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

Routing is a critical function in multi-hop mobile ad hoc networks (MANETs). A number of MANET-oriented routing protocols have been proposed, of which DSR is widely considered both the simplest and the most effective. At the same time, security in MANETs – especially, routing security – presents a number of new and interesting challenges. Many security techniques geared for MANETs have been developed, among which Ariadne is the flagship protocol for securing DSR. The focus of this work is on securing the route discovery process in DSR. Our goal is to explore a range of suitable cryptographic techniques with varying flavors of security, efficiency and robustness. The Ariadne approach (with TESLA), while very efficient, assumes loose time synchronization among MANET nodes and does not offer non-repudiation. If the former is not possible or the latter is desired, an alternative approach is necessary. To this end, we construct a secure route discovery protocol (SRDP) which allows the source to securely discover an authenticated route to the destination using either aggregated message authentication codes (MACs) or multi-signatures. Several concrete techniques are presented and their efficiency and security are compared and evaluated.

SRDP: Secure route discovery for dynamic source routing in MANETs

The emerging and much-touted Internet of Things (IoT) presents a variety of security and privacy challenges. Prominent among them is the establishment of trust in remote IoT devices, which is typically attained via remote attestation, a distinct security service that aims to ascertain the current state of a potentially compromised remote device. Remote attestation ranges from relatively heavy-weight secure hardware-based techniques, to light-weight software-based ones, and also includes approaches that blend software (e.g., control-flow integrity) and hardware features (e.g., PUFs). In this paper, we survey the landscape of state-of-the-art attestation techniques from the IoT device perspective and argue that most of them have a role to play in IoT trust establishment.

Things, Trouble, Trust: On Building Trust in IoT Systems

An unattended wireless sensor network (UWSN) might collect valuable data representing an attractive target for the adversary. Since a sink visits the network infrequently, unattended sensors cannot immediately off-load data to some safe external entity. With sufficient time between sink visits, a powerful mobile adversary can easily compromise sensor-collected data.In this paper, we propose two schemes (CoMAC and ExCo) that leverage sensor co-operation to achieve data authentication. These schemes use standard (and inexpensive) symmetric cryptographic primitives coupled with key evolution and few messages exchange. We provide security analysis for proposed schemes and assess their effectiveness via simulations. We show that proposed schemes cope well with real WSN issues, such as message loss and sensor failure. We also compare the two schemes with respect to robustness and overhead, which allows network designers to carefully select the right scheme and tune appropriate system parameters.

Collaborative authentication in unattended WSNs

A fairly common modern setting entails users, each in possession of a personal wireless device, wanting to communicate securely, via their devices. If these users (and their devices) have no prior association, a new security context must be established. In order to prevent potential attacks, the initial context (association) establishment process must involve only the intended devices and their users.A number of methods for initial secure association of two devices have been proposed; their usability factors have been explored and compared extensively. However, a more challenging problem of initial secure association of a group of devices (and users) has not received much attention. Although a few secure group association methods have been proposed, their usability aspects have not been studied, especially, in a comparative manner. This paper discusses desirable features and evaluation criteria for secure group association, identifies suitable methods and presents a comparative usability study. Results show that some simple methods (e.g., peer- or leader-based number comparisons) are quite attractive for small groups, being fast, reasonably secure and well-received by users.

https://www3.cs.stonybrook.edu/~rnithyanand/pubs/ubicomp2010_pre.pdf

Groupthink: usability of secure group association for wireless devices

As the global society becomes more interconnected and more privacy-conscious, communication protocols must balance access control with protecting participants' privacy. A common current scenario involves an authorized party (client) who needs to retrieve sensitive information held by another party (server) such that: (1) the former only gets the information for which it is duly authorized, (2) the latter does not learn what information information is retrieved. To address this scenario, in this paper, we introduce and explore the concept of Privacy-preserving Policy-based Information Transfer (PPIT). We construct three PPIT schemes based, respectively, on: RSA, Schnorr and IBE techniques. We then investigate various performance improvements and demonstrate the practicality of proposed PPIT schemes.

https://www.emilianodc.com/PAPERS/PETS09.pdf

Gene Tsudik

Papers

SRDP: Secure route discovery for dynamic source routing in MANETs

Things, Trouble, Trust: On Building Trust in IoT Systems

Collaborative authentication in unattended WSNs

Groupthink: usability of secure group association for wireless devices

Privacy-Preserving Policy-Based Information Transfer