1. Problem Definition
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flowchart LR
A["1. Problem Definition
问题定义"] A --> B["Protected Asset
保护对象"] A --> C["Participants
参与方"] A --> D["Protection Goals
保护目标"] A --> E["Core Questions
核心问题"] B --> B1["Model Parameters
模型参数"] B --> B2["Model Functionality
模型功能"] B --> B3["Learned Representations
学习表示"] B --> B4["Model Identity and Provenance
模型身份与来源"] C --> C1["Model Owner
模型所有者"] C --> C2["Authorized User
授权用户"] C --> C3["Suspect Provider
嫌疑模型提供者"] C --> C4["Verifier or Auditor
验证者或审计者"] C --> C5["Adversary
攻击者"] D --> D1["Ownership Verification
所有权验证"] D --> D2["Unauthorized-use Prevention
防止未授权使用"] D --> D3["Piracy Detection
盗版检测"] D --> D4["Leakage Tracing
泄露追踪"] D --> D5["Model Provenance
模型来源追踪"] E --> E1["Derivative Relationship
模型派生关系"] E --> E2["Unauthorized Usage
未授权使用"] E --> E3["Model Origin
模型来源"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E nodeBranch;
问题定义"] A --> B["Protected Asset
保护对象"] A --> C["Participants
参与方"] A --> D["Protection Goals
保护目标"] A --> E["Core Questions
核心问题"] B --> B1["Model Parameters
模型参数"] B --> B2["Model Functionality
模型功能"] B --> B3["Learned Representations
学习表示"] B --> B4["Model Identity and Provenance
模型身份与来源"] C --> C1["Model Owner
模型所有者"] C --> C2["Authorized User
授权用户"] C --> C3["Suspect Provider
嫌疑模型提供者"] C --> C4["Verifier or Auditor
验证者或审计者"] C --> C5["Adversary
攻击者"] D --> D1["Ownership Verification
所有权验证"] D --> D2["Unauthorized-use Prevention
防止未授权使用"] D --> D3["Piracy Detection
盗版检测"] D --> D4["Leakage Tracing
泄露追踪"] D --> D5["Model Provenance
模型来源追踪"] E --> E1["Derivative Relationship
模型派生关系"] E --> E2["Unauthorized Usage
未授权使用"] E --> E3["Model Origin
模型来源"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E nodeBranch;
2. Reactive Ownership Verification
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flowchart LR
A["2. Reactive Ownership Verification
事后所有权验证"] A --> B["Model Watermarking
模型水印"] A --> C["Model Fingerprinting
模型指纹"] B --> B1["Parameter-based
参数型"] B --> B2["Representation-based
表示型"] B --> B3["Backdoor or Trigger-based
后门或触发器型"] B --> B4["Functional or Behavioral
功能或行为型"] B1 --> B11["Weight Encoding
权重编码"] B1 --> B12["Bit-string Embedding
比特信息嵌入"] B2 --> B21["Hidden Representation
隐藏表示"] B2 --> B22["Activation or Feature Space
激活或特征空间"] B3 --> B31["Trigger Set
触发器集合"] B3 --> B32["Secret Response
秘密响应"] B4 --> B41["Functional Signature
功能签名"] B4 --> B42["Behavioral Pattern
行为模式"] C --> C1["Behavioral
行为指纹"] C --> C2["Decision-boundary
决策边界指纹"] C --> C3["Representation
表示指纹"] C --> C4["Parameter or Structural
参数或结构指纹"] C --> C5["Gradient or Functional
梯度或功能指纹"] C --> C6["Natural or Intrinsic
自然或内生指纹"] C1 --> C11["Output Pattern
输出模式"] C1 --> C12["Prediction Preference
预测偏好"] C2 --> C21["Boundary Samples
