The Evolution of IoT Security : From Basic to Advanced Protection

By: Vanna karthik; Vel Tech University, Chennai, India

Abstract

With applications in a wide range of industries, including healthcare, smart cities, transportation, and more, the Internet of Things (IoT) has grown rapidly in recent years. However, the complexity and scope of security issues related to IoT devices are growing along with their growth. This study examines how IoT security has changed over time, