IoT Security Research Topics

Internet of things (IoT) is a network which connects devices physically over internet. Basically this is a connection between human, machine and the data which needed to be shared between them. You can now go through this research if you want to learn more about this technology.

  1. Define IOT

IoT is a network in which it has sensors, devices or other items that are connected physically with same technology to collect, transmit and exchange data over internet. The devices involved in it are connected to each other and also to the central server when working in real-time environment which is used in several fields such as manufacturing, home automation, agriculture and healthcare for monitoring and control. IoT helps for improving production, decision making and easy to use with data analysis techniques. But here issues regarding privacy and security also rise because of dealing with the large amount of data generated by those devices.

  1. What is IOT?

IoT is nothing but a network which connects things physically which is embedded along with technologies like software and sensors to share data with other devices through internet.

  1. Where IOT is used?

In the fast growing technology of IoT and the need for connectivity it has now been used in many industries for its great performance in collecting and processing of data from the connected device through network also for better decision making and automation. The need for IoT has increased in industries such as transportation, manufacturing and others which use IoT devices like sensors. It is also used in the businesses related to digital transformation of home automation, agriculture, and infrastructure.

  1. Why IOT is proposed? Previous Technology Issues

This technology was designed in order to make improvement in efficiency, automation, user experience and in the knowledge about data driving by creating connection between the real world and the digital world. The main reason behind developing IoT is to overcome the limitations addressed in current technology and to build a better community. IoT was designed to overcome some other issues also which are listed below:

Limited connectivity: With earlier technology it was not possible to communicate always between others, IoT was designed for exchange of data and communication wirelessly.

Lack of remote monitoring: Remote monitoring came into existence because of IoT, through which enterprises or people can operate their device from any place.

Environmental impacts: Because of not properly using resource or monitoring them, problems on environment may occur. IoT technology can properly maintain energy and disposal of trashes.

Complexity of scaling: Scaling in IoT become more manageable and flexible because of its modular architecture which is resource consuming and difficult in earlier technologies.

  1. Algorithms / Protocols

The algorithms provided for C-RAN to overcome the previous issues faced by it are mentioned here: “Hierarchical federated learning intrusion detection system” (HFed-IDS), “K-nearest neighbor” (KNN), “Cheetah Optimization Algorithm” (COA), “Viterbi algorithm” and “Multi-Head Attention (MHA)-Based Gated Recurrent Unit” (GRU).

  1. Comparative study / Analysis

The comparison analysis between the previous studies and the framework suggested here are done to build secure IoT devices by developing intrusion detection. The performance of IoT devices should not go down because of increase in number of users, it should provide better accuracy, rate of false alarm, detection rate, recall, F1-score and precision.

  1. Simulation results / Parameters

The approaches which were proposed to overcome the issues faced by IoT technology are tested using different methodologies to analyze its performance. The comparison is done by using metrics like F1-score, Specificity, Scalability, Sensitivity, Precision, Accuracy, Throughput, Time complexity, Recall and Latency.

  1. Dataset LINKS / Important URL

Here are some of the links provided for you below to gain more knowledge about IoT technology which can be useful for you:

  1. IOT Applications

The applications of IoT have increased in many areas and business. IoT automates, simplifies and improves the processes by creating a connection between humans, machines and the data. Sensors which are connected to each other and working based on artificial intelligence, can build an efficiently working system which are also cost effective.

  1. Topology

Topology refers to the structure of an IoT network, about their organization, configuration and how the components of network are connected to each other in order to build a proper system. The topology of network may vary based on the communication protocols, requirements, devices involved and scalability.

  1. Environment

IoT networks are working in several sectors such as healthcare, transportation, smart homes, agriculture and industrial automation. They have significant advantages like cost efficiency, safety and bring new applications by using data from real world. This network also has some issues regarding privacy, data management and security which have to be addressed.

  1. Simulation Tools

Here we provide some simulation software for previous works, which is established with the usage of NS 3 tool with version 3.36 or above version.

  1. Results

After going through this research based on IoT Technology, you can understand in detail about this technology, how it is connected, applications of this technology, different topologies of it, algorithms followed by it and also about the limitations of it.

