14,010 research outputs found
Preserving Both Privacy and Utility in Network Trace Anonymization
As network security monitoring grows more sophisticated, there is an
increasing need for outsourcing such tasks to third-party analysts. However,
organizations are usually reluctant to share their network traces due to
privacy concerns over sensitive information, e.g., network and system
configuration, which may potentially be exploited for attacks. In cases where
data owners are convinced to share their network traces, the data are typically
subjected to certain anonymization techniques, e.g., CryptoPAn, which replaces
real IP addresses with prefix-preserving pseudonyms. However, most such
techniques either are vulnerable to adversaries with prior knowledge about some
network flows in the traces, or require heavy data sanitization or
perturbation, both of which may result in a significant loss of data utility.
In this paper, we aim to preserve both privacy and utility through shifting the
trade-off from between privacy and utility to between privacy and computational
cost. The key idea is for the analysts to generate and analyze multiple
anonymized views of the original network traces; those views are designed to be
sufficiently indistinguishable even to adversaries armed with prior knowledge,
which preserves the privacy, whereas one of the views will yield true analysis
results privately retrieved by the data owner, which preserves the utility. We
present the general approach and instantiate it based on CryptoPAn. We formally
analyze the privacy of our solution and experimentally evaluate it using real
network traces provided by a major ISP. The results show that our approach can
significantly reduce the level of information leakage (e.g., less than 1\% of
the information leaked by CryptoPAn) with comparable utility
SIG-DB: leveraging homomorphic encryption to Securely Interrogate privately held Genomic DataBases
Genomic data are becoming increasingly valuable as we develop methods to
utilize the information at scale and gain a greater understanding of how
genetic information relates to biological function. Advances in synthetic
biology and the decreased cost of sequencing are increasing the amount of
privately held genomic data. As the quantity and value of private genomic data
grows, so does the incentive to acquire and protect such data, which creates a
need to store and process these data securely. We present an algorithm for the
Secure Interrogation of Genomic DataBases (SIG-DB). The SIG-DB algorithm
enables databases of genomic sequences to be searched with an encrypted query
sequence without revealing the query sequence to the Database Owner or any of
the database sequences to the Querier. SIG-DB is the first application of its
kind to take advantage of locality-sensitive hashing and homomorphic encryption
to allow generalized sequence-to-sequence comparisons of genomic data.Comment: 38 pages, 3 figures, 4 tables, 1 supplemental table, 7 supplemental
figure
Multi-party Quantum Computation
We investigate definitions of and protocols for multi-party quantum computing
in the scenario where the secret data are quantum systems. We work in the
quantum information-theoretic model, where no assumptions are made on the
computational power of the adversary. For the slightly weaker task of
verifiable quantum secret sharing, we give a protocol which tolerates any t <
n/4 cheating parties (out of n). This is shown to be optimal. We use this new
tool to establish that any multi-party quantum computation can be securely
performed as long as the number of dishonest players is less than n/6.Comment: Masters Thesis. Based on Joint work with Claude Crepeau and Daniel
Gottesman. Full version is in preparatio
Symbolic Abstractions for Quantum Protocol Verification
Quantum protocols such as the BB84 Quantum Key Distribution protocol exchange
qubits to achieve information-theoretic security guarantees. Many variants
thereof were proposed, some of them being already deployed. Existing security
proofs in that field are mostly tedious, error-prone pen-and-paper proofs of
the core protocol only that rarely account for other crucial components such as
authentication. This calls for formal and automated verification techniques
that exhaustively explore all possible intruder behaviors and that scale well.
The symbolic approach offers rigorous, mathematical frameworks and automated
tools to analyze security protocols. Based on well-designed abstractions, it
has allowed for large-scale formal analyses of real-life protocols such as TLS
1.3 and mobile telephony protocols. Hence a natural question is: Can we use
this successful line of work to analyze quantum protocols? This paper proposes
a first positive answer and motivates further research on this unexplored path
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