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A
Hello,
everybody,
my
name
is
Gasol.
Thank
you.
So
much
for
coming
I'm
gonna
be
talking
about
what
we've
been
doing
at
hash
matter
on
some
research
and
development
on
privacy-preserving
peer-to-peer
networks.
There
is
no
way
I
have
enough
time
to
talk
about
everything,
so
please,
let's
grab
a
beer
afterwards
and
discuss
about
all
the
things
we
bringing
in
today.
So
all
right,
so
the
cool
thing
about
decentralized
applications,
decentralized
networks-
is
that
we
can
remove
these
huge
entity
in
the
middle
of
the
interactions
between
different
users.
Right,
that's
super
cool.
A
It
brings
us
a
lot
of
interesting,
brings
a
lot
of
interesting
properties
to
the
network
or
to
the
services.
One
of
the
properties
that
I'm
interested
the
most
is
privacy
right.
So
one
of
the
big
problems
nowadays
is
that
basically,
these
big
entities
know
or
potentially
know
everything
I
do
right.
What
are
the
websites
I'm
visiting?
A
A
This
really
hash
tables
are
basically
like
the
bread
and
butter
of
IVFs,
so
collaborative
peer-to-peer
overlay
network
that
allows
peers
in
the
network
to
resolve
content,
resolve
store
contents
in
a
completely
centralized
way,
no
need
for
any
central
authority,
very
scalable,
etc,
etc.
So
it's
in
a
very
high
level.
It
provides
every
node
in
the
network
with
the
API
to
get
a
specific
content,
ID
and
store
a
specific
on
today.
All
right
so
I
think
I,
don't
know
how
to
play
DS,
but
maybe
I
can
just
go
ahead.
I,
don't
think
I
had
okay
cool.
A
So
the
idea
this
is
just
a
show
like
very
briefly,
very
high-level.
How
actually,
as
we
all
know,
the
sort
of
a
DHT
routing
and
work.
So,
basically,
if
I
don't
know
who
has
a
particular
ID
or
Content
ID
I
can
actually
ask
to
the
peers,
which
I'd
know
if
they
know
someone
which
is
closer
to
that
ID.
So,
basically
I
do
this
recursively
right
and
if
you
have
very
high
level,
that's
more
or
less
how
things
work
and
what
we
actually.
A
Okay,
cool.
Thank
you.
Thank
you,
so
yeah.
So
the
idea
is
that
this
is
basically
a
like
a
collaborative
network
right.
So
basically,
because
we
don't
have
anyone
who
knows
where
all
the
resources
are.
We
have
to
rely
on
our
sort
of
friends,
not
friends
but
other
nodes
in
the
network
to
resolve
this
content
right.
So
basically,
what's
happening
is
that
we
are
in
this
huge
place
full
of
people,
and
we
are
sharing
at
each
other
about
what
we
want
from
the
network
right.
A
But
the
people
around
me
know
that
I'm
talking
with
this
person
right-
and
this
is
like
metadata
leakage
that
comes
from
these
sort
of
collaborative
networks-
and
this
is
a
big
problem
when
it
comes
to
peer-to-peer
networks
right
because,
if
especially,
if
we're
talking
about
content
addressed
of
all
the
rest
of
all
networks,
what
we
have
is
that
the
fact
that
we're
connecting
or
requesting
for
to
a
particular
from
a
particular
peer.
It
means
that
we're
interested
in
this
particular
theory.
A
So
the
idea
is
that
or
the
big
question
here,
how
about
privacy
right?
The
issues
are
very
cool,
very
simple
algorithms
or
protocols
that
work
very
well,
but
unfortunately,
the
same
properties
that
make
the
HDS
great
building
blocks
for
the
decentralized
or
centralized
web.
It
also
makes
them
very
vulnerable
privacy
attacks
right
and
there's
a
bunch
of
like
there's
a
bunch
of
literature
on
these.
A
This
is
no
science
rocket
science,
and
the
problem,
though,
is
that
if
you
want
to
build
sort
of
an
application
layer
on
top
of
this
with
the
hash
tables
or
any
other
appear
to
be
a
protocol,
we
actually
are
trickling
or
kind
of
bubbling
up
all
these
privacy
problems.
So
the
applications
on
top
of
build
built
on
top
of
these
protocols
are
actually
gonna
have
the
same
privacy
vulnerabilities.
A
So
one
very
quick
example
of
these
is
that,
if
I'm
sort
of
storing
my
own
web
page
and
I'm,
actually
you
as
a
sort
of
part
of
the
DHD
part
of
IVFs
network,
you
can
actually
try
to
find
the
provider
of
this
particular
webpage,
which
is
mine
and
most
likely,
because
I'm,
the
only
one
who's
actually
storing
and
and
pinning
in
my
own
web
page
you're
gonna
get
me
as
a
provider
right.
So
the
problem
is
that
as
I
actually
move
around,
you
can
check
very
likely.
A
So
one
of
the
main
ideas
here
is
that
the
problem
is
that,
like
in
centralized
services,
basically
when
an
entity
gains
a
lot
of
information
about
what
people
are
doing
and
in
naive
decentralized
networks,
that's
information
exactly
potentially
some
resolvable
by
everyone
in
the
network
and
everyone
might
be
your
neighbor
might
be
your
like
X
company,
government,
etcetera,
etcetera.
So
this
is
exactly
the
kind
of
problem
we'll
try
to
solve
and
there's
a
bunch
of
other
really
cool
attacks.
A
If
we
could
talk
about,
let's
talk
about
it
later
on,
so
all
right
so
about
the
solutions
right,
that's
basically
what
we've
been
working
on.
The
first
thing
is
to
see
privacy
in
a
more
granular
way.
So
basically,
we
want
to
make
sure
that
initiator,
a
bunch
of
like
not
just
see
privacy
as
something
okay,
so
yeah,
there's
a
bunch
of
like
the
different
granularities
of
what
privacy
means
in
a
decentralized
network.
You
can
talk
about
these
later
on
and
we
also
obviously,
on
top
of
this
one
low
latency
decentralization.
A
We
want
scalability
at
etc,
because
we're
very
small
in
terms
of
like
experience
on
connected
services,
so
we
all
want
embedded
in
our
future
of
the
internet
and
connected
service
all
right.
So
what
we're
doing
now
is
at
the
hatch
matter
is
like
trying
to
come
up
with
this
sort
of
a
middle
layer
between
the
overlay,
Network,
routing
and
application
layer
right
in
which
we
can
embed
like
protocols
or
primitives.