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

Secure firmware update is an important stage in the Internet of Things (IoT) device life-cycle Prior techniques, designed for other computational settings, are not readily suitable for IoT devices, since they do not consider idiosyncrasies of a realistic large-scale IoT deployment This motivates our design of architecture for secure software update of realistic embedded devices ( ASSURED ), a secure and scalable update framework for IoT ASSURED includes all stakeholders in a typical IoT update ecosystem, while providing end-to-end security between manufacturers and devices To demonstrate its feasibility and practicality, ASSURED is instantiated and experimentally evaluated on two commodity hardware platforms Results show that ASSURED is considerably faster than current update mechanisms in realistic settings

/pdf/assured-architecture-for-secure-software-update-of-realistic-1pyd2uxd9v.pdf

ASSURED: Architecture for Secure Software Update of Realistic Embedded Devices

Remote Attestation (RA) is a distinct security service that allows a trusted verifier (V rf) to measure the software state of an untrusted remote prover (P rv). If correctly implemented, RA allows V rf to remotely detect if P rv is in an illegal or compromised state. Although several RA approaches have been explored (including hardware-based, software-based, and hybrid) and many concrete methods have been proposed, comparatively little attention has been devoted to formal verification. In particular, thus far, no RA designs and no implementations have been formally verified with respect to claimed security properties. In this work, we take the first step towards formal verification of RA by designing and verifying an architecture called VRASED: Verifiable Remote Attestation for Simple Embedded Devices. VRASED instantiates a hybrid (HW/SW) RA codesign aimed at low-end embedded systems, e.g., simple IoT devices. VRASED provides a level of security comparable to HW-based approaches, while relying on SW to minimize additional HW costs. Since security properties must be jointly guaranteed by HW and SW, verification is a challenging task, which has never been attempted before in the context ofRA. We believe that VRASED is the first formally verified RA scheme. To the best of our knowledge, it is also the first formal verification of a HW/SW co-design implementation of any security service. To demonstrate VRASED’s practicality and low overhead, we instantiate and evaluate it on a commodity platform (TI MSP430). VRASED was deployed using the Basys3 Artix-7 FPGA and its implementation is publicly available.

/pdf/vrased-a-verified-hardware-software-co-design-for-remote-26358nkrsf.pdf

{VRASED}: A Verified Hardware/Software Co-Design for Remote Attestation

Group key agreement (GKA) is a fundamental building block for securing peer group communication systems (GCS). Several group key agreement protocols were proposed in the past, all assuming an underlying group communication infrastructure. This paper presents a performance evaluation of 5 notable GKA protocols integrated with a reliable group communication system (Spread). They are: centralized group key distribution (CKD), Burmester-Desmedt (BD), Steer et al. (STR), group Diffie-Hellman GDH) and tree-based group Diffie-Hellman (TGDH).. We present concrete results obtained in experiments on local- and wide-area networks. Our analysis of these results offers insights into their relative scalability and practicality.

On the performance of group key agreement protocols

The paper considers the problem of key agreement in a group setting with highly dynamic group member population A protocol suite, called CLIQUES, is developed by extending the well known Diffie-Hellman key agreement method to support dynamic group operations Constituent protocols are provably secure and efficient

Cliques: A new approach to group key agreement

In the last decade, Remote Attestation (RA) emerged as a distinct security service for detecting attacks on embedded devices, cyber-physical systems (CPS) and Internet of Things (IoT) devices. RA involves verification of current internal state of an untrusted remote hardware platform (prover) by a trusted entity (verifier). RA can help the latter establish a static or dynamic root of trust in the prover and can also be used to construct other security services, such as software updates and secure deletion. Various RA techniques with different assumptions, security features and complexities, have been proposed for the single-prover scenario. However, the advent of IoT brought about the paradigm of many interconnected devices, thus triggering the need for efficient collective attestation of a (possibly mobile) group or swarm of provers. Though recent work has yielded some initial concepts for swarm attestation, several key issues remain unaddressed, and practical realizations have not been explored. This paper's main goal is to advance swarm attestation by bringing it closer to reality. To this end, it makes two contributions: (1) a new metric, called QoSA: Quality of Swarm Attestation, that captures the information offered by a swarm attestation technique; this allows comparing efficacy of multiple protocols, and (2) two practical attestation protocols -- called LISAa and LISAs -- for mobile swarms, with different QoSA features and communication and computation complexities. Security of proposed protocols is analyzed and their performance is assessed based on experiments with prototype implementations.

https://dl.acm.org/doi/pdf/10.1145/3052973.3053010

Gene Tsudik

Papers

ASSURED: Architecture for Secure Software Update of Realistic Embedded Devices

{VRASED}: A Verified Hardware/Software Co-Design for Remote Attestation

On the performance of group key agreement protocols

Cliques: A new approach to group key agreement

Lightweight Swarm Attestation: A Tale of Two LISA-s