result is the estill been tampered with
it will mean that at the same time at
the same exact time
android Qualcomm Amazon and Google were
all providing the same wrong data which
is pretty unlikely
so the last thing that we are presenting
today and that it's available in our
documentation is the option computation
so this is yet another solution to the
limitation the constraints of the VM
meaning that if you want to execute any
piece of code if you want to reuse any
library external library or if you have
concerns related to the gas limit in
some cases you might want to delegate to
an option context the execution of this
code and the approach that we follow
here is again the one based on at least
a torso at the station and what we do
essentially is extending the base Amazon
Web service sandbox concept introduced
by today's notary and with this extended
concept you can execute in a safe
Amazon Web service best lockdown
instance any piece of code and you can
get out an authenticity proof so this
authenticity proof can be verified by
anybody and
the the way it works is that you define
our zip so this is there is an example
here using for example the Python numpy
library and we can get a result out we
distribute it over IP FS and
in india oracle ice query we specify as
datasource computation metadata source
and as query we specify the ipfs
mutation so what happens is that oracle
eyes that does initiate the secure
instance generate the honesty proofs and
the verification steps are essentially
based on an extended verification of the
authenticity proof that i've ever just
explained before so what you get out is
the proof that the result is really
coming from a correct execution in an
efficient context of a single instance
of this piece of code so there is not
anymore this child this challenge game
but it's more like
audit or based
approach so thank you for the attention
and i will be around so come find me if
you have any question we are looking for
feedbacks and we are releasing as I said
the Android paper later today so please
give us some feedbacks and thank you for
that again
thank you very much time
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