边界样本"] C2 --> C22["Boundary Geometry
边界几何特征"] C3 --> C31["Hidden-state Features
隐状态特征"] C3 --> C32["Representation Similarity
表示相似性"] C4 --> C41["Weight Statistics
权重统计"] C4 --> C42["Structural Features
结构特征"] C5 --> C51["Gradient or Jacobian
梯度或雅可比"] C5 --> C52["Functional Network
功能网络"] C6 --> C61["Training Identity
训练身份"] C6 --> C62["Seed Signature
随机种子特征"] C6 --> C63["Knowledge Boundary
知识边界"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C nodeBranch; class B1,B2,B3,B4,C1,C2,C3,C4,C5,C6 nodeGroup;
事后所有权验证"] A --> B["Model Watermarking
模型水印"] A --> C["Model Fingerprinting
模型指纹"] B --> B1["Parameter-based
参数型"] B --> B2["Representation-based
表示型"] B --> B3["Backdoor or Trigger-based
后门或触发器型"] B --> B4["Functional or Behavioral
功能或行为型"] B1 --> B11["Weight Encoding
权重编码"] B1 --> B12["Bit-string Embedding
比特信息嵌入"] B2 --> B21["Hidden Representation
隐藏表示"] B2 --> B22["Activation or Feature Space
激活或特征空间"] B3 --> B31["Trigger Set
触发器集合"] B3 --> B32["Secret Response
秘密响应"] B4 --> B41["Functional Signature
功能签名"] B4 --> B42["Behavioral Pattern
行为模式"] C --> C1["Behavioral
行为指纹"] C --> C2["Decision-boundary
决策边界指纹"] C --> C3["Representation
表示指纹"] C --> C4["Parameter or Structural
参数或结构指纹"] C --> C5["Gradient or Functional
梯度或功能指纹"] C --> C6["Natural or Intrinsic
自然或内生指纹"] C1 --> C11["Output Pattern
输出模式"] C1 --> C12["Prediction Preference
预测偏好"] C2 --> C21["Boundary Samples
边界样本"] C2 --> C22["Boundary Geometry
边界几何特征"] C3 --> C31["Hidden-state Features
隐状态特征"] C3 --> C32["Representation Similarity
表示相似性"] C4 --> C41["Weight Statistics
权重统计"] C4 --> C42["Structural Features
结构特征"] C5 --> C51["Gradient or Jacobian
梯度或雅可比"] C5 --> C52["Functional Network
功能网络"] C6 --> C61["Training Identity
训练身份"] C6 --> C62["Seed Signature
随机种子特征"] C6 --> C63["Knowledge Boundary
知识边界"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C nodeBranch; class B1,B2,B3,B4,C1,C2,C3,C4,C5,C6 nodeGroup;
3. Active / Proactive Protection
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flowchart LR
A["3. Active or Proactive Protection
主动版权保护"] A --> B["Model Access Control
模型访问控制"] A --> C["Model Locking
模型锁定"] A --> D["Authorization Management
授权管理"] A --> E["Traitor Tracing
用户可追踪保护"] B --> B1["Authentication
身份认证"] B --> B2["Key-based Access Control
基于密钥的访问控制"] B --> B3["API Permission Control
接口权限控制"] B1 --> B11["User Authentication
用户认证"] B1 --> B12["Client Authentication
客户端认证"] B2 --> B21["Secret-key Activation
密钥激活"] B2 --> B22["Key-conditioned Inference
密钥条件推理"] B3 --> B31["Access Policy
访问策略"] B3 --> B32["Unauthorized Rejection
未授权拒绝"] C --> C1["Parameter Locking
参数锁定"] C --> C2["Passport-based Protection
Passport保护"] C --> C3["Unauthorized-use Degradation
未授权性能退化"] C1 --> C11["Locked Parameters
参数锁定"] C1 --> C12["Key-dependent Recovery
密钥恢复"] C2 --> C21["Passport Layer
