February 2024 MBR The Computer Shelf

[Midwest Book Review]

The Computer Shelf

Algorithmic Thinking, second edition
Daniel Zingaro
No Starch Press
www.nostarch.com
9781718503229, $49.99, PB, 480pp

https://www.amazon.com/Algorithmic-Thinking-2nd-Problem-Based-Introduction/dp/1718503229

Synopsis: Are you hitting a wall with data structures and algorithms? Whether you're a student prepping for coding interviews or an independent learner, this newly updated and expanded second edition of "Algorithmic Thinking: Unlock Your Programming Potential" by Daniel Zingaro is your essential guide to efficient problem-solving in programming.

You will be able to unlock the power of data structures and algorithms by learning about the intricacies of hash tables, recursion, dynamic programming, trees, graphs, and heaps. Become proficient in choosing and implementing the best solutions for any coding challenge.

"Algorithmic Thinking" includes real-world, competition-proven code examples. The programs and challenges featuring in "Algorithmic Thinking" aren't just theoretical -- they are drawn from real programming competitions enabling you to train with problems that have tested and honed the skills of coders around the world.

"Algorithmic Thinking" is ideal for getting 'interview ready" by preparing yourself for coding interviews with practice exercises that help you think algorithmically, weigh different solutions, and implement the best choices efficiently.

All the code examples are written in C and designed for clarity and accessibility to those familiar with languages like C++, Java, or Python. If you need help with the C code, no problem: recommended reading resources are also included.

Simply stated, "Algorithmic Thinking" is the complete package, providing the solid foundation you need to elevate your coding skills to the next level.

Critique: Now is a fully updated and expanded second edition, Daniel Zingaro's "Algorithmic Thinking: Unlock Your Programming Potential" from No Starch Press is an ideal, comprehensive, and thoroughly 'user friendly' instructional resource for C Programming Language students and software development professionals alike. Also available in a digital book format (Kindle, $29.99), "Algorithmic Thinking: Unlock Your Programming Potential: 2nd Edition" is a highly recommended addition to personal, professional, and college/university library Computer Program Structured Design collections and curriculum studies lists.

Editorial Note: Dr. Daniel Zingaro (https://danielzingaro.com) is an Associate Professor of Mathematical and Computational Sciences at the University of Toronto Mississauga. He is well known for his uniquely interactive approach to teaching and internationally recognized for his expertise in active learning. He is also the author of Learn to Code by Solving Problems (No Starch Press) and a co-author of Learn AI-Assisted Python Programming (Manning).

Math for Security
Daniel Reilly
No Starch Press
www.nostarch.com
9781718502567, $49.99, PB, 312pp

https://www.amazon.com/Applied-Math-Security-Introduction-Programmers/dp/1718502567

Synopsis: For those who wish to explore the intersection of mathematics and computer security with this engaging and accessible guide, "Math for Security: From Graphs and Geometry to Spatial Analysis" will equip you with essential tools to tackle complex security problems head on. All you need are some basic programming skills. Once you've set up your development environment and reviewed the necessary Python syntax and math notation in the early chapters, you will be able to dive deep into practical applications, leveraging the power of math to analyze networks, optimize resource distribution, and much more.

Of special note are the final chapters that will enable you to take your projects from proof of concepts to viable applications and explore options for delivering them to end users.

As you work through various security scenarios, you will be able to: Employ packet analysis and graph theory to detect data exfiltration attempts in a network; Predict potential targets and find weaknesses in social networks with Monte Carlo simulations; Use basic geometry and OpenCell data to triangulate a phone's location without GPS; Apply computational geometry to Voronoi diagrams for use in emergency service planning; Train a facial recognition system with machine learning for real-time identity verification; Use spatial analysis to distribute physical security features effectively in an art gallery.

Critique: Impressively comprehensive, expertly organized and thoroughly 'user friendly' in presentation, "Math for Security: From Graphs and Geometry to Spatial Analysis" will prove of particular interest to aspiring security professionals, social network analysts, or innovators seeking to create cutting-edge security solutions."Math for Security" will empower readers with an interest in web encryption, computer hacking, and Python programming to resolve complex problems with precision and confidence -- as well as embracing the intricate world of math as a secret weapon in creating and maintaining computer security. While a core addition to personal, professional, corporate, and college/university library Computer/Database Security collections and supplemental curriculum studies lists, it should be noted that "Math for Security" is also available in a digital book format (Kindle, $29.99).

