Denial Of Service Final Year Projects with Source Code

Byadmin Final Year Projects

Denial Of Service Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Denial Of Service projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

Denial Of Service Final Year Projects

  1. A Network Intrusion Detection System for Building Automation and Control Systems
    This project focuses on improving security for building automation systems, like smart lighting and HVAC controls. The researchers designed a network intrusion detection system that can detect attacks across different building system protocols, not just one. They built and tested a working version for KNX, a common building automation protocol, using a real installation to show it works. The system aims to make smart buildings safer from cyber threats.
  2. An Attention-Based Convolutional Neural Network for Intrusion Detection Model
    This project focuses on improving network security by detecting intrusions quickly and accurately. It uses a type of artificial intelligence called convolutional neural networks with attention mechanisms. The method organizes network data into images in a smart way to make the detection process faster. Experiments show that this approach can identify threats efficiently while keeping high accuracy.
  3. MAC Protocol Based IoT Network Intrusion Detection Using Improved Efficient Shuffle Bidirectional COOT Channel Attention Network
    This project focuses on protecting IoT networks from cyberattacks. It uses a smart system to detect intrusions while keeping data secure and reducing energy use and delays. The approach balances and processes IoT data, selects important features, and then classifies attacks using an advanced AI model. Overall, it improves accuracy and performance compared to existing methods.
  4. Security-Aware Provenance for Transparency in IoT Data Propagation
    This project studies how to make data in an Internet of Things system more transparent and trustworthy. It adds extra security information to track every step of data movement. The system is tested with different cyber-attack situations to see how well it detects problems. This helps users understand risks and make better decisions without slowing down the system.
  5. Blockchain Based Dynamic Spectrum Access of Non Real Time Data in Cyber Physical Social Systems
    This project focuses on sharing wireless spectrum efficiently in systems where devices, humans, and computers interact. It uses blockchain to manage access to unused spectrum channels, making the process fair and secure. Users can earn access rights through mining and can trade them if not needed. The system also supports faster data processing at the network edge for non-urgent data.
  6. An Efficient Authenticated Elliptic Curve Cryptography Scheme for Multicore Wireless Sensor Networks
    This project focuses on improving the lifespan and security of Wireless Sensor Networks. It groups sensors together and uses multicore sensors to reduce power consumption. The system applies advanced cryptography to keep data secure and verify devices. Tests show it is energy-efficient, fast, scalable, and resistant to attacks.
  7. LCSS Based Sybil Attack Detection and Avoidance in Clustered Vehicular Networks
    This project focuses on making road networks safer for connected vehicles. It detects malicious vehicles, called Sybil nodes, that send fake messages and disrupt traffic systems. The method uses a cluster-based network and compares signal patterns to spot attackers. It improves detection speed, accuracy, and reduces false alarms compared to older approaches.
  8. Simulative Survey of Flooding Attacks in Intermittently Connected Vehicular Delay Tolerant Networks
    This project studies communication between vehicles and roadside units in networks where connections are often unreliable. It focuses on security problems, especially flood attacks, where malicious nodes overwhelm the network and waste resources. The research proposes a clear classification of these attacks and evaluates different methods to detect and reduce them efficiently. It also identifies open areas for further research on improving security in these networks.
  9. Toward the Design of an Efficient and Secure System Based on the Software-Defined Network Paradigm for Vehicular Networks
    This project focuses on making vehicle networks smarter and safer. It uses a special network system called SDN to manage how vehicles connect and communicate with each other. The system improves security, protecting data from hackers, and uses machine learning to predict traffic changes and optimize network performance. Tests show it reduces delays and increases the reliability of messages between vehicles.
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