IoT Security Research Ideas

  1. Investigation of the Internet of Things (IoT) Security and Privacy Issues
  2. Enhancing IoT Security and User Experience: Leveraging SGIoT-SURE for Effective Security Implementations
  3. Penetration Testing for IoT Security: The Case Study of a Wireless IP Security CAM
  4. Taxonomy of IoT Security Attacks and Emerging Solutions
  5. Issues and Future Trends in IoT Security using Blockchain: A Review
  6. IoT Security: AI Block chaining Solutions and Practices
  7. Enhancing IoT Security and Privacy with Trusted Execution Environments and Machine Learning
  8. Enhancing IoT Security: Design and Evaluation of a Raspberry Pi-Based Intrusion Detection System
  9. Enhancing IoT Security: Integrating MQTT with ARIA Cipher 256 Algorithm Cryptography and mbedTLS
  10. An IoT Security Risk Assessment Framework for Healthcare Environment
  11. Statistical Analysis of Remote Health Monitoring Based IoT Security Models & Deployments from a Pragmatic Perspective
  12. Top 10 IoT security probing areas
  13. Advances in IoT Security: Vulnerabilities, Enabled Criminal Services, Attacks, and Countermeasures
  14. Enhancing IoT Security with Federated Deep Learning Techniques
  15. A survey on key management solutions for IoT security
  16. Threat Modeling with Mitre ATT&CK Framework Mapping for SD-IOT Security Assessment and Mitigations
  17. Four-layer Architecture for IoT Security in Fog Network
  18. Implementation of IoT Security System by Incorporating Block Chain Technology
  19. Blockchain-Enabled IoT (B-IoT): Overview, Security, Scalability & Challenges
  20. IOT Security and Machine Learning Algorithms: Survey and Analysis
  21. Addressing IoT Security Challenges: A Framework for Determining Security Requirements of Smart Locks Leveraging MQTT-SN
  22. Enhancing IoT Security: A Machine Learning Approach to Intrusion Detection System Evaluation
  23. A Brief Overview of Deep Learning Approaches for IoT Security
  24. Malware Clustering System using Moth-Flame Optimization as IoT Security Strengthening
  25. A Machine Learning-Based Methodology for IoT Security
  26. Quantifying IoT Security Parameters: An Assessment Framework
  27. Key Update for the IoT Security Standard OSCORE
  28. IoT Security Based on Smart Contracts: Classification of Algorithms, Complexity, Robustness and Fields of Application
  29. Comparative Study of Machine Learning Algorithms for IoT Security
  30. Wireless IoT Security Management Enhancement and Optimization using Various Elements
  31. Reinforcing IoT Security through Machine Learning Based Spam Detection
  32. Anomaly Detection for IoT Security: Comprehensive Survey
  33. Introducing Deep Learning for IoT Security
  34. Overcoming New Technologies Challenges in IoT Security Labs: Strategies for Effective Adaptation
  35. Enhancing IoT Security: Machine Learning-Based Network Intrusion Detection
  36. Enhancing IoT Security and Privacy through Blockchain Technology, Reinforcement Learning, and Constitutional AI
  37. A Review on Role of Image Processing Techniques to Enhancing Security of IoT Applications
  38. Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation
  39. A Blockchain-based IoT Security Solution Using Multichain
  40. Social IoT Security and Privacy
  41. Edge Computing for IoT Security: Integrating Machine Learning with Key Agreement
  42. Juliet-PUF: Enhancing the Security of IoT-Based SRAM-PUFs Using the Remanence Decay Effect
  43. Research and Design of Programmable IoT Security Controller
  44. PRIDES: A Power Rising Descending Signature for Improving IoT Security
  45. A Key Generation Scheme from Sensing Data for IoT Security: IEEE CNS 23 Poster
  46. IoT Security Performance Intelligent Prediction Based on Lightweight M-Squeeze Net
  47. Worst Attack Vulnerability and Fortification for IoT Security Management: An approach and An Illustration for Smart Home IoT
  48. A Comprehensive Analysis of Machine Learning and Deep Learning Approaches towards IoT Security
  49. Efficient ASIC Implementation for Satellite-IoT Security Co-processor
  50. Soft Bloc: An IoT Security and Privacy Architecture for a Cashier less Retail Store