Editorial Note: Daniel Reilly is a security researcher, analyst, and consultant based out of Seattle, WA. He has worked in the security field for 20 years, more than half of which has been spent developing and managing operational security for small businesses.

The Art of Randomness
Ronald T. Kneusel
No Starch Press
www.nostarch.com
9781718503243 $49.99 pbk / $29.99 Kindle

https://www.amazon.com/Art-Randomness-Using-Randomized-Algorithms/dp/1718503245

Synopsis: The Art of Randomness is a hands-on guide to mastering the many ways you can use randomized algorithms to solve real programming and scientific problems. You'll learn how to use randomness to run simulations, hide information, design experiments, and even create art and music. All you need is some Python, basic high school math, and a roll of the dice.

Author Ronald T. Kneusel focuses on helping you build your intuition so that you'll know when and how to use random processes to get things done. You'll develop a randomness engine (a Python class that supplies random values from your chosen source), then explore how to leverage randomness to:

Simulate Darwinian evolution and optimize with swarm-based search algorithms
Design scientific experiments to produce more meaningful results by making them truly random
Implement machine learning algorithms like neural networks and random forests
Use Markov Chain Monte Carlo methods to sample from complex distributions
Hide information in audio files and images, generate art, and create music
Reconstruct original signals and images from only randomly sampled data

Scientific anecdotes and code examples throughout illustrate how randomness plays into areas like optimization, machine learning, and audio signals. End-of-chapter exercises encourage further exploration.

Whether you're a programmer, scientist, engineer, mathematician, or artist, you'll find The Art of Randomness to be your ticket to discovering the hidden power of applied randomness and the ways it can transform your approach to solving problems, from the technical to the artistic.

Critique: The Art of Randomness: Randomized Algorithms in the Real World is a useful reference and resource for anyone who needs to apply the power of randomized algorithms, including programmers, scientists, engineers, mathematicians, even artists and musicians. A wealth of graphs, tables, and example programing code in Python to help clarify the text's discussion of applications such as reconstructing original signals or images from randomly sampled data, implementing machine learning algorithms like neural networks and random forests, and designing scientific experiments with better randomness, in order to generate more meaningful results. The Art of Randomness is highly recommended especially for college library collections and the personal study of aspiring and practicing professionals. It should be noted for personal reading lists that The Art of Randomness is also available in a Kindle edition ($29.99).

Javascript Crash Course
Nick Morgan
No Starch Press
www.nostarch.com
9781718502260 $49.99 pbk / $23.99 Kindle

https://www.amazon.com/JavaScript-Crash-Course-Nick-Morgan/dp/1718502265

Synopsis: JavaScript Crash Course is a fun-filled, fast-paced introduction to programming with JavaScript. Dive right in and you'll be writing code, solving problems, and building working web applications and games in no time. You'll start by learning fundamental programming concepts, such as variables, arrays, objects, functions, conditionals, loops, classes, and more. Aided by engaging examples and hands-on exercises, you'll build on this foundation and combine JavaScript with HTML and CSS to create interactive web applications that you can run right away.

Then you'll put your new skills into play with three substantial projects: a Pong-style game with a virtual opponent, an app that generates electronic music, and a platform for visualizing data fetched from an API.

Along the way, you'll learn how to:

Update web pages in real time by manipulating the Document Object Model
Trigger functions in response to events like key presses and mouse clicks
Generate graphics and animations with JavaScript and HTML's Canvas element
Visualize data with the D3.js library and scalable vector graphics (SVG)
Make electronic music with Tone.js and the Web Audio API

If you've been thinking about digging into programming, JavaScript Crash Course will get you writing real programs fast. Why wait any longer? Jump on your magic carpet and ride!

