[Applause]
and the funky CEO as Isis loves and also
a professor at UC Berkeley and today I
will talk about the decentralized petty
tyranny so first as we all know Peter is
the new oil this data is really helpful
for us to make better decisions and give
us a lot in fact hi a lot of this people
is really is also very sensitive and had
not any sensitive data protists a lot of
challenges so for example we continue to
see really large-scale data breaches
where attackers compromised sensitive
and still sensitive information about
hundreds of millions of users being in a
one in a single account and also we
continue to see that users are using
trusts incomplete as a lot bigger and
maybe mishandles abuse and
so as we handle sensitive data there are
a number of challenges that we need to
address one as the English actor maybe
untrusted attackers may have compromised
the computer infrastructure are the
advocates not only be untrusted because
the again attackers may have may have
launched some malicious applications
other applications may have poor
abilities and also some applications may
have undesirable deferred leakage so to
address these problems at oasis labs we
have been developing new solutions where
we essentially builds the next
generation Block in our contract
platform with British scalability and
privacy protection where we unique or
skill a postmark on to execution and
also enable for the first time
confidential smart contracts and also on
top of the platform we've built SDKs to
enable privacy
a machine so today I'll talk about some
new research that we have done at every
Clarion our voices with decentralized
afetr children so Christmas book has a
motivating example and again frantic
action
so one banks provides financial services
for example immigrants the lands they
need to detect fraud and typically how
this works is that each Bank uses its
own data to build for example some
agility model for fraud detection
poverty as well as we know that it would
be much better if these banks can
actually share that it had to build one
traffic picture instead of the
individual ones the case with Mozilla
the machine imago can essentially be
more practice I witnessed another today
because there is a lot of privacy
concerns because it is excessive and
also there may be missed
so luckily address this problem
so there are alternative solutions that
we can consider so II with one
admissible solution we can use something
called a feathery learning so our
facility is mechanism we've done it's an
approach that actually has seen some
adoption deployments I could go and
Apple for example we're essentially
using fertility and usage data are
stores locally on their mobile phones
and then the central server at Google
are a broken coordinates these different
local devices to collectively train a
machine any model in this distributed
fashion so in this case with ready
tyranny it takes an iterative approach
where in run time it has very high
bridge in a fleece global global model
that's that is being trained and then
this model is distributed to the local
devices and and then each local device
uses its own local data to try to update
this model gives more we can't really
update and then the sweetie updates is
then sent back to the central server to
then the listener terminal advocate
studies with the updates to the create
to the next version of the mother and
then this continues so in this way the
advantage is that the each user's data
is stored locally is not actually
uploaded to the cloud out to the central
server but still in this case it still
needs as inter server to coordinate this
ferry terminal and there are of course a
number of challenges about which might
be use this type of approach to address
the problem that I just mentioned for
example in this case when the banks
wants to collaborate the questions and
one question is the who should actually
hooks the center server ideally you
don't want to rely on using be trusted
so you don't want to actually have and
you are hosting the central server and
also this is a new survey by rely on
accessibility and creates each year
spreads at home if they became malicious
are taken may also give the single
server some some unfair advantage
so in contrast to this family tyranny
motto which realises that your server to
coordinate distribute the devices to
together train machine is our winner
distributed way and that alternative
solution is was had a peer-to-peer
solution in this case essentially the
different devices form a peer-to-peer
network if there is no central server
and essentially the the different
devices will communicate through this
peer-to-peer network with its neighbors
and then through again an interesting
approach to try to together updates this
much mini model to utilize the local
data on the different devices to train
the to train the sandwich minimum I
would advantage of this approach is that
in the city we don't need to trust any
central server because there's simply no
central server however the challenge
here is as in dispute appear the
significant results and for our
communication as on and especially when
Anna Raph the client becomes flourished
and also there is more privacy
challenges Elizabeth so in our recent
work here we proposed a new paradigm
that we call decentralize the 2020 with
where we combine is into the best of
both worlds both giving and this
virtualized setting while we don't rely
on a nice central server
but also at the same time we can achieve
much better efficiency and dementia
stronger privacy protection than the
peer to peer said and the way we do that
is the instead of using as intrusive a
wastage we use a blockchain smacking
telephone to coordinate this
distribution meaning across the
different local devices in different
coins that would you host the the
pocketing
using this new paradise we achieve a
number of advantages
once again we ended with the centralized
and the secularization so we do need to
trust and listen to party for the
operations and against much more
efficient and community scale to large
number of participants compared to the
peer-to-peer solution and we can achieve
we're high utility essentially the
accuracy can be comparable to the
centralized model and we achieve strong
privacy where we can protect the clients
data privacy and by using drugs an
entire platform that wasn't me incentive
method
so now let's take a look at how this
