2026-english-2-80 詳見活動內容 »
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90折
$2,484Comptia Linux+ Study Guide: Essential Exam Prep -
90折
$2,520Video Generation with AI: Working with Diffusion Transformers and Multimodal Learning (Paperback) -
90折
$1,890Mapping Experiences: A Complete Guide to Activating Customer-Centered Collaboration 3/e -
90折
$2,493Databricks Certified Generative AI Engineer Associate Study Guide: Generative AI with Databricks -
90折
$2,502Ai-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python -
90折
$2,268Observability Engineering: Achieving Production Excellence, 2/e (Paperback) -
90折
$1,935Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data -
90折
$1,980The C4 Model: Visualizing Software Architecture (Paperback) -
90折
$1,935Learning Cloud Security: Cloud Computing and Security Architecture Essentials -
90折
$2,502Vision Language Models: Building Vlms with Hugging Face (Paperback) -
90折
$2,106High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark 2/e -
90折
$1,944Python for Excel: A Modern Environment for Automation and Data Analysis -
90折
$1,440Managing AI Projects: Drive Innovation and Successfully Navigate the Full AI Project Lifecycle (Paperback) -
90折
$2,520AI-Ready Data Blueprints: From Raw Data to Ai-Driven Innovation (Paperback) -
90折
$1,917Certified Kubernetes Application Developer (Ckad) Study Guide: In-Depth Guidance and Practice (Paperback) -
90折
$2,484Large Language Models: The Hard Parts: Open Source AI Solutions for Common Pitfalls (Paperback) -
90折
$1,917Real-Time Intelligence with Microsoft Fabric: Empowering Data-Driven Decisions in the Era of AI (Paperback) -
90折
$2,484Rag with Python Cookbook: Practical Recipes from Data Preprocessing to LLM Agents (Paperback) -
90折
$2,448Hands-On LLM Serving and Optimization: Hosting Llms at Scale (Paperback) -
90折
$2,205Vector Databases: A Practical Introduction (Paperback) -
90折
$2,205Generative AI on Microsoft Azure: From Large Language Models to Advanced Multi-Agent Systems (Paperback) -
90折
$1,890Learning Generative AI Tools for Excel: Speed Up Your Everyday Tasks with Microsoft Excel, Copilot, Chatgpt, and Beyond (Paperback) -
90折
$2,520Learning Automl: Automating ML Pipelines with Autogluon, Leading Frameworks, and Real-World Integration (Paperback) -
90折
$2,520Transformers: The Definitive Guide: Applications Beyond NLP (Paperback) -
90折
$1,809UX Skills for Business Strategy: Articulating Impact for Product, User, and Business Outcomes
商品描述
By 2020, the Internet of Things (IoT) will consist of millions of computational devices intimately connected to real-world aspects of human life. In this insightful book, Professor Sean Smith, who worked in information security long before the web appeared, explains that if we build the IoT the way we built the current internet and other information technology initiatives, we’re headed for trouble.
With a focus on concrete solutions, The Internet of Risky Things explains how we can avoid simple flaws that have plagued several dramatic IT advances in recent decades. Developers, engineers, industrial designers, makers, and researchers will explore "design patterns of insecurities" and learn what’s required to route around or fix them in the nascent IoT.
- Examine bugs that plague large-scale systems, including integer overflow, race conditions, and memory corruption
- Look at successful and disastrous examples of previous quantum leaps in health IT, the smart grid, and autonomous vehicles
- Explore patterns in coding, authentication, and cryptography that led to insecurity
- Learn how blunders that led to spectacular IT disasters could have been avoided
商品描述(中文翻譯)
在2020年,物聯網(IoT)將由數百萬個計算設備組成,這些設備與人類生活的現實世界緊密相連。在這本深具洞察力的書中,肖恩·史密斯教授(Professor Sean Smith)解釋了如果我們以建造當前互聯網和其他資訊科技倡議的方式來建設物聯網,那麼我們將面臨麻煩。史密斯教授在網路出現之前就已經從事資訊安全工作。
《風險物品的互聯網》(The Internet of Risky Things)專注於具體解決方案,解釋了我們如何避免在近幾十年來困擾多項重大資訊科技進展的簡單缺陷。開發人員、工程師、工業設計師、創客和研究人員將探討「不安全設計模式」,並了解在新興的物聯網中,如何繞過或修復這些問題所需的條件。
- 檢視困擾大型系統的錯誤,包括整數溢位、競爭條件和記憶體損壞
- 觀察健康資訊科技、智慧電網和自駕車等先前重大飛躍的成功與災難性範例
- 探索導致不安全的編碼、身份驗證和加密模式
- 學習導致驚人資訊科技災難的失誤如何能夠避免