Passport层"] C2 --> C22["Passport Verification
Passport验证"] C3 --> C31["Accuracy Degradation
精度退化"] C3 --> C32["Functional Degradation
功能退化"] D --> D1["License Management
许可证管理"] D --> D2["Key Distribution and Binding
密钥分发与绑定"] D --> D3["Revocation
授权撤销"] D1 --> D11["User or Organization License
用户或组织许可"] D1 --> D12["Time-limited License
限时许可"] D2 --> D21["User-model Binding
用户模型绑定"] D2 --> D22["Device or Hardware Binding
设备或硬件绑定"] D3 --> D31["Key Revocation
密钥撤销"] D3 --> D32["License Revocation
许可撤销"] E --> E1["User-specific Watermark
用户特异性水印"] E --> E2["User-specific Fingerprint
用户特异性指纹"] E --> E3["Leakage Tracing
泄露追踪"] E --> E4["Collusion-resistant Tracing
抗共谋追踪"] E1 --> E11["Per-user Watermark
用户级水印"] E2 --> E21["Per-user Fingerprint
用户级指纹"] E3 --> E31["Leak-source Attribution
泄露来源归因"] E3 --> E32["Responsible-user Identification
责任用户识别"] E4 --> E41["Multi-user Collusion
多用户共谋"] E4 --> E42["Model Mixing Resistance
模型混合抵抗"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E nodeBranch; class B1,B2,B3,C1,C2,C3,D1,D2,D3,E1,E2,E3,E4 nodeGroup;
主动版权保护"] A --> B["Model Access Control
模型访问控制"] A --> C["Model Locking
模型锁定"] A --> D["Authorization Management
授权管理"] A --> E["Traitor Tracing
用户可追踪保护"] B --> B1["Authentication
身份认证"] B --> B2["Key-based Access Control
基于密钥的访问控制"] B --> B3["API Permission Control
接口权限控制"] B1 --> B11["User Authentication
用户认证"] B1 --> B12["Client Authentication
客户端认证"] B2 --> B21["Secret-key Activation
密钥激活"] B2 --> B22["Key-conditioned Inference
密钥条件推理"] B3 --> B31["Access Policy
访问策略"] B3 --> B32["Unauthorized Rejection
未授权拒绝"] C --> C1["Parameter Locking
参数锁定"] C --> C2["Passport-based Protection
Passport保护"] C --> C3["Unauthorized-use Degradation
未授权性能退化"] C1 --> C11["Locked Parameters
参数锁定"] C1 --> C12["Key-dependent Recovery
密钥恢复"] C2 --> C21["Passport Layer
Passport层"] C2 --> C22["Passport Verification
Passport验证"] C3 --> C31["Accuracy Degradation
精度退化"] C3 --> C32["Functional Degradation
功能退化"] D --> D1["License Management
许可证管理"] D --> D2["Key Distribution and Binding
密钥分发与绑定"] D --> D3["Revocation
授权撤销"] D1 --> D11["User or Organization License
用户或组织许可"] D1 --> D12["Time-limited License
限时许可"] D2 --> D21["User-model Binding
用户模型绑定"] D2 --> D22["Device or Hardware Binding
设备或硬件绑定"] D3 --> D31["Key Revocation
密钥撤销"] D3 --> D32["License Revocation
许可撤销"] E --> E1["User-specific Watermark
用户特异性水印"] E --> E2["User-specific Fingerprint
用户特异性指纹"] E --> E3["Leakage Tracing
泄露追踪"] E --> E4["Collusion-resistant Tracing
抗共谋追踪"] E1 --> E11["Per-user Watermark
用户级水印"] E2 --> E21["Per-user Fingerprint
用户级指纹"] E3 --> E31["Leak-source Attribution
泄露来源归因"] E3 --> E32["Responsible-user Identification
责任用户识别"] E4 --> E41["Multi-user Collusion
多用户共谋"] E4 --> E42["Model Mixing Resistance
