Update README.md

README.md

@@ -10,16 +10,23 @@ size_categories:
 - 100K<n<1M
 ---
 # Advanced SIEM Dataset
+
 Dataset Description
-The advanced_siem_dataset is a synthetic dataset of 100,000 security event records designed for training machine learning (ML) and artificial intelligence (AI) models in cybersecurity. It simulates logs from Security Information and Event Management (SIEM) systems, capturing diverse event types such as firewall activities, intrusion detection system (IDS) alerts, authentication attempts, endpoint activities, network traffic, cloud operations, IoT device events, and AI system interactions. The dataset includes advanced metadata, MITRE ATT&CK techniques, threat actor associations, and unconventional indicators of compromise (IOCs), making it suitable for tasks like anomaly detection, threat classification, predictive analytics, and user and entity behavior analytics (UEBA).
-]
+
+The advanced_siem_dataset is a synthetic dataset of 100,000 security event records designed for training machine learning (ML) and artificial intelligence (AI) models in cybersecurity. 
+
+It simulates logs from Security Information and Event Management (SIEM) systems, capturing diverse event types such as firewall activities, intrusion detection system (IDS) alerts, authentication attempts, endpoint activities, network traffic, cloud operations, IoT device events, and AI system interactions. 
+
+The dataset includes advanced metadata, MITRE ATT&CK techniques, threat actor associations, and unconventional indicators of compromise (IOCs), making it suitable for tasks like anomaly detection, threat classification, predictive analytics, and user and entity behavior analytics (UEBA).
+```java
 Paper: N/A
 Point of Contact: sunny thakur ,sunny48445@gmail.com
 Size of Dataset: 100,000 records
 File Format: JSON Lines (.jsonl)
 License: MIT License
+```
+# Dataset Structure
 
-Dataset Structure
 The dataset is stored in a single train split in JSON Lines format, with each record representing a security event. Below is the schema:
 
 ```
@@ -114,8 +121,10 @@ Predictive Analytics: Forecast high-risk periods using time-series analysis of r
 Threat Hunting: Leverage MITRE ATT&CK techniques and IOCs in additional_info for threat intelligence.
 Red Teaming: Simulate adversarial scenarios (e.g., APTs, DNS tunneling) for testing SIEM systems.
 ```
-Loading the Dataset
+# Loading the Dataset
+
 Install the datasets library:
+
 ```python
 pip install datasets