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

The increasing use of internetworking protocols to connect administratively heterogeneous networks has raised the question of how an organization can control the flow of information across its network boundaries. One method for doing so is the use of visas, a cryptographic technique for authenticating and authorizing a flow of datagrams. Two visa protocols are presented and evaluated: one that requires distributed state information in gateways and one that uses additional encryptions instead of distributed state. Applications for such visa protocols include access control, accounting and billing for packet transit, and network resource management. >

/pdf/visa-protocols-for-controlling-interorganizational-datagram-2qgtd9jgek.pdf

Visa protocols for controlling interorganizational datagram flow

In recent years, wireless sensor networks (WSNs) have been a very popular research topic, offering a treasure trove of systems, networking, hardware, security, and application-related problems. Much of prior research assumes that the WSN is supervised by a constantly present sink and sensors can quickly offload collected data. In this paper, we focus on unattended WSNs (UWSNs) characterized by intermittent sink presence and operation in hostile settings. Potentially lengthy intervals of sink absence offer greatly increased opportunities for attacks resulting in erasure, modification, or disclosure of sensor-collected data. This paper presents an in-depth investigation of security problems unique to UWSNs (including a new adversarial model) and proposes some simple and effective countermeasures for a certain class of attacks.

Data Security in Unattended Wireless Sensor Networks

Mobile ad-hoc networks (MANETs) are particularly useful and well-suited for critical scenarios, including military, law enforcement as well as emergency rescue and disaster recovery. When operating in hostile or suspicious settings, MANETs require communication security and privacy, especially, in underlying routing protocols. This paper focuses on privacy aspects of mobility. 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 security, privacy and performance of PRISM and compare it to alternative techniques. Results show that PRISM is more computationally efficient and offers better privacy than prior work.

/pdf/prism-privacy-friendly-routing-in-suspicious-manets-and-vr0btuglxp.pdf

PRISM: Privacy-friendly routing in suspicious MANETs (and VANETs)

The proliferation of group-centric computing and communication motivates the need for mechanisms to provide group access control. Group access control includes mechanisms for admission as well as revocation/eviction of group members. Particularly in ad hoc groups, such as peer-to-peer (P2P) systems and mobile ad hoc networks (MANETs), secure group admission is needed to bootstrap other group security services. In addition, secure membership revocation is required to evict misbehaving or malicious members. Unlike centralized (e.g., multicast) groups, ad hoc groups operate in a decentralized manner and accommodate dynamic membership which make access control both interesting and challenging. Although some recent work made initial progress as far as the admission problem, the membership revocation problem has not been addressed.

In this paper, we develop an identity-based group admission control technique which avoids certain drawbacks of previous (certificate-based) approaches. We also propose a companion membership revocation mechanism. Our solutions are robust, fully distributed, scalable and, at the same time, reasonably efficient, as demonstrated by the experimental results.

Identity-Based access control for ad hoc groups

With the widespread use of e-business coupled with the public’s awareness of data privacy issues and recent database security related legislations, incorporating security features into modern database products has become an increasingly important topic. Several database vendors already offer integrated solutions that provide data privacy within existing products. However, treating security and privacy issues as an afterthought often results in inefficient implementations. Some notable RDBMS storage models (such as the N-ary Storage Model) suffer from this problem. In this work, we analyze issues in storage security and discuss a number of trade-offs between security and efficiency. We then propose a new secure storage model and a key management architecture which enable efficient cryptographic operations while maintaining a very high level of security. We also assess the performance of our proposed model by experimenting with a prototype implementation based on the well-known TPC-H data set.

/pdf/a-framework-for-efficient-storage-security-in-rdbms-jgol0x79nq.pdf

Gene Tsudik

Papers

Visa protocols for controlling interorganizational datagram flow

Data Security in Unattended Wireless Sensor Networks

PRISM: Privacy-friendly routing in suspicious MANETs (and VANETs)

Identity-Based access control for ad hoc groups

A Framework for Efficient Storage Security in RDBMS