175 research outputs found
Balancing Security, Performance and Deployability in Encrypted Search
Encryption is an important tool for protecting data, especially data stored in the cloud. However, standard encryption techniques prevent efficient search. Searchable encryption attempts to solve this issue, protecting the data while still providing search functionality. Retaining the ability to search comes at a cost of security, performance and/or utility.
An important practical aspect of utility is compatibility with legacy systems. Unfortunately, the efficient searchable encryption constructions that are compatible with these systems have been proven vulnerable to attack, even against weaker adversary models.
The goal of this work is to address this security problem inherent with efficient, legacy compatible constructions. First, we present attacks on previous constructions that are compatible with legacy systems, demonstrating their vulnerability. Then we present two new searchable encryption constructions. The first, weakly randomized encryption, provides superior security to prior easily deployable constructions, while providing similar ease of deployment and query performance nearly identical to unencrypted databases. The second construction, EDDiES, provides much stronger security at the expense of a slight regression on performance.
These constructions show that it is possible to achieve a better balance of security and performance with the utility constraints that come with deployment in legacy systems
Analyse de la propriété d'incrémentalité dans le modèle de calcul du programme de branchement
Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal
Myeloid-Specific Rictor Deletion Induces M1 Macrophage Polarization and Potentiates In Vivo Pro-Inflammatory Response to Lipopolysaccharide
The phosphoinositide-3-kinase (PI3K)/protein kinase B (Akt) axis plays a central role in attenuating inflammation upon macrophage stimulation with toll-like receptor (TLR) ligands. The mechanistic target of rapamycin complex 2 (mTORC2) relays signal from PI3K to Akt but its role in modulating inflammation in vivo has never been investigated. To evaluate the role of mTORC2 in the regulation of inflammation in vivo, we have generated a mouse model lacking Rictor, an essential mTORC2 component, in myeloid cells. Primary macrophages isolated from myeloid-specific Rictor null mice exhibited an exaggerated response to TLRs ligands, and expressed high levels of M1 genes and lower levels of M2 markers. To determine whether the loss of Rictor similarly affected inflammation in vivo, mice were either fed a high fat diet, a situation promoting chronic but low-grade inflammation, or were injected with lipopolysaccharide (LPS), which mimics an acute, severe septic inflammatory condition. Although high fat feeding contributed to promote obesity, inflammation, macrophage infiltration in adipose tissue and systemic insulin resistance, we did not observe a significant impact of Rictor loss on these parameters. However, mice lacking Rictor exhibited a higher sensitivity to sceptic shock when injected with LPS. Altogether, these results indicate that mTORC2 is a key negative regulator of macrophages TLR signalling and that its role in modulating inflammation is particularly important in the context of severe inflammatory challenges. These observations suggest that approaches aimed at modulating mTORC2 activity may represent a possible therapeutic approach for diseases linked to excessive inflammation.Howard Hughes Medical Institute (Investigator)National Institutes of Health (U.S.) (NIH grant CA103866)National Institutes of Health (U.S.) (NIH grant CA129105)National Institutes of Health (U.S.) (NIH grant AI47389)Canadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaFonds de la recherche en santé du Québe
Early Detection and Analysis of Leakage Abuse Vulnerabilities
In order to be useful in the real world, efficient cryptographic constructions often reveal, or ``leak,\u27\u27 more information about their plaintext than one might desire. Up until now, the approach for addressing leakage when proposing a new cryptographic construction has focused entirely on qualifying exactly what information is leaked. Unfortunately there has been no way to predict what the real-world impact of that leakage will be.
In this paper, we argue in favor of an analytical approach for quantifying the vulnerability of leaky cryptographic constructions against attacks that use leakage to recover the plaintext or other sensitive information. In contrast to the previous empirical and ad-hoc approach for identifying and assessing such vulnerabilities, analytical techniques can be integrated much earlier in the design lifecycle of a new construction, and the results of the analysis apply much more broadly across many different kinds of data.
We applied the proposed framework to evaluate the leakage profiles of five recent constructions for deterministic and order-revealing encryption. Our analysis discovered powerful attacks against every construction that we analyzed, and with only one possible exception, the attack allows the adversary to recover virtually any plaintext with only an exponentially small probability of error. We hope that these results, together with the proposed analytical framework, will help spur the development of new efficient constructions with improved leakage profiles that meaningfully limit the power of leakage abuse attacks in the real world
The Strength of Weak Randomization: Efficiently Searchable Encryption with Minimal Leakage
Efficiently searchable and easily deployable encryption schemes enable an untrusted, legacy service such as a relational database engine to perform searches over encrypted data. The ease with which such schemes can be deployed on top of existing services makes them especially appealing in operational environments where encryption is needed but it is not feasible to replace large infrastructure components like databases or document management systems. Unfortunately all previously known approaches for efficiently searchable encryption are vulnerable to inference attacks where an adversary can use knowledge of the distribution of the data to recover the plaintext with high probability.
In this paper, we present the first efficiently searchable, easily deployable database encryption scheme that is provably secure against inference attacks even when used with real, low-entropy data. Ours is also the only efficiently searchable construction that provides any provable security for protecting multiple related attributes (columns) in the same database. Using this ESE construction as a building block, we give an efficient construction for performing range queries over encrypted data.
We implemented our constructions in Haskell and used them to query encrypted databases of up to 10 million records. In experiments with a local Postgres database and with a Google Cloud Platform database, the response time for our encrypted queries is not excessively slower than for plaintext queries. With the use of parallel query processing, our encrypted queries can achieve similar and in some cases superior performance to queries on
the plaintext
BioWarehouse: a bioinformatics database warehouse toolkit
BACKGROUND: This article addresses the problem of interoperation of heterogeneous bioinformatics databases. RESULTS: We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. CONCLUSION: BioWarehouse embodies significant progress on the database integration problem for bioinformatics
Flavor Unification and Discrete Nonabelian Symmetries
Grand unified theories with fermions transforming as irreducible
representations of a discrete nonabelian flavor symmetry can lead to realistic
fermion masses, without requiring very small fundamental parameters. We
construct a specific example of a supersymmetric GUT based on the flavor
symmetry --- a subgroup of --- which can explain the
observed quark and lepton masses and mixing angles. The model predicts
and gives a neutrino mass eV, with other neutrino masses much lighter. Combined
constraints of light quark masses and perturbative unification place flavor
symmetry breaking near the GUT scale; it may be possible to probe these
extremely high energies by continuing the search for flavor changing neutral
currents.Comment: 24 pages, UCSD-PTH-93-30 (uuencoded file; requires epsf.tex,
available from this bulletin board
Flavor from Strongly Coupled Supersymmetry
Strongly coupled supersymmetric theories can give rise to composite quarks
and leptons at low energy. We show that the internal structure of these
particles can explain the origin of three generations and provide a qualitative
understanding of mass ratios and mixing angles between the different flavors of
fermions, all within a renormalizable theory. The main point of the paper is to
show how fermion masses and mixing angles can result from a ``dual''
Frogatt-Nielsen mechanism: fields neutral under which carry flavor quantum numbers are confined within quarks and
leptons, and from their perturbative interactions arises the observed flavor
structure.Comment: 28 pages, 5 figures, LATEX. A few typos corrected and references
adde
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