-
Notifications
You must be signed in to change notification settings - Fork 0
/
index.html
221 lines (172 loc) · 9.34 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>IntelAI</title>
<link rel="stylesheet" href="style.css">
<script defer src="script.js"></script>
</head>
<body>
<button class="nav-toggle" onclick="toggleSidebar()">☰</button>
<aside class="sidebar">
<h2> </h2> <br>
<ul>
<li class="active"><a href="#home">Home</a></li>
<li class="active"><a href="#model">Model</a></li>
<li class="active"><a href="#architecture">Architecture</a></li>
<li class="active"><a href="#performance">Performance</a></li>
<li class="active"><a href="#team">Team</a></li>
<li class="active"><a href="#documentation">Documentation</a></li>
<li class="active"><a href="#documentation">Feedback</a></li>
</ul>
</aside>
<main>
<!-- Hero Section -->
<section id="home" class="hero">
<h1 class="main-title">ML-Enhanced Suricata IDS/IPS for Network Security</h1>
<p>Next-Generation Firewall Security with AI-Powered Threat Detection.</p>
<img src="src/images/bg_img2.jpeg" alt="Model Diagram" class="hero-image">
<div class="cta-buttons">
<a href="#features" class="btn">Features</a>
<a href="#demo" class="btn">Live Demo</a>
</div>
</section>
<!-- Features Section -->
<section id="features">
<h2>Introduction</h2>
<!-- First container -->
<div class="feature-container">
<ul>
<li><strong>Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS)</strong> are
essential for identifying and preventing unauthorized access to network systems.</li>
<li><strong>Suricata</strong> is a high-performance, open-source IDS/IPS engine that detects network
anomalies using predefined rules.</li>
<li><strong> </strong> Traditional rule-based systems like Suricata are prone to high false
positives and may struggle with evolving cyber threats and zero-day attacks.
</li>
<li><strong>Long Short-Term Memory (LSTM)</strong> networks, a type of Recurrent Neural Network
(RNN), excel at recognizing patterns in sequential data, making them suitable for detecting
complex, time-dependent network threats.</li>
<li><strong> </strong> This project proposes integrating LSTM with Suricata to enhance the accuracy
of intrusion detection, reduce false positives, and detect sophisticated or evolving attacks in
real-time.
</li>
<li><strong> </strong> The goal is to leverage LSTM’s learning capabilities to complement Suricata’s
rule-based approach, resulting in a hybrid system that improves both detection efficiency and
scalability.</li>
</ul>
</div>
<!-- Second container -->
<!-- <div class="feature-container">
<ul>
<li><strong>ML-Based Anomaly Detection:</strong> Real-time improved threat detection.</li>
<li><strong>Adaptive Threat Response:</strong> Dynamic rule adjustment based on ML predictions.</li>
<li><strong>Predictive Network Analytics:</strong> Preemptively block suspicious activity.</li>
<li><strong>Automated Responses:</strong> Autonomous log analysis and alert flagging.</li>
<li><strong>Visualizations:</strong> Graphs showing improved detection rates.</li>
</ul>
</div> -->
<h2>Key Features</h2>
<!-- First container -->
<div class="feature-container">
<ul>
<li><strong>ML-Based Anomaly Detection:</strong> Real-time improved threat detection.</li>
<li><strong>Adaptive Threat Response:</strong> Dynamic rule adjustment based on ML predictions.</li>
<li><strong>Predictive Network Analytics:</strong> Preemptively block suspicious activity.</li>
<li><strong>Automated Responses:</strong> Autonomous log analysis and alert flagging.</li>
<li><strong>Visualizations:</strong> Graphs showing improved detection rates.</li>
</ul>
</div>
<!-- Second container -->
<!-- <div class="feature-container">
<ul>
<li><strong>ML-Based Anomaly Detection:</strong> Real-time improved threat detection.</li>
<li><strong>Adaptive Threat Response:</strong> Dynamic rule adjustment based on ML predictions.</li>
<li><strong>Predictive Network Analytics:</strong> Preemptively block suspicious activity.</li>
<li><strong>Automated Responses:</strong> Autonomous log analysis and alert flagging.</li>
<li><strong>Visualizations:</strong> Graphs showing improved detection rates.</li>
</ul>
</div> -->
</section>
<br> <br> <br> <br>
<!-- Demo Section with Prediction Form -->
<section id="demo">
<h2>Live Demo</h2>
<p>See our ML-enhanced Suricata detecting suspicious activities in real-time.</p> <br>
<video src="demo.mp4" controls class="demo-video"></video> <br><br><br>
<form class="network-data-form">
<!-- Label for entering network data -->
<label for="network-input">Enter Network Data:</label> <br>
<textarea id="network-input" name="networkData" placeholder="Enter your network data here"></textarea>
<!-- OR section -->
<p style="text-align: center; font-weight: bold;">OR</p>
<!-- File upload section -->
<label for="file-upload">Upload a file:</label>
<input type="file" id="file-upload" name="fileUpload" accept=".txt, .csv" class="file-upload">
<!-- Submit button -->
<button type="submit">Submit</button>
</form>
<div id="prediction-result" class="prediction-box">
<!-- Prediction result will be displayed here -->
</div>
</section>
<br> <br> <br> <br>
<!-- Performance Section -->
<section id="performance">
<h2>Performance Comparison</h2> <br><br>
<img src="src/images/performance_graph.png" alt="Performance Metrics" class="performance-image">
<!-- <p>Here we compare key metrics like accuracy, precision, and recall, showing how the ML model enhances the
IDS/IPS.</p> -->
</section>
<br> <br> <br> <br>
<!-- Team Section -->
<section id="team">
<h2>Meet the Team</h2> <br> <br>
<div class="team-members">
<div class="team-member">
<img src="src/team_image/ibrahim.jpeg" alt="Team Member 1" class="team-image">
<h3>Md. Ibrahim</h3>
<p>Team Leader</p>
</div>
<div class="team-member">
<img src="src/team_image/lpd.jpeg" alt="Team Member 2" class="team-image">
<h3>Priyadarshan</h3>
<p>Cyber Security Specialist</p>
</div>
<div class="team-member">
<img src="src/team_image/sarvesh.jpeg" alt="Team Member 1" class="team-image">
<h3>Sarvesh</h3>
<p>Model Trainer</p>
</div>
<div class="team-member">
<img src="src/team_image/shubham.jpeg" alt="Team Member 2" class="team-image">
<h3>Shubham Pandey</h3>
<p>Web Developer & Git</p>
</div>
</div>
</section>
<br> <br> <br> <br>
<!-- Documentation Section -->
<section id="documentation">
<h2>Documentation & Resources</h2>
<p>Check out the <a https://github.com/heizshubham/IntelAI-Hackathon" target="_blank">GitHub Repository</a> for the full
project documentation and code samples.</p>
</section>
<br> <br> <br><br> <br> <br><br> <br> <br>
<!-- Contact Section -->
<section id="contact">
<h2>Contact Us / Feedback</h2> <br>
<form action="submit_contact.php" method="post" class="contact-form">
<label for="name">Name:</label>
<input type="text" id="name" name="name" required>
<label for="email">Email:</label>
<input type="email" id="email" name="email" required>
<label for="message">Message / Feedback:</label>
<textarea id="message" name="message" required></textarea>
<button type="submit">Send</button>
</form>
</section> <br><br> <br> <br> <br>
</main>
</body>
</html>