approach works so first let me give you
a strongman solution whereas emissions
want me to achieve this decentralize the
federal sovereignty as we use of
lotteries my contact upon to coordinates
these different clients for training the
marina model isn't a distributed
decentralized way
so one a stronger approach is that we
can simply set have asthma contracts
under party platform which performs a
mother aggregation as I mentioned
earlier in the feathers it's been
exciting
where essentially this a modification
smart contract will perform what the
central server would do down life but
however so the child in this case it can
be very efficient and also provides
strong integrity guarantees even
industry centralized the city where we
don't need to actually rely trusts are
at the center server Harvard the China
here is they using this approach there
can be privacy concerns because on a
typical protein smacking her perform the
protein dinner is public and even though
in this case the the clients are now
sending location to the
got a platform but however even these
screening others for it were updates in
motion any models they can see okay
information so the question is how can
we do this in in a more appropriate way
so to adjust these challenges we
proposed pipelines to enable this new
paradigm up he centralized effectively
happened essentially you utilizes a
number of private secretively
technologies including adventure privacy
where we actually differentially
comments virtually numata and using
secure aggregation where the mother
updates has been sent to the blockchain
smart contract upon actually will be in
an encrypted form and the way a new
secure application to do the mother
aggregation and of course in this case
also to protect privacy we we ensure
that the mother is equal to so how this
works is that again we take an iterative
approach and in this case in particular
we actually have we have enabled this as
essential as a materially
mother always is fourteen perform so
when the animation are here oasis party
platform actually may pose computational
contract where the stock contracts
States is actually even perform and we
utilize secure computing to enable
secure computation our execution is not
contracts
well the
my contract state is stored in an
encrypted form so essentially we kind of
mind that we utilize this capital to
smart contract
primitives where again this iterative
approach at each interior iteration the
Machinima models are happening between
if you view it as as part of the state's
our confidential smart contracts well we
can't hide mites and as each it erodes
the the secret input the mother is sent
to the local devices we do handle some
key management
so the the model then gives decrypted
and the local device on the local
devices and then the clients uses its
own local data to update the local model
and then it computes that really
athletes and then it also has
differential privacy in perturbation to
ensure that they the nest authority
creates evening activity trained as
eventually private owner and then this
Brittany updates with the differential
privacy annoys Alice is then again at
encrypted and the send to the also
static route to the highlights of our
contracts whether my smart contracts in
then combines the screening updated that
you measure different differentially
planets perturbations and through the
secure application and then compute the
next iteration after update mode so
again by taking this iterative approach
within the news this combines
combination is my contract to
coordinates the distributed dimension
and in our training across the different
devices to enable decentralize the
practice area so now I'm going to give
you an example of actual application
that we have in the domain of anomaly
detection so in this case essentially we
can update the head - my contract to
enable especially to achieve commercial
model for anomaly detection and in
particular in this case for anomaly
detection we look at the application of
a system block another detection so as
computers around throughout certain
programs other times it produces the
system loss and this is perhaps contains
very useful information and one can try
to train which million others to go over
this system now so try to detect
anomalies essentially one way to do
system of anomaly detection and you
think bringing is over here to between a
sequence model and then using the
sequence model we can then go
this is not to try to detect anomalies
so so in our case essentially were to
use the liberal system lot and then
Trinity through you see this
decentralized fertility to actually
train and update drama on our plasma and
we achieve we enable strong privacy
protection well as system achieve high
utility and in many settings with
utility extension which is close to the
centralized model so to summarize we
have proposed a new paradigm can't be
centralized federal revenue where we
don't need to Villa and the trust and
incentive ready and we provide much
British efficiency for training teacher
with much mini model then the
peer-to-peer setting now with the strong
privacy protection and the beauty
incentive mechanisms and this the
sentiments friendly bringing has been
enabled by the ISIS party platform with
its unique capabilities to operate a
skill ability and also privacy
protection so right so with the Oasis
Network a week here as I just
demonstrated it's the first project
smart contractor on that can enable this
type of solutions and decentralized
and we we hope encouraged everyone to to
build the new applications and the Oasis
Network and we recently launched the
algorithm that 2.0 and also we release a
number of new developer tools within
with a new developer experience to make
it really easy to build applications on
top of the platform and in particular
also equally new and as we are
developing new the capacity is in
particular to make it easier for a
developer to build our secret
applications and we are and we are
inviting know the operatives and to join
our and our
and we'll be starting out a patent team
and also we'll be launching a public
destination and with the state
competition so the speaking competition
will be coming in a little interval and
we really welcome everyone to to join
the sticky competition and again we look
forward to have people ask the network
and to build new applications that
couldn't be built before thank you
[Applause]