模型混合抵抗"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E nodeBranch; class B1,B2,B3,C1,C2,C3,D1,D2,D3,E1,E2,E3,E4 nodeGroup;
4. Verification Setting
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flowchart LR
A["4. Verification Setting
验证场景"] A --> B["White-box Verification
白盒验证"] A --> C["Gray-box Verification
灰盒验证"] A --> D["Black-box Verification
黑盒验证"] B --> B1["Model Weights
模型权重"] B --> B2["Hidden States
隐藏状态"] B --> B3["Activations
激活值"] B --> B4["Attention
注意力"] B --> B5["Gradients
梯度"] B --> B6["Architecture
模型结构"] C --> C1["Logits
输出Logits"] C --> C2["Confidence Scores
置信度"] C --> C3["Embeddings
嵌入表示"] C --> C4["Partial Internal Information
部分内部信息"] D --> D1["Input and Output
输入输出"] D --> D2["API-only Access
仅API访问"] D --> D3["Query-based Verification
查询式验证"] D --> D4["Limited-query Setting
受限查询"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D nodeBranch;
验证场景"] A --> B["White-box Verification
白盒验证"] A --> C["Gray-box Verification
灰盒验证"] A --> D["Black-box Verification
黑盒验证"] B --> B1["Model Weights
模型权重"] B --> B2["Hidden States
隐藏状态"] B --> B3["Activations
激活值"] B --> B4["Attention
注意力"] B --> B5["Gradients
梯度"] B --> B6["Architecture
模型结构"] C --> C1["Logits
输出Logits"] C --> C2["Confidence Scores
置信度"] C --> C3["Embeddings
嵌入表示"] C --> C4["Partial Internal Information
部分内部信息"] D --> D1["Input and Output
输入输出"] D --> D2["API-only Access
仅API访问"] D --> D3["Query-based Verification
查询式验证"] D --> D4["Limited-query Setting
受限查询"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D nodeBranch;
5. Threat Model & Attacks
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flowchart LR
A["5. Threat Model and Attacks
威胁模型与攻击"] A --> B["Model Modification
模型修改"] A --> C["Knowledge Transfer
知识迁移"] A --> D["Model Composition
模型组合"] A --> E["Protection Removal
保护机制移除"] A --> F["Forgery and Evasion
伪造与规避"] A --> G["Ownership Manipulation
所有权操纵"] A --> H["Adaptive Attack
自适应攻击"] B --> B1["Fine-tuning
微调"] B --> B2["PEFT or LoRA
参数高效微调"] B --> B3["Pruning
剪枝"] B --> B4["Quantization
量化"] B --> B5["Model Editing
模型编辑"] B --> B6["RLHF or DPO
对齐训练"] C --> C1["Knowledge Distillation
知识蒸馏"] C --> C2["Model Extraction
模型提取"] C --> C3["Model Stealing
模型窃取"] D --> D1["Model Merging
模型合并"] D --> D2["Weight Averaging
权重平均"] D --> D3["Multi-model Composition
多模型组合"] E --> E1["Watermark Removal
水印移除"] E --> E2["Fingerprint Removal
指纹移除"] E --> E3["Overwriting
覆盖攻击"] E --> E4["Erasure Fine-tuning
擦除式微调"] F --> F1["Fingerprint Spoofing
指纹伪造"] F --> F2["Model Impersonation
模型冒充"] F --> F3["Verification Evasion
验证规避"] G --> G1["False Ownership Claim
虚假所有权声明"] G --> G2["Fake Fingerprint
虚假指纹"] G --> G3["Collusion Attack
共谋攻击"] H --> H1["Known Protection Algorithm
已知保护算法"] H --> H2["Known Verification Rule
已知验证规则"] H --> H3["Adaptive Querying
自适应查询"] H --> H4["Verifier-aware Attack
