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Post-docs and interns will be in residence at Microsoft Research Redmond, the main campus of Microsoft\\\'s basic research division with over four hundred researchers in dozens of areas of computer science research. Researchers benefit from close proximity to Microsoft product units, collaborative relations and joint seminars with University of Washington, and an active research environment. For more information about MSR Redmond and the Cryptography group see: http://research.microsoft.com/aboutmsr/labs/redmond/ and http://research.microsoft.com/crypto/
The post-doctoral positions offer a competitive salary, benefits, and a relocation allowance. The term is for two years; the start date is July 1, 2014. Post-docs will report to Dr. Kristin Lauter, Research Manager for the MSR Crypto Group. Internships for graduate students will be for 10-12 weeks in Summer 2014, with flexible start date.
port various signature schemes including Direct Anonymous Attestation
(DAA), U-Prove and Schnorr signature. This signature primitive is im-
plemented by several APIs. In this paper, we show these DAA-related
APIs can be used as a static Diffie-Hellman oracle thus the security
strength of these signature schemes can be weakened by 14-bit. We pro-
pose a novel property of DAA called forward anonymity and show how
to utilize these DAA-related APIs to break forward anonymity. Then we
propose new APIs which not only remove the Static Diffie-Hellman oracle
but also support the forward anonymity, thus significantly improve the
security of DAA and the other signature schemes supported by TPM2.0.
We prove the security of our new APIs under the discrete logarithm
assumption in the random oracle model. We prove that DAA satisfy for-
ward anonymity using the new APIs under the Decision Diffie-Hellman
assumption. Our new APIs are almost as efficient as the original APIs
in TPM2.0 specification and can support LRSW-DAA and SDH-DAA
together with U-Prove as the original APIs.
be represented as the sum of two bent functions. This problem was
recently presented by N. Tokareva in studying the number of bent
functions. Firstly, many functions, such as
quadratic Boolean functions, Maiorana-MacFarland bent functions,
partial spread functions etc, are proved to be able to be
represented as the sum of two bent functions. Methods to construct
such functions from low dimension ones are also introduced. N.
Tokareva\'s main hypothesis is proved for $n\\leq 6$. Moreover,
two hypotheses which are equivalent to N. Tokareva\'s main hypothesis
are presented. These hypotheses may lead to new ideas or methods to
solve this problem. At last, necessary and sufficient conditions on
the problem when the sum of several bent functions is again a bent
function are given.
In this research paper, we have contemplated a design for cloud architecture which ensures secured movement of data at client and server end. We have used the non breakability of Elliptic curve cryptography for data encryption and Diffie Hellman Key Exchange mechanism for connection establishment. The proposed encryption mechanism uses the combination of linear and elliptical cryptography methods. It has three security checkpoints: authentication, key generation and encryption of data.
This report focuses on the IKA of two-pass MQV, without key confirmation. Arguably, implicit key authentication is the most essential security objective in authenticated key agreement. The report examines various necessary or sufficient formal conditions under which MQV may provide IKA.
Incidentally, this report defines, relies on, and inter-relates various conditions on the key deriviation function and Diffie--Hellman groups. While it should be expected that most such definitions and results are already well-known, a reader interested in these topics may be interested in this report as a kind of review, even if they have no interest in MQV whatsoever.
gaming, gambling, and computer science in general. True random number generators
need an entropy source which is a physical source with inherent uncertainty, to ensure
unpredictability of the output. In this paper we propose a new indirect approach to
collecting entropy using human errors in the game play of a user against a computer. We
argue that these errors are due to a large set of factors and provide a good source of
randomness. To show the viability of this proposal, we design and implement a game,
conduct a user study in which we collect user input in the game, and extract randomness
from it. We measure the rate and the quality of the resulting randomness that clearly
show effectiveness of the approach. Our work opens a new direction for construction of
entropy sources that can be incorporated into a large class of video games.