Iycee Charles de Gaulle Summary SYSTEM third parties, offline trusted third parties,

SYSTEM third parties, offline trusted third parties,



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v The
data provenance methodology, in the form of robust watermarking techniques or
adding fake data, has already been suggested in the literature and employed by
some industries.

v Hasan
et al. present a system that enforces logging of read and write actions in a
tamper-proof provenance chain. This creates the possibility of verifying the
origin of information in a document.

v Poh
addresses the problem of accountable data transfer with untrusted senders using
the term fair content tracing. He presents a general framework to compare
different approaches and splits protocols into four categories depending on
their utilization of trusted third parties, i.e., no trusted third parties,
offline trusted third parties, online trusted third parties and trusted
hardware. Furthermore, he introduces the additional properties of recipient
anonymity and fairness in association with payment.



v In
some cases, identification of the leaker is made possible by forensic
techniques, but these are usually expensive and do not always generate the
desired results.

v Most
efforts have been ad-hoc in nature and there is no formal model available.

v Additionally,
most of these approaches only allow identification of the leaker in a
non-provable manner, which is not sufficient in many cases.

v An
attacker is able to strip of the provenance information of a file, the problem
of data leakage in malicious environments is not tackled by their approach. 


v We
point out the need for a general accountability mechanism in data transfers.
This accountability can be directly associated with provably detecting a
transmission history of data across multiple entities starting from its origin.
This is known as data provenance, data lineage or source tracing.

v In
this paper, we formalize this problem of provably associating the guilty party
to the leakages, and work on the data lineage methodologies to solve the
problem of information leakage in various leakage scenarios.

v This
system defines LIME, a generic data lineage framework for data flow across
multiple entities in the malicious environment.

v We
observe that entities in data flows assume one of two roles: owner or consumer.
We introduce an additional role in the form of auditor, whose task is to
determine a guilty party for any data leak, and define the exact properties for
communication between these roles.

v In
the process, we identify an optional non-repudiation assumption made between
two owners, and an optional trust (honesty) assumption made by the auditor
about the owners.

v As
our second contribution, we present an accountable data transfer protocol to
verifiably transfer data between two entities. To deal with an untrusted sender
and an untrusted receiver scenario associated with data transfer between two
consumers, our protocols employ an interesting combination of the robust
watermarking, oblivious transfer, and signature primitives. 


v The
key advantage of our model is that it enforces accountability by design; i.e.,
it drives the system designer to consider possible data leakages and the
corresponding accountability constraints at the design stage. This helps to
overcome the existing situation where most lineage mechanisms are applied only
after a leakage has happened.

v We
prove its correctness and show that it is realizable by giving micro
benchmarking results. By presenting a general applicable framework, we
introduce accountability as early as in the design phase of a data transfer infrastructure.