面向验证器攻击"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E,F,G,H nodeBranch;
威胁模型与攻击"] A --> B["Model Modification
模型修改"] A --> C["Knowledge Transfer
知识迁移"] A --> D["Model Composition
模型组合"] A --> E["Protection Removal
保护机制移除"] A --> F["Forgery and Evasion
伪造与规避"] A --> G["Ownership Manipulation
所有权操纵"] A --> H["Adaptive Attack
自适应攻击"] B --> B1["Fine-tuning
微调"] B --> B2["PEFT or LoRA
参数高效微调"] B --> B3["Pruning
剪枝"] B --> B4["Quantization
量化"] B --> B5["Model Editing
模型编辑"] B --> B6["RLHF or DPO
对齐训练"] C --> C1["Knowledge Distillation
知识蒸馏"] C --> C2["Model Extraction
模型提取"] C --> C3["Model Stealing
模型窃取"] D --> D1["Model Merging
模型合并"] D --> D2["Weight Averaging
权重平均"] D --> D3["Multi-model Composition
多模型组合"] E --> E1["Watermark Removal
水印移除"] E --> E2["Fingerprint Removal
指纹移除"] E --> E3["Overwriting
覆盖攻击"] E --> E4["Erasure Fine-tuning
擦除式微调"] F --> F1["Fingerprint Spoofing
指纹伪造"] F --> F2["Model Impersonation
模型冒充"] F --> F3["Verification Evasion
验证规避"] G --> G1["False Ownership Claim
虚假所有权声明"] G --> G2["Fake Fingerprint
虚假指纹"] G --> G3["Collusion Attack
共谋攻击"] H --> H1["Known Protection Algorithm
已知保护算法"] H --> H2["Known Verification Rule
已知验证规则"] H --> H3["Adaptive Querying
自适应查询"] H --> H4["Verifier-aware Attack
面向验证器攻击"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E,F,G,H nodeBranch;
6. Evaluation Metrics
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flowchart LR
A["6. Evaluation Metrics
评价指标"] A --> B["Effectiveness
有效性"] A --> C["Fidelity or Harmlessness
保真性或无损性"] A --> D["Robustness
鲁棒性"] A --> E["Uniqueness or Discriminability
唯一性或可区分性"] A --> F["Reliability
可靠性"] A --> G["Security or Stealthiness
安全性或隐蔽性"] A --> H["Efficiency
效率"] A --> I["Capacity and Scalability
容量与可扩展性"] B --> B1["Detection Rate
检测率"] B --> B2["Verification Success Rate
验证成功率"] B --> B3["True Positive Rate
真阳性率"] C --> C1["Accuracy Preservation
精度保持"] C --> C2["Utility Preservation
效用保持"] C --> C3["Performance Degradation
性能下降"] D --> D1["Benign Robustness
良性变换鲁棒性"] D --> D2["Adversarial Robustness
对抗鲁棒性"] D1 --> D11["Fine-tuning"] D1 --> D12["Quantization"] D1 --> D13["Pruning"] D1 --> D14["Distillation"] D1 --> D15["Model Merging"] D2 --> D21["Removal Attack
移除攻击"] D2 --> D22["Spoofing
伪造攻击"] D2 --> D23["Adaptive Attack
自适应攻击"] D2 --> D24["Collusion
共谋攻击"] E --> E1["Inter-model Separation
模型间区分"] E --> E2["Intra-lineage Similarity
同血缘相似性"] E --> E3["Independent-model Rejection
独立模型排除"] F --> F1["False Positive Rate
假阳性率"] F --> F2["False Negative Rate
假阴性率"] F --> F3["Confidence
置信度"] F --> F4["Calibration
校准"] F --> F5["Statistical Significance
统计显著性"] G --> G1["Detectability
可检测性"] G --> G2["Secret Exposure Risk
秘密泄露风险"] G --> G3["Unforgeability
不可伪造性"] H --> H1["Embedding Cost
嵌入成本"] H --> H2["Verification Cost
