{"product_id":"privacy-and-security-for-large-language-models","title":"Privacy and Security for Large Language Models: Hands-On Privacy-Preserving Techniques for Personalized AI  by Baihan Lin","description":"\u003ch2\u003ePrivacy and Security for Large Language Models: Hands-On Privacy-Preserving Techniques for Personalized AI  by Baihan Lin\u003c\/h2\u003e\n\u003cp data-path-to-node=\"6\"\u003eThe core thesis of \u003ci data-path-to-node=\"6\" data-index-in-node=\"19\"\u003ePrivacy and Security for Large Language Models\u003c\/i\u003e is that foundation models introduce entirely new attack surfaces that traditional cybersecurity architectures are fundamentally ill-equipped to handle. Large Language Models are highly fluid, probabilistic systems. They do not just execute explicit code paths; they interpret natural language prompts, memorize training data characteristics, and rely on external retrieval tools (like RAG databases) that can be easily manipulated. Lin establishes that securing production AI requires a comprehensive \u003cb data-path-to-node=\"6\" data-index-in-node=\"567\"\u003edefense-in-depth framework\u003c\/b\u003e that guards the model across its entire lifecycle: from raw training datasets to runtime token inferences.\u003c\/p\u003e\n\u003cp data-path-to-node=\"7\"\u003e\u003cspan class=\"text-block-with-attachment\"\u003e\u003cspan class=\"attachment-container search-images\"\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"7\"\u003e\u003cspan class=\"text-block-with-attachment\"\u003e\u003cspan\u003eRather than offering generic security tips, Lin walks readers through the exact mechanics of advanced AI exploitation and defense. The book outlines how attackers manipulate context windows through automated \u003cb data-path-to-node=\"7\" data-index-in-node=\"208\"\u003eindirect prompt injections\u003c\/b\u003e, extract confidential enterprise secrets via \u003cb data-path-to-node=\"7\" data-index-in-node=\"280\"\u003edata leakage exploits\u003c\/b\u003e, and force corporate chatbots to bypass safety protocols using complex \u003cb data-path-to-node=\"7\" data-index-in-node=\"373\"\u003ejailbreaking vectors\u003c\/b\u003e. To counter these threats, the text serves as an operational masterclass in cutting-edge mitigation frameworks. It details how to mathematically guarantee user anonymity using \u003cb data-path-to-node=\"7\" data-index-in-node=\"570\"\u003eDifferential Privacy (DP)\u003c\/b\u003e, run computations on untrusted clouds using \u003cb data-path-to-node=\"7\" data-index-in-node=\"640\"\u003eHomomorphic Encryption\u003c\/b\u003e, and build real-time guardrail networks that actively sanitize user inputs and model outputs.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"7\"\u003e\u003cspan class=\"text-block-with-attachment\"\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cdiv class=\"code-block ng-tns-c3299913081-59 ng-animate-disabled ng-trigger ng-trigger-codeBlockRevealAnimation\" data-hveid=\"0\" data-ved=\"0CAAQhtANahgKEwjvvJOByMeUAxUAAAAAHQAAAAAQhQE\"\u003e\n\u003c!----\u003e\n\u003cdiv class=\"formatted-code-block-internal-container ng-tns-c3299913081-59\"\u003e\n\u003cdiv class=\"animated-opacity ng-tns-c3299913081-59\"\u003e\n\u003c!----\u003e\n\u003cpre class=\"ng-tns-c3299913081-59\"\u003e\u003ccode role=\"text\" data-test-id=\"code-content\" class=\"code-container formatted ng-tns-c3299913081-59 no-decoration-radius\"\u003e\u003c\/code\u003e\u003cbr\u003e\u003c\/pre\u003e\n\u003cp data-path-to-node=\"30\"\u003eAs our regional enterprise ecosystem rapidly adopts corporate AI solutions, fintech automation, and intelligent database integrations, security and compliance are becoming top priorities. However, many engineering leads and technical teams are moving fast without a clear safety net. They deploy live chatbots and autonomous agents that pull directly from proprietary company data, leaving themselves highly vulnerable to sophisticated cyber exploits. A single successful prompt injection attack or data leakage incident can compromise customer trust, expose corporate secrets, and result in massive regulatory fines.\u003c\/p\u003e\n\u003cp data-path-to-node=\"31\"\u003e \u003c\/p\u003e\n\u003cp data-path-to-node=\"31\"\u003e\u003ci data-path-to-node=\"31\" data-index-in-node=\"0\"\u003ePrivacy and Security for Large Language Models\u003c\/i\u003e provides the precise, technical blueprint needed to secure these systems. Baihan Lin bypasses high-level philosophical debates and delivers an immensely practical, code-driven security guide. He provides local CTOs, security engineers, and DevOps leads with a clear, step-by-step roadmap to harden their systems against modern threats, prevent expensive data breaches, and build production-grade AI platforms that pass strict institutional audits. It is an indispensable technical playbook for anyone ready to eliminate AI vulnerabilities and deploy secure, robust intelligent software at scale.\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eLanguage: English.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eGenre: Artificial Intelligence.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eBinding: সেলাই করা বাইন্ডিং\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eQuality: Premium Quality Books.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003ePrinting: High Quality Printing.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003ePaper: Eye Friendly paper (Cream White)\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eCover: Matt cover (Paperback).\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Royal Books BD","offers":[{"title":"Default Title","offer_id":47228067315897,"sku":null,"price":290.0,"currency_code":"BDT","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0780\/0874\/6169\/files\/Privacy_and_Security_for_Large_Language_Models.webp?v=1779271202","url":"https:\/\/royalbooksbd.com\/products\/privacy-and-security-for-large-language-models","provider":"Royal Books BD","version":"1.0","type":"link"}