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

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

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

"Grid" computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high performance orientation. In this article, the authors define this new field. First, they review the "Grid problem," which is defined as flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources--what is referred to as virtual organizations. In such settings, unique authentication, authorization, resource access, resource discovery, and other challenges are encountered. It is this class of problem that is addressed by Grid technologies. Next, the authors present an extensible and open Grid architecture, in which protocols, services, application programming interfaces, and software development kits are categorized according to their roles in enabling resource sharing. The authors describe requirements that they believe any such mechanisms must satisfy and discuss the importance of defining a compact set of intergrid protocols to enable interoperability among different Grid systems. Finally, the authors discuss how Grid technologies relate to other contemporary technologies, including enterprise integration, application service provider, storage service provider, and peer-to-peer computing. They maintain that Grid concepts and technologies complement and have much to contribute to these other approaches.

The Anatomy of the Grid: Enabling Scalable Virtual Organizations

Unattended sensor networks operating in hostile environments might collect data that represents a high-value target for the adversary. The unattended sensor's inability to off-load -- in real time -- sensitive data to a safe external entity makes it easy for the adversary to mount a focused attack aimed at eliminating or modifying certain offending data. In order to facilitate data survival, sensors must collectively attempt to confuse the adversary by changing the location and the representation of the data. Unfortunately, since the network is unattended most of the time, the adversary (even if it is limited in scale/scope of simultaneous compromise) has free reign and can move freely among sensors, compromising them at will.A very similar "mobile adversary" model is quite well-known in cryptography, having spawned an entire line of research, called "proactive cryptography". However, the mobile adversary model has not been embraced by the security research community. This talk will address several flavors of the mobile adversary in the context of unattended sensor networks, discuss some viable and simple counter-measures (with varying degrees of effectiveness) and outline open problems and challenges.

Confronting a mobile adversary in unattended sensor networks

An increasing number of mobile devices are incorporating cameras, allowing users to record videos at any time, anywhere. This opens up a wide variety of applications, most notably security-critical ones, where videos are used as evidence or include sensitive content. Examples of such applications include (but are not limited to): (i) citizen journalists recording important events (e.g., protests), (ii) courts using videos as evidence, and (iii) electronic legal contract-signing platforms using videos to identify signing users [1].

Vronicle: verifiable provenance for videos from mobile devices

A group signature scheme allows any group member to sign on behalf of the group in an anonymous and unlinkable fashion. In the event of a dispute, a designated trusted entity can reveal the identity of the signer. Group signatures are claimed to have many useful applications such as voting and electronic cash. A number of group signature schemes have been proposed to-date. However, in order for the whole group signature concept to become practical and credible, the problem of secure and efficient group member revocation must be addressed. In this paper, we construct a new revocation method for group signatures based on the signature scheme by Ateniese et al. [ACJT]. This new method represents an advance in the state-of-the-art since the only revocation schemes proposed thus far are either: 1) based on implicit revocation and the use of fixed time periods, or 2) require the signature size to be linear in the number of revoked members. Our method, in contrast, does not rely on time periods, offers constant-length signatures and constant work for the signer.

/pdf/quasi-efficient-revocation-of-group-signatures-z8hbfxk2bm.pdf

Quasi-Efficient Revocation of Group Signatures.

Mobile Ad-Hoc Networks (MANETs) are partic- ularly useful and well-suited for critical scenarios, including military, law enforcement as well as emergency rescue and dis- aster recovery. When operating in hostile or suspicious settings, MANETs require communication security and privacy, especially, in underlying routing protocols. Unlike most networks, where communication is based on long-term identities (addresses), we argue that the location-centric communication paradigm is better-suited for privacy in suspicious MANETs. To this end, we construct an on-demand location-based anonymous MANET routing protocol (PRISM) that achieves privacy and security against both outsider and insider adversaries. We analyze the security, privacy and performance of PRISM and compare it to alternative techniques. Results show that PRISM is more efficient and offers better privacy than prior work. Index Terms—Privacy, communication system security, com- munication system routing, on-demand routing protocol, mobile communication, location-based communication, military commu- nication.

/pdf/privacy-preserving-location-based-on-demand-118cfkwxxh.pdf

Privacy-Preserving Location-Based On-Demand

Internetworks that are global in scale, contain mul- tiple administrative domains, and support a range of services present special requirements for routing. Multiple administrative domains introduce the need for policy-sensitive routing. Service heterogeneity intensifies the requirement for type of service (TOS) routing, as well as other protocol support for handling a range of services, from datagrams to multimedia streams. This paper summarizes the key concepts and protocols devel- oped as part of the Interdomain Policy Routing (IDPR) archi- tecture. We place particular emphasis on the route installation and packet forwarding mechanisms because they are critical to protocol performance and differ significantly from current practice in datagram wide area networks.

Gene Tsudik

Papers

Confronting a mobile adversary in unattended sensor networks

Vronicle: verifiable provenance for videos from mobile devices

Quasi-Efficient Revocation of Group Signatures.

Privacy-Preserving Location-Based On-Demand

A Protocol for Forwarding Route Establishment and Packet Across Multidomain Internets