验证成本"] H --> H3["Query Cost
查询成本"] H --> H4["Runtime Overhead
运行开销"] I --> I1["Embedded Information
嵌入信息量"] I --> I2["Number of Identities
身份数量"] I --> I3["Multi-user Scalability
多用户扩展"] I --> I4["Large-model Scalability
大模型扩展"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E,F,G,H,I nodeBranch; class D1,D2 nodeGroup;
评价指标"] A --> B["Effectiveness
有效性"] A --> C["Fidelity or Harmlessness
保真性或无损性"] A --> D["Robustness
鲁棒性"] A --> E["Uniqueness or Discriminability
唯一性或可区分性"] A --> F["Reliability
可靠性"] A --> G["Security or Stealthiness
安全性或隐蔽性"] A --> H["Efficiency
效率"] A --> I["Capacity and Scalability
容量与可扩展性"] B --> B1["Detection Rate
检测率"] B --> B2["Verification Success Rate
验证成功率"] B --> B3["True Positive Rate
真阳性率"] C --> C1["Accuracy Preservation
精度保持"] C --> C2["Utility Preservation
效用保持"] C --> C3["Performance Degradation
性能下降"] D --> D1["Benign Robustness
良性变换鲁棒性"] D --> D2["Adversarial Robustness
对抗鲁棒性"] D1 --> D11["Fine-tuning"] D1 --> D12["Quantization"] D1 --> D13["Pruning"] D1 --> D14["Distillation"] D1 --> D15["Model Merging"] D2 --> D21["Removal Attack
移除攻击"] D2 --> D22["Spoofing
伪造攻击"] D2 --> D23["Adaptive Attack
自适应攻击"] D2 --> D24["Collusion
共谋攻击"] E --> E1["Inter-model Separation
模型间区分"] E --> E2["Intra-lineage Similarity
同血缘相似性"] E --> E3["Independent-model Rejection
独立模型排除"] F --> F1["False Positive Rate
假阳性率"] F --> F2["False Negative Rate
假阴性率"] F --> F3["Confidence
置信度"] F --> F4["Calibration
校准"] F --> F5["Statistical Significance
统计显著性"] G --> G1["Detectability
可检测性"] G --> G2["Secret Exposure Risk
秘密泄露风险"] G --> G3["Unforgeability
不可伪造性"] H --> H1["Embedding Cost
嵌入成本"] H --> H2["Verification Cost
验证成本"] H --> H3["Query Cost
查询成本"] H --> H4["Runtime Overhead
运行开销"] I --> I1["Embedded Information
嵌入信息量"] I --> I2["Number of Identities
身份数量"] I --> I3["Multi-user Scalability
多用户扩展"] I --> I4["Large-model Scalability
大模型扩展"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E,F,G,H,I nodeBranch; class D1,D2 nodeGroup;
7. Research Frontier
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flowchart LR
A["7. Research Frontier
研究前沿"] A --> B["Robust Ownership Verification
鲁棒所有权验证"] A --> C["Fingerprint Attack and Defense
指纹攻防"] A --> D["False-claim-resistant Verification
抗虚假声明验证"] A --> E["Model Extraction Attribution
模型提取归因"] A --> F["Model Provenance
模型来源追踪"] A --> G["Model Lineage or Genealogy
模型谱系"] A --> H["Multi-source Attribution
多来源归因"] A --> I["Certified or Provable Verification
可证明验证"] B --> B1["Fine-tuning Robustness
微调鲁棒性"] B --> B2["Distillation Robustness
蒸馏鲁棒性"] B --> B3["Merge Robustness
合并鲁棒性"] C --> C1["Fingerprint Removal
指纹移除"] C --> C2["Fingerprint Spoofing
指纹伪造"] C --> C3["Adaptive Attack
自适应攻击"] C --> C4["Anti-removal Protection
抗移除保护"] D --> D1["Ownership Unforgeability
所有权不可伪造"] D --> D2["Claim Exclusivity
