Cybersecurity for 2025: Principles, Practice, and Preemptive Strategy (en Inglés)
Reseña del libro "Cybersecurity for 2025: Principles, Practice, and Preemptive Strategy (en Inglés)"
Cybersecurity for 2025: Principles, Practice, and Preemptive Strategy is your no-nonsense guide to surviving-and thriving-in tomorrow's digital battlefield. This book packs five tight parts into one actionable read. Part 1 nails the 2025 threat scene: nation-states, ransomware-as-a-service, AI deepfakes, and the new "preemptive" mindset that beats detect-and-respond. You get NIST CSF 2.0's fresh Govern function, Parkerian Hexad, Saltzer-Schroeder principles, and STRIDE threat modeling. Part 2 dives into attack vectors-TCP/IP hijacks, buffer overflows, XSS, SSRF, side-channels, and browser data leaks. Part 3 flips to Blue Team ops: SOC workflows, IR playbooks, forensics, SIEM labs with Splunk, and Zero Trust pillars. Part 4 arms the Red Team: MITRE ATT&CK, nmap, Nessus, Metasploit, and ethical lotL tactics. Part 5 tackles the frontier-cloud shared responsibility, IoT botnets, OT convergence, AI malware, model poisoning, plus GRC, policy writing, and a picoCTF capstone. Every chapter ends with a hands-on lab, tabletop, or code exercise you can run today. What sets this book apart is ruthless 2025 focus and zero fluff. Other texts rehash 2015 exploits or bury you in theory; this one cites ENISA 2025, CrowdStrike 2025, Gartner preemptive forecasts, and Cloudflare's live PQC rollout. You won't find recycled OWASP Top 10 lists-you'll build IAM policies in AWS JSON, craft iptables rules, debug stack-smashing in GDB, and write Splunk alerts that trigger in real time. Labs use free tools: Kali, Metasploitable, Nessus Essentials, Splunk trial, Wireshark, OpenSSL, Shodan. The capstone sends you to picoCTF to prove you can pivot from crypto to forensics to rev-eng under pressure. No other single volume ties academic rigor (MIT, Stanford, CMU syllabi) to street-ready skills while prepping you for the quantum cliff and AI arms race. (c) 2025 Azhar ul Haque Sario. This work is not affiliated with, endorsed by, or sponsored by MIT, Stanford, Carnegie Mellon, NIST, ENISA, CrowdStrike, Gartner, Cloudflare, Splunk, Tenable, or any cited entity. All trademarks are used under nominative fair use for identification and educational purposes only.
