Domain hris.deployment.mom
Iran
Noyan Abr Arvan Co. ( Private Joint Stock)
Software information

ArvanCloud

tcp/8443

nginx nginx 1.26.2

tcp/443

  • MacOS file listing through .DS_Store file
    First seen 2024-07-29 15:57
    Last seen 2024-10-10 22:34
    Open for 73 days
  • MacOS file listing through .DS_Store file
    First seen 2024-09-28 01:37
    Last seen 2024-10-10 17:36
    Open for 12 days
  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-11-20 04:38

    HTTP/1.1 200 OK
    Date: Wed, 20 Nov 2024 04:39:11 GMT
    Content-Type: text/html
    Transfer-Encoding: chunked
    Connection: close
    Vary: Accept-Encoding
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    CF-RAY: 8e55c1373daebe58-CPH
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    Page title: University Research Initiative: Analyzing Encrypted Data Patterns
    
    
        <!DOCTYPE html>
        <html lang="en">
        <head>
          <meta charset="UTF-8">
          <meta name="viewport" content="width=device-width, initial-scale=1.0">
          <title>University Research Initiative: Analyzing Encrypted Data Patterns</title>
          <style>
            body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; margin: 40px; line-height: 1.6; color: #333; }
            header, footer { text-align: center; background-color: #f4f4f4; padding: 20px; }
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        <body>
          <header>
            <h1>University Research Initiative</h1>
            <p>Exploring NLP-Inspired Analysis on Encrypted Data Patterns</p>
          </header>
          <main>
            <div class="section">
              <h2>About the Project</h2>
              <p>Our team of engineering and data science researchers is engaged in an exploratory project focused on applying natural language processing (NLP) techniques to the analysis of encrypted data. While traditional NLP is used to understand human language, we are investigating how similar algorithms could be adapted to observe and analyze patterns in encrypted data streams. The goal is not to decrypt data but to study the behavior, 'tone,' and characteristics of data traffic.</p>
            </div>
            
            <div class="section">
              <h2>Research Objectives</h2>
              <ul>
                <li>Identify and analyze patterns within encrypted data flows using statistical NLP models.</li>
                <li>Develop tools to simulate data traffic and apply NLP-based algorithms to discern structural traits.</li>
                <li>Explore potential applications in anomaly detection and network health monitoring.</li>
              </ul>
              <p>This project aligns with ongoing research in data science, cryptography, and cybersecurity, and it serves as a foundation for innovative approaches in traffic analysis.</p>
            </div>
            
            <div class="section">
              <h2>Methodology</h2>
              <p>The project methodology includes:</p>
              <ol>
                <li>Data Collection: Using public and synthetic data to create large datasets representative of encrypted traffic.</li>
                <li>Algorithm Development: Adapting NLP algorithms to process and model these datasets, treating them as unique, non-linguistic languages.</li>
                <li>Pattern Analysis: Observing and interpreting structural patterns to infer the 'tone' or nature of data flows without compromising encryption.</li>
              </ol>
              <p>This allows us to observe data characteristics without violating privacy or encryption principles.</p>
            </div>
            
            <div class="section">
              <h2>Applications and Future Work</h2>
              <p>Potential applications of this research include:</p>
              <ul>
                <li>Network anomaly detection for improved security and network management.</li>
                <li>Academic insights into how encrypted data behaves under different conditions.</li>
                <li>Contributions to fields intersecting machine learning and data cryptography.</li>
              </ul>
              <p>Future work may involve collaboration with cryptography experts and exploring more advanced NLP models to refine our findings.</p>
            </div>
        
            
            <footer>
              <div class="contact-info">
                <p>Contact us: research@oracletunnel.space</p>
              </div>
              <div class="footer-text">
                <p>© 2024 Oracle Tunnels | Engineering and Data Science Research</p>
              </div>
            </footer>
          </main>
        </body>
        </html>
      
    Found 2024-11-20 by HttpPlugin
    Create report
  • Open service 194.48.198.180:443 · hris.deployment.mom

    2024-11-20 03:44

    HTTP/1.1 200 OK
    Server: nginx/1.26.2
    Date: Wed, 20 Nov 2024 03:45:02 GMT
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    Page title: University Research Initiative: Analyzing Encrypted Data Patterns
    