所有权声明排他性"] D --> D3["Independent-model Rejection
独立模型拒绝"] E --> E1["Functional Similarity
功能相似性"] E --> E2["Architecture-independent Attribution
架构无关归因"] E --> E3["Knowledge-transfer Detection
知识迁移检测"] F --> F1["Source-model Identification
源模型识别"] F --> F2["Derivative-model Detection
派生模型检测"] F --> F3["Provenance Inference
来源推断"] G --> G1["Parent-child Relation
父子关系"] G --> G2["Model Evolution
模型演化"] G --> G3["Family-tree Reconstruction
谱系树恢复"] H --> H1["Merge Detection
合并检测"] H --> H2["Source Decomposition
来源分解"] H --> H3["Contribution Estimation
贡献估计"] H --> H4["Multi-parent Attribution
多父模型归因"] I --> I1["Statistical Guarantee
统计保证"] I --> I2["False-positive Control
假阳性控制"] I --> I3["Certified Robustness
可认证鲁棒性"] I --> I4["Error Bounds
误差界"] I --> I5["Provable Provenance
可证明来源追踪"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E,F,G,H,I nodeBranch;
研究前沿"] A --> B["Robust Ownership Verification
鲁棒所有权验证"] A --> C["Fingerprint Attack and Defense
指纹攻防"] A --> D["False-claim-resistant Verification
抗虚假声明验证"] A --> E["Model Extraction Attribution
模型提取归因"] A --> F["Model Provenance
模型来源追踪"] A --> G["Model Lineage or Genealogy
模型谱系"] A --> H["Multi-source Attribution
多来源归因"] A --> I["Certified or Provable Verification
可证明验证"] B --> B1["Fine-tuning Robustness
微调鲁棒性"] B --> B2["Distillation Robustness
蒸馏鲁棒性"] B --> B3["Merge Robustness
合并鲁棒性"] C --> C1["Fingerprint Removal
指纹移除"] C --> C2["Fingerprint Spoofing
指纹伪造"] C --> C3["Adaptive Attack
自适应攻击"] C --> C4["Anti-removal Protection
抗移除保护"] D --> D1["Ownership Unforgeability
所有权不可伪造"] D --> D2["Claim Exclusivity
所有权声明排他性"] D --> D3["Independent-model Rejection
独立模型拒绝"] E --> E1["Functional Similarity
功能相似性"] E --> E2["Architecture-independent Attribution
架构无关归因"] E --> E3["Knowledge-transfer Detection
知识迁移检测"] F --> F1["Source-model Identification
源模型识别"] F --> F2["Derivative-model Detection
派生模型检测"] F --> F3["Provenance Inference
来源推断"] G --> G1["Parent-child Relation
父子关系"] G --> G2["Model Evolution
模型演化"] G --> G3["Family-tree Reconstruction
谱系树恢复"] H --> H1["Merge Detection
合并检测"] H --> H2["Source Decomposition
来源分解"] H --> H3["Contribution Estimation
贡献估计"] H --> H4["Multi-parent Attribution
多父模型归因"] I --> I1["Statistical Guarantee
统计保证"] I --> I2["False-positive Control
假阳性控制"] I --> I3["Certified Robustness
可认证鲁棒性"] I --> I4["Error Bounds
误差界"] I --> I5["Provable Provenance
可证明来源追踪"] classDef default fill:#F8FAFC,color:#334155,stroke:#CBD5E1,stroke-width:1px; classDef nodeRoot fill:#315FA8,color:#FFFFFF,stroke:#234A87,stroke-width:2px,font-weight:bold; classDef nodeBranch fill:#EAF2FB,color:#1F4168,stroke:#8FB3DD,stroke-width:1.5px,font-weight:bold; classDef nodeGroup fill:#ECF8F3,color:#205A49,stroke:#82CDB1,stroke-width:1px; class A nodeRoot; class B,C,D,E,F,G,H,I nodeBranch;