*00:17* [Pub][ePrint]
Automatic Search of Truncated Impossible Differentials and Applications, by Shengbao Wu, Mingsheng Wang
Finding the longest impossible differentials is an essential assignment in proceedingimpossible differential cryptanalysis.

In this paper, we introduce a novel tool to search the longest truncated impossible

differentials for word-oriented block ciphers with bijective S-boxes. It costs polynomial time to

return a flag indicating whether a truncated differential is impossible under several filter conditions.

To demonstrate the strength of our tool, we show that it allows to automatically

find the longest truncated impossible differentials for many word-oriented block ciphers.

It independently rediscovers all known truncated impossible differentials on nine round CLEFIA.

What\'s more, it finds

new and longest truncated impossible differentials for the AES, ARIA, Camellia without $FL$ and $FL^{-1}$ layers, E2, MIBS,

LBlock and Piccolo.

Finally,

we give an impossible differential of 14-round LBlock to illustrate that our tool is more powerful than the $\\mathcal{U}$-method and UID-method.

We expect that the tool proposed in this paper will be useful for evaluating the security of block ciphers

against impossible differentials, especially when one tries to design a word-oriented block cipher with bijective S-boxes.

*00:17* [Pub][ePrint]
Quadratic Span Programs and Succinct NIZKs without PCPs, by Rosario Gennaro and Craig Gentry and Bryan Parno and Mariana Raykova
We introduce a new characterization of the NP complexity class, called Quadratic Span Programs (QSPs), which is a natural extension of span programs defined by Karchmer and Wigderson. Our main motivation is the construction of succinct arguments of NP-statements that are quick to construct and verify. QSPs seem well-suited for this task, perhaps even better than Probabilistically Checkable Proofs (PCPs).In 2010, Groth constructed a NIZK argument in the common reference string (CRS) model for Circuit-SAT consisting of only 42 elements in a bilinear group. Interestingly, his argument does not (explicitly) use PCPs. But his scheme has some disadvantages -- namely, the CRS size and prover computation are both quadratic in the circuit size. In 2011, Lipmaa reduced the CRS size to quasi-linear, but with prover computation still quadratic.

Using QSPs we construct a NIZK argument in the CRS model for Circuit-SAT consisting of just 7 group elements. The CRS size is linear in the circuit size, and prover computation is quasi-linear, making our scheme seemingly quite practical. (The prover only needs to do a linear number of group operations; the quasi-linear computation is a multipoint evaluation and interpolation.)

Our results are complementary to those of Valiant (TCC 2008) and Bitansky et al. (2012), who use \"bootstrapping\" (recursive composition) of arguments to reduce CRS size and prover and verifier computation. QSPs also provide a crisp mathematical abstraction of some of the techniques underlying Groth\'s and Lipmaa\'s constructions.

*00:17* [Pub][ePrint]
Efficient Dissection of Composite Problems, with Applications to Cryptanalysis, Knapsacks, and Combinatorial Search Problems, by Itai Dinur and Orr Dunkelman and Nathan Keller and Adi Shamir
In this paper we show that a large class of diverse problems have abicomposite structure which makes it possible to solve them with a new

type of algorithm called {\\it dissection}, which has much better time/memory

tradeoffs than previously known algorithms. A typical example is the problem

of finding the key of multiple encryption schemes with $r$ independent

$n$-bit keys. All the previous error-free attacks required time $T$ and memory

$M$ satisfying $TM = 2^{rn}$, and even if ``false negatives\'\' are allowed, no

attack could achieve $TM

*00:17* [Pub][ePrint]
Differentially Private Continual Monitoring of Heavy Hitters from Distributed Streams, by T-H. Hubert Chan and Mingfei Li and Elaine Shi and Wenchang Xu
We consider applications scenarios where an untrusted aggregator wishes to continually monitor the heavy-hitters across a set of distributed streams. Since each stream can contain sensitive data, such as the purchase history of customers, we wish to guarantee the privacy of each stream, while allowing the untrusted aggregator to accurately detect the heavy hitters and their approximate frequencies.Our protocols are scalable in settings where the volume of streaming data is large, since we guarantee low memory usage and processing overhead by each data source, and low communication overhead between the data sources and the aggregator.