Critique: Javascript Crash Course: A Hands-On, Project-Based Introduction to Programming is a user-friendly guide to quickly learning Javascript for writing code, solving problems, building web applications, making games, and much more. Chapters cover Javascript basics, and offer several interactive projects to try one's hand at coding as soon as possible! Ideal for high school and college students, self-study, and public library collections, Javascript Crash Course is a "must-have" for anyone who needs to learn Javascript fast for school, business, or just plain fun. Highly recommended! It should be noted for personal reading lists that Javascript Crash Course is also available in a Kindle edition ($23.99).

The Android Malware Handbook
Qian Han, et al.
No Starch Press
www.nostarch.com
9781718503304, $49.99, PB, 320pp

https://www.amazon.com/Android-Malware-Handbook-Detection-Analysis/dp/171850330X

Synopsis: "The Android Malware Handbook: Detection and Analysis by Human and Machine" is a groundbreaking guide to Android malware. It distills years of research by machine learning experts in academia and members of Meta and Google's Android Security teams. The result is a comprehensive introduction to detecting common threats facing the Android eco-system today.

"The Android Malware Handbook" explores the history of Android malware 'in the wild' since the operating system was first launched and then focuses on static and dynamic approaches to analyzing real malware specimens. Next, it examine machine learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models.

In adapting these machine learning strategies to the identification of malware categories like banking trojans, ransomware, and SMS fraud, you will Dive deep into the source code of real malware; Explore the static, dynamic, and complex features you can extract from malware for analysis; Master the machine learning algorithms useful for malware detection; Survey the efficacy of machine learning techniques at detecting common Android malware categories.

Critique: Comprehensive and exceptionally user friendly in organization and presented, "The Android Malware Handbook: Detection and Analysis by Human and Machine" is an ideal textbook from the team of Android experts Qian Han, Salvador Mandujano, Sebastian Porst, V.S. Subrahmanian, Sai Deep Tetali, and Yanhai Xiong should be considered essential reading for anyone with an interest in computer viruses, computer software testing, and computer hacking. While a core addition to personal, professional, and college/university library Computer Science collections and supplemental curriculum studies lists, it should be noted that "The Android Malware Handbook" is also available in a digital book format (Kindle, $29.99).

Editorial Note #1: Qian Han, is a Research Scientist at Meta since 2021, received his PhD in Computer Science from Dartmouth College and his Bachelor's in Electronic Engineering from Tsinghua University, Beijing, China.

Editorial Note #2: Salvador Mandujano, Security Engineering Manager at Google, has led product security engineering, malware reverse engineering and payments security teams. Before Google, he held senior security research and architecture positions at Intel and Nvidia. He has a PhD in Artificial Intelligence from Tecnologico de Monterrey, an MSc in Computer Science from Purdue, an MBA from The University of Texas, and a BSc in Computer Engineering from Universidad Nacional Autonoma de Mexico.

Editorial Note #3: Sebastian Porst is manager of Google's Android Application Security Research team, which tries to predict or research novel attacks on Android devices and Android users by malware or through app vulnerabilities. He has an MSc Masters from Trier University of Applied Sciences, Germany in 2007.

Editorial Note #4: V.S. Subrahmanian is the Walter P. Murphy Professor of Computer Science and Buffet Faculty Fellow in the Buffet Institute of Global Affairs at Northwestern University. Prof. Subrahmanian is one of the world's foremost experts at the intersection of AI and security issues. He has written eight books, edited ten, and published over 300 refereed articles.

Editorial Note #5: Sai Deep Tetali, Principal Engineer and Tech Lead Manager at Meta, works on privacy solutions for augmented and virtual reality applications. He spent 5 years at Google developing machine learning techniques to detect Android malware and has a PhD from University of California Los Angeles.

Editorial Note #6: Yanhai Xiong is currently an Assistant Professor in the Department of Computer Science and Engineering at the University of Louisville. She has a PhD from Nanyang Technological University focusing on applying AI techniques to improve the efficiency of electric vehicle infrastructure and a BS in Engineering from the University of Science and Technology of China. will guide you through the Android threat landscape and prepare you for the next wave of malware to come.

EDITOR'S NOTE:

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