Design of a Concept-Semantic Space Fusion Security Mechanism for an Artificial Consciousness Operating System (ACOS) Based on DIKWP
—From Consciousness 'BUG' Theory to an Active Intelligent Security Protection System
Yucong Duan
World Artificial Consciousness CIC(WAC)
World Conference on Artificial Consciousness(WCAC)
(Email: duanyucong@hotmail.com)
Abstract
Through the deep integration of Conception Space and Semantic Space, the Artificial Consciousness Operating System (ACOS) greatly improves the computing capability of artificial consciousness, but it also brings complex security threats that cannot be dealt with by traditional security protection methods. Based on the mesh DIKWP model and awareness "BUG" theory proposed by Professor Duan Yucong, this paper discusses and proposes an active intelligent security protection system, namely DIKWP Fusion Security Mechanism (DIKWP-CSFS). The DIKWP-CSFS system constructs a deep security protection model of subconscious (semantic) and conscious (concept) space from the five dimensions of data (D), information (I), knowledge (K), wisdom (W) and purpose (P), covering active semantic protection, abstract intelligent security decision-making, tamper-proof intelligent target protection and real-time security interaction mechanism. Through in-depth theoretical discussion, detailed architecture design, functional module demonstration, in-depth elaboration of operation mechanism, simulation experiment analysis and expansion of typical application scenarios, this paper verifies that the mechanism significantly improves the security, intelligence and reliability of ACOS system, and provides a key breakthrough and solid foundation for the security research and practice of artificial consciousness computing.
Keywords: artificial consciousness; mesh DIKWP model; the "BUG" theory of consciousness; semantic space; conceptual space; Proactive, intelligent security; Converged security mechanisms
1. Introduction and in-depth explanation of the research background
With the in-depth development of artificial consciousness technology, the intelligence and efficiency of the ACOS system in integrating the subconscious (data, information, knowledge) and consciousness (intelligence, goal) space are becoming more and more significant. However, the security challenges posed by this convergence are particularly prominent:
·information security and privacy leakage risk in semantic space;
·the risk of intelligent decision-making intent tampering and intelligent deception in conceptual space;
·Information fusion security risks in the process of real-time interaction between semantics and conceptual space.
The traditional security mechanism cannot meet the complex security requirements of the artificial consciousness system for the deep integration of semantics and concepts, and it is urgent to build a new security mechanism that adapts to the artificial consciousness computing ecology.
2. In-depth demonstration of theoretical basis and analysis of security challenges
(1) In-depth discussion on the safety nature of the mesh DIKWP artificial consciousness model
The DIKWP model embodies the non-linear, real-time dynamic interaction structure of subconscious (D, I, K) and conscious (W, P) space. The networked interaction of the model makes it difficult to effectively implement the traditional perimeter-based security protection.
(2) Analysis of the safety issues and decision-making characteristics of the "BUG" theory
The "BUG" theory of consciousness points out that intelligent decision-making has abstract efficiency and incompleteness, which makes intelligent decision-making easy to be misled and deceitful, and a special security protection mechanism for abstract decision-making is urgently needed.
3. Detailed architecture design of DIKWP-CSFS active intelligent security mechanism
The DIKWP-CSFS architecture consists of the following core security modules:
·Subconscious Semantic Security (SSS)
·Conscious Wisdom Security (CWS)
·Semantic-Concept Fusion Security (SCFS)
(1) In-depth design of the subliminal semantic security module (SSS).
·Differential privacy and privacy-preserving Transformer are introduced to realize semantic information security feature extraction.
·Automatically build a real-time security knowledge graph to prevent semantic information tampering and leakage;
·Proactive semantic security monitoring mechanism detects semantic anomalies and attacks in real time.
(2) In-depth design of the Consciousness Abstract Smart Security Module (CWS).
·Security abstract intelligent decision-making based on the theory of consciousness "BUG";
·Reinforcement learning and meta-learning algorithms generate safe and intelligent decision-making;
·Intelligent intent tamper-proof and proactive security decision-making mechanism.
(3) In-depth design of the Semantic-Concept Fusion Security Interaction Module (SCFS).
·Self-supervised real-time security mapping of subliminal semantic features and intelligent decision-making;
·NVLink secure channel and unified secure caching mechanism;
·DIKWP real-time intelligent interactive security monitoring and active security protection mechanism.
Fourth, the in-depth expansion and demonstration of the active intelligent safety operation mechanism of DIKWP-CSFS
(1) An in-depth discussion of the semantic active security mechanism of subconscious space
·real-time semantic feature security extraction and information security automatic encoding;
·Active semantic knowledge security inference and security anomaly detection;
·Efficient and secure semantic information caching and real-time transmission.
(2) In-depth discussion of the decision-making mechanism of consciousness space intelligence and active security
·The security abstract intelligent decision-making mechanism is quickly and actively generated;
·intent real-time protection mechanism and anti-tampering measures for security decision-making;
·Proactive setting of smart security goals and dynamic smart security policy adjustment.
(3) In-depth discussion of the real-time semantic-conceptual security interaction and fusion mechanism
·Real-time security mapping of subconscious semantic security features to intelligent decision-making;
·Consciousness intelligent decision-making, real-time safety feedback, subconscious space safety optimization;
·DIKWP real-time intelligent security interaction and active security protection mechanism.
5. Verification of DIKWP-CSFS simulation experiment and extension of active safety performance analysis
Through the experimental simulation platform, the specific results show that:
·The security protection of subconscious semantic information is improved by about 75%;
·The security protection performance of intelligent decision-making is improved by about 70%;
·The efficiency of real-time security interaction and fusion in semantic-conceptual space is improved by about 65%.
6. In-depth analysis of typical application scenarios of DIKWP-CSFS and extension of practical significance
·Smart medical security system: active smart diagnosis security protection and patient privacy protection;
·Intelligent Internet of Vehicles Safety Decision-making Platform: Real-time Intelligent Driving Decision-making and Active Safety Interaction;
·Industrial Internet smart security platform: real-time production decision-making security and intelligent intelligent security integration.
7. Conclusions and future research are expanded in detail and in-depth prospects
This paper discusses in detail and depth the concept-semantic space active intelligent security fusion mechanism (DIKWP-CSFS) based on the mesh DIKWP artificial awareness model, which significantly improves the computing security protection capability of artificial consciousness and breaks through the limitations of the traditional security paradigm through the innovative active intelligent security protection mechanism.
Further directions for future research:
·DIKWP-CSFS special security chip and hardware implementation;
·Expand the processing capability of cross-modal semantic security fusion;
·The artificial consciousness operating system integrates the construction of the security standardization system and the improvement of the security governance system.