    
        <!DOCTYPE html>
        <html lang="en">
        <head>
          <meta charset="UTF-8">
          <meta name="viewport" content="width=device-width, initial-scale=1.0">
          <title>University Research Initiative: Analyzing Encrypted Data Patterns</title>
          <style>
            body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; margin: 40px; line-height: 1.6; color: #333; }
            header, footer { text-align: center; background-color: #f4f4f4; padding: 20px; }
            main { max-width: 900px; margin: auto; padding: 20px; background-color: #fff; border-radius: 8px; box-shadow: 0 0 10px rgba(0, 0, 0, 0.1); }
            h1, h2 { color: #2c3e50; }
            p { margin: 15px 0; }
            .section { margin-bottom: 40px; }
            .contact-info, .footer-text { font-size: 0.9em; color: #777; }
          </style>
        </head>
        <body>
          <header>
            <h1>University Research Initiative</h1>
            <p>Exploring NLP-Inspired Analysis on Encrypted Data Patterns</p>
          </header>
          <main>
            <div class="section">
              <h2>About the Project</h2>
              <p>Our team of engineering and data science researchers is engaged in an exploratory project focused on applying natural language processing (NLP) techniques to the analysis of encrypted data. While traditional NLP is used to understand human language, we are investigating how similar algorithms could be adapted to observe and analyze patterns in encrypted data streams. The goal is not to decrypt data but to study the behavior, 'tone,' and characteristics of data traffic.</p>
            </div>
            
            <div class="section">
              <h2>Research Objectives</h2>
              <ul>
                <li>Identify and analyze patterns within encrypted data flows using statistical NLP models.</li>
                <li>Develop tools to simulate data traffic and apply NLP-based algorithms to discern structural traits.</li>
                <li>Explore potential applications in anomaly detection and network health monitoring.</li>
              </ul>
              <p>This project aligns with ongoing research in data science, cryptography, and cybersecurity, and it serves as a foundation for innovative approaches in traffic analysis.</p>
            </div>
            
            <div class="section">
              <h2>Methodology</h2>
              <p>The project methodology includes:</p>
              <ol>
                <li>Data Collection: Using public and synthetic data to create large datasets representative of encrypted traffic.</li>
                <li>Algorithm Development: Adapting NLP algorithms to process and model these datasets, treating them as unique, non-linguistic languages.</li>
                <li>Pattern Analysis: Observing and interpreting structural patterns to infer the 'tone' or nature of data flows without compromising encryption.</li>
              </ol>
              <p>This allows us to observe data characteristics without violating privacy or encryption principles.</p>
            </div>
            
            <div class="section">
              <h2>Applications and Future Work</h2>
              <p>Potential applications of this research include:</p>
              <ul>
                <li>Network anomaly detection for improved security and network management.</li>
                <li>Academic insights into how encrypted data behaves under different conditions.</li>
                <li>Contributions to fields intersecting machine learning and data cryptography.</li>
              </ul>
              <p>Future work may involve collaboration with cryptography experts and exploring more advanced NLP models to refine our findings.</p>
            </div>
        
            
            <footer>
              <div class="contact-info">
                <p>Contact us: research@oracletunnel.space</p>
              </div>
              <div class="footer-text">
                <p>© 2024 Oracle Tunnels | Engineering and Data Science Research</p>
              </div>
            </footer>
          </main>
        </body>
        </html>
      
    Found 2024-11-20 by HttpPlugin
    Create report
  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-11-18 05:13

    HTTP/1.1 502 Bad Gateway
    Date: Mon, 18 Nov 2024 05:13:50 GMT
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    X-Request-ID: 33daf56b8111bc0ccb4d5c3fe38502d6
    X-SID: 6112
    
    
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    Found 2024-11-18 by HttpPlugin
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  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-11-16 07:52

    HTTP/1.1 200 OK
    Date: Sat, 16 Nov 2024 07:52:16 GMT
    Content-Type: text/plain;charset=UTF-8
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    X-SID: 6230
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    Found 2024-11-16 by HttpPlugin
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  • Open service 194.48.198.180:443 · hris.deployment.mom

    2024-11-16 04:05

    HTTP/1.1 200 OK
    Server: nginx/1.26.2
    Date: Sat, 16 Nov 2024 04:05:30 GMT
    Content-Type: text/plain;charset=UTF-8
    Content-Length: 0
    Connection: close
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    Found 2024-11-16 by HttpPlugin
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  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-11-02 12:27

    
                                
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  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-11-01 10:36

    
                                
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  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-10-30 11:54

    
                                
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  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-10-28 12:17

    
                                
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  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-10-20 15:33

    
                                
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  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-10-18 20:31

    
                                
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  • Open service 185.143.233.120:8443 · hris.deployment.mom

    2024-10-16 23:48

    
                                
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*.deployment.momdeployment.mom
CN:
deployment.mom
Key:
ECDSA-256
Issuer:
E6
Not before:
2024-11-08 23:17
Not after:
2025-02-06 23:17
edge-1.oracletunnel.space
CN:
edge-1.oracletunnel.space
Key:
ECDSA-256
Issuer:
E5
Not before:
2024-11-18 20:17
Not after:
2025-02-16 20:17
api-zone-2.chill-hub.net
CN:
api-zone-2.chill-hub.net
Key:
ECDSA-256
Issuer:
E6
Not before:
2024-11-13 23:37
Not after:
2025-02-11 23:37
*.deployment.momdeployment.mom
CN:
deployment.mom
Key:
ECDSA-256
Issuer:
E6
Not before:
2024-08-17 17:14
Not after:
2024-11-15 17:14
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