There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

From the Publisher:
A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols; more than 200 tables and figures; more than 1,000 numbered definitions, facts, examples, notes, and remarks; and over 1,250 significant references, including brief comments on each paper.

Handbook of Applied Cryptography

PROBLEM TO BE SOLVED: To solve the problem, wherein it is impossible for an electronic content information provider to provide commercially secure and effective method, for a configurable general-purpose electronic commercial transaction/distribution control system. SOLUTION: In this system, having at least one protected processing environment for safely controlling at least one portion of decoding of digital information, a secure content distribution method comprises a process for encapsulating digital information in one or more digital containers; a process for encrypting at least a portion of digital information; a process for associating at least partially secure control information for managing interactions with encrypted digital information and/or digital container; a process for delivering one or more digital containers to a digital information user; and a process for using a protected processing environment, for safely controlling at least a portion of the decoding of the digital information. COPYRIGHT: (C)2006,JPO&NCIPI

https://apps.dtic.mil/dtic/tr/fulltext/u2/a423264.pdf

Systems and Methods for Secure Transaction Management and Electronic Rights Protection

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

We propose a fully functional identity-based encryption scheme (IBE). The scheme has chosen ciphertext security in the random oracle model assuming an elliptic curve variant of the computational Diffie-Hellman problem. Our system is based on the Weil pairing. We give precise definitions for secure identity based encryption schemes and give several applications for such systems.

/pdf/identity-based-encryption-from-the-weil-pairing-sfqdyadlbb.pdf

Identity-Based Encryption from the Weil Pairing

Consider Alice and Bob, who have some shared secret which helps Alice to identify Bob-impersonators, and Eve, who does not know their secret. Eve wants to impersonate Bob and "fool" Alice. If Eve is computationally unbounded, how long does she need to observe Bob before she can impersonate him? What is a good strategy for Eve? If (cryptographic) one-way functions exist, an efficient Eve cannot impersonate even very simple Bobs, but if they do not exist, can Eve learn to impersonate any efficient Bob?We formalize these questions in a new computational learning model, which we believe captures a wide variety of natural learning tasks, and tightly bound the number of observations Eve makes in terms of the secret's entropy. We then show that if one-way functions do not exist, then an efficient Eve can learn to impersonate any efficient Bob nearly as well as an unbounded Eve.For the full version of this work see (Naor & Rothblum, 2006).

/pdf/learning-to-impersonate-1xueflas62.pdf

Learning to impersonate

To distinguish between random generation in bounded, as opposed to expected, polynomial time, a model of Probabalisic Turing Machine (PTM) with the ability to make random choices with any (small) rational bias is necessary. This ability is equivalent to that of being able to simulate rolling any k-sided die (where |k| is polynomial in the length of the input). We would like to minimize the amount of hardware required for a machine with this capability. This leads to the problem of efficiently simulating a family of dice with as few different types of biased coins as possible.

On dice and coins: models of computation for random generation

Many efficient data structures use randomness, allowing them to improve upon deterministic ones. Usually, their efficiency and correctness are analyzed using probabilistic tools under the assumption that the inputs and queries are independent of the internal randomness of the data structure. In this work, we consider data structures in a more robust model, which we call the adversarial model. Roughly speaking, this model allows an adversary to choose inputs and queries adaptively according to previous responses. Specifically, we consider a data structure known as "Bloom filter" and prove a tight connection between Bloom filters in this model and cryptography. 
A Bloom filter represents a set $S$ of elements approximately, by using fewer bits than a precise representation. The price for succinctness is allowing some errors: for any $x \in S$ it should always answer `Yes', and for any $x \notin S$ it should answer `Yes' only with small probability. 
In the adversarial model, we consider both efficient adversaries (that run in polynomial time) and computationally unbounded adversaries that are only bounded in the number of queries they can make. For computationally bounded adversaries, we show that non-trivial (memory-wise) Bloom filters exist if and only if one-way functions exist. For unbounded adversaries we show that there exists a Bloom filter for sets of size $n$ and error $\varepsilon$, that is secure against $t$ queries and uses only $O(n \log{\frac{1}{\varepsilon}}+t)$ bits of memory. In comparison, $n\log{\frac{1}{\varepsilon}}$ is the best possible under a non-adaptive adversary.

Bloom Filters in Adversarial Environments

A Bloom filter is a method for reducing the space (memory) required for representing a set by allowing a small error probability. In this paper we consider a Sliding Bloom Filter: a data structure that, given a stream of elements, supports membership queries of the set of the last n elements (a sliding window), while allowing a small error probability and a slackness parameter. The problem of sliding Bloom filters has appeared in the literature in several communities, but this work is the first theoretical investigation of it. We formally define the data structure and its relevant parameters and analyze the time and memory requirements needed to achieve them. We give a low space construction that runs in $$O(1)$$O(1) time per update with high probability (that is, for all sequences with high probability all operations take constant time) and provide an almost matching lower bound on the space that shows that our construction has the best possible space consumption up to an additive lower order term.

/pdf/tight-bounds-for-sliding-bloom-filters-1fkbo2omtt.pdf

Tight Bounds for Sliding Bloom Filters

We consider Primary-Secondary-Resolver Membership Proof Systems (PSR for short) and show different constructions of that primitive. A PSR system is a 3-party protocol, where we have a primary, which is a trusted party which commits to a set of members and their values, then generates public and secret keys in order for secondaries (provers with knowledge of both keys) and resolvers (verifiers who only know the public key) to engage in interactive proof sessions regarding elements in the universe and their values. The motivation for such systems is for constructing a secure Domain Name System (DNSSEC) that does not reveal any unnecessary information to its clients.

/pdf/primary-secondary-resolver-membership-proof-systems-8ofbhddh6x.pdf

Moni Naor

Papers

Learning to impersonate

On dice and coins: models of computation for random generation

Bloom Filters in Adversarial Environments

Tight Bounds for Sliding Bloom Filters

Primary-Secondary-Resolver Membership Proof Systems