Why Machine Intelligence Struggles in Cybersecurity: Core Paradigms

Machine Intelligence: Core Essence and Paradigms

The core essence of machine intelligence is the autonomous acquisition of knowledge from the environment, enabling machines to perceive, reason, decide, and act without human intervention. Security, viewed as a knowledge‑centric confrontation between intelligent agents, highlights why AI has struggled to deliver robust security solutions.

General‑Purpose Technologies and Human Development

Throughout history, a handful of general‑purpose technologies (GPTs) such as agriculture, the steam engine, electricity, computing, and now AI have repeatedly reshaped productivity and society. Each era provides energy or data to machines: mechanical power in the steam age, electrical power in the electric age, data in the information age, and knowledge in the intelligent age.

History of Machine Intelligence

From Tesla’s 1882 AC generator to Turing’s 1936 machine concept, the evolution of AI has passed through symbolic, connectionist, and behaviorist paradigms. Milestones include the first neural network (1949), the Dartmouth AI conference (1956), the rise of expert systems, the deep‑learning resurgence (2012), and recent breakthroughs by Hinton, LeCun, and Bengio.

From Data‑Driven to Intelligence‑Driven

Data‑driven security relies on humans to interpret summarized data, while intelligence‑driven security lets machines make online decisions directly from raw data, turning the decision‑making主体 from humans to autonomous agents.

Core Paradigm of Intelligent Systems

A genuine intelligent system comprises four subsystems: perception (collecting raw data), cognition (extracting knowledge), decision (planning and strategizing), and action (interacting with the environment). Continuous feedback closes the loop, allowing the system to evolve.

Intelligent Security Levels (L0‑L5)

The article proposes a six‑level maturity model for security AI: L0 (manual), L1 (assistive), L2 (low autonomy), L3 (moderate autonomy), L4 (high autonomy in limited domains), and L5 (full autonomy across domains). Most current products sit at L1, with few reaching L2; true intelligent security systems have yet to achieve L3 or higher.