Update README.md

README.md

@@ -35,7 +35,7 @@ SecBench Technical Paper: *[link](https://arxiv.org/abs/2412.20787)*.
 
 
 
-## SecBench Design
+## 1, SecBench Design
 
 
 The following figure shows the overview of the SecBench design: it is a comprehensive benchmarking dataset aiming to benchmark LLM's capability in cybersecurity from *Multi-Level*, *Multi-Language*, *Multi-Form*, *Multi-Domain*.
@@ -55,7 +55,7 @@ The following figure shows the overview of the SecBench design: it is a comprehe
 
 - **Multi-Domain** : The questions in SecBench consist of 9 different domains, including **D1. Security Management**, **D2. Data Security**, **D3. Network and Infrastructure Security**, **D4. Security Standards and Regulations**, **D5. Application Security**, **D6. Identity and Access Control**, **D7. Fundamental Software and Hardware and Technology**, **D8. Endpoint and Host Security**, **D9. Cloud Security**. Particularly, the above domains were devised from several rounds of brainstorming and revision, which were expected to cover most (if not all) related sub-domains in cybersecurity. Note that we do not expect these domains to be \emph{orthogonal}, and it is possible that one question can be reasonably labeled into different domains. In our dataset, one question is assigned only one most-related domain label from D1 to D9.
 
-## Data Example
+## 2. Data Example
 
 
 ### MCQ Example
@@ -76,7 +76,7 @@ Following is one SAQ example, labeled in the domain of *Data Security* and the l
 
 
 
-## Benchmarking
+## 3. Benchmarking
 
 Based on SecBench, we conducted extensive benchmarking on 16 SOTA LLMs, including the GPT series and competitive open-source ones.
 
@@ -91,7 +91,7 @@ Based on SecBench, we conducted extensive benchmarking on 16 SOTA LLMs, includin
 
 
 
-## Released Data
+## 4. Released Data
 
 We release a total of 3,000 questions from SecBench (under the [data] folder), including: