290 research outputs found
Lime: Data Lineage in the Malicious Environment
Intentional or unintentional leakage of confidential data is undoubtedly one
of the most severe security threats that organizations face in the digital era.
The threat now extends to our personal lives: a plethora of personal
information is available to social networks and smartphone providers and is
indirectly transferred to untrustworthy third party and fourth party
applications.
In this work, we present a generic data lineage framework LIME for data flow
across multiple entities that take two characteristic, principal roles (i.e.,
owner and consumer). We define the exact security guarantees required by such a
data lineage mechanism toward identification of a guilty entity, and identify
the simplifying non repudiation and honesty assumptions. We then develop and
analyze a novel accountable data transfer protocol between two entities within
a malicious environment by building upon oblivious transfer, robust
watermarking, and signature primitives. Finally, we perform an experimental
evaluation to demonstrate the practicality of our protocol
Models and Algorithms for Graph Watermarking
We introduce models and algorithmic foundations for graph watermarking. Our
frameworks include security definitions and proofs, as well as
characterizations when graph watermarking is algorithmically feasible, in spite
of the fact that the general problem is NP-complete by simple reductions from
the subgraph isomorphism or graph edit distance problems. In the digital
watermarking of many types of files, an implicit step in the recovery of a
watermark is the mapping of individual pieces of data, such as image pixels or
movie frames, from one object to another. In graphs, this step corresponds to
approximately matching vertices of one graph to another based on graph
invariants such as vertex degree. Our approach is based on characterizing the
feasibility of graph watermarking in terms of keygen, marking, and
identification functions defined over graph families with known distributions.
We demonstrate the strength of this approach with exemplary watermarking
schemes for two random graph models, the classic Erd\H{o}s-R\'{e}nyi model and
a random power-law graph model, both of which are used to model real-world
networks
Towards Provably Invisible Network Flow Fingerprints
Network traffic analysis reveals important information even when messages are
encrypted. We consider active traffic analysis via flow fingerprinting by
invisibly embedding information into packet timings of flows. In particular,
assume Alice wishes to embed fingerprints into flows of a set of network input
links, whose packet timings are modeled by Poisson processes, without being
detected by a watchful adversary Willie. Bob, who receives the set of
fingerprinted flows after they pass through the network modeled as a collection
of independent and parallel queues, wishes to extract Alice's embedded
fingerprints to infer the connection between input and output links of the
network. We consider two scenarios: 1) Alice embeds fingerprints in all of the
flows; 2) Alice embeds fingerprints in each flow independently with probability
. Assuming that the flow rates are equal, we calculate the maximum number of
flows in which Alice can invisibly embed fingerprints while having those
fingerprints successfully decoded by Bob. Then, we extend the construction and
analysis to the case where flow rates are distinct, and discuss the extension
of the network model
Authentication with Distortion Criteria
In a variety of applications, there is a need to authenticate content that
has experienced legitimate editing in addition to potential tampering attacks.
We develop one formulation of this problem based on a strict notion of
security, and characterize and interpret the associated information-theoretic
performance limits. The results can be viewed as a natural generalization of
classical approaches to traditional authentication. Additional insights into
the structure of such systems and their behavior are obtained by further
specializing the results to Bernoulli and Gaussian cases. The associated
systems are shown to be substantially better in terms of performance and/or
security than commonly advocated approaches based on data hiding and digital
watermarking. Finally, the formulation is extended to obtain efficient layered
authentication system constructions.Comment: 22 pages, 10 figure
Publicly Detectable Watermarking for Language Models
We construct the first provable watermarking scheme for language models with
public detectability or verifiability: we use a private key for watermarking
and a public key for watermark detection. Our protocol is the first
watermarking scheme that does not embed a statistical signal in generated text.
Rather, we directly embed a publicly-verifiable cryptographic signature using a
form of rejection sampling. We show that our construction meets strong formal
security guarantees and preserves many desirable properties found in schemes in
the private-key watermarking setting. In particular, our watermarking scheme
retains distortion-freeness and model agnosticity. We implement our scheme and
make empirical measurements over open models in the 7B parameter range. Our
experiments suggest that our watermarking scheme meets our formal claims while
preserving text quality
Watermarking for multimedia security using complex wavelets
This paper investigates the application of complex wavelet transforms to the field of digital data hiding. Complex wavelets offer improved directional selectivity and shift invariance over their discretely sampled counterparts allowing for better adaptation of watermark distortions to the host media. Two methods of deriving visual models for the watermarking system are adapted to the complex wavelet transforms and their performances are compared. To produce improved capacity a spread transform embedding algorithm is devised, this combines the robustness of spread spectrum methods with the high capacity of quantization based methods. Using established information theoretic methods, limits of watermark capacity are derived that demonstrate the superiority of complex wavelets over discretely sampled wavelets. Finally results for the algorithm against commonly used attacks demonstrate its robustness and the improved performance offered by complex wavelet transforms
Hashing Based Software Watermarking for Source Code Files
Software is developed and delivered to clients as a routine part of software engineering life cycle . Software is quite an expensive entity. However various attacks are possible on software to make its illegal use. Different solutions are there to prevent piracy. Software watermarking embeds a watermark in the source code so that it is undetectable yet it proves the ownership of the developer. The technique has been tested for C++ source code files, however, it can be applicable on any other language. The proposed techniques scans the code for all possible constants, forms a hash sequence using MD5 algorithm that calculates the watermark and stores in Date & Watermark Value Repository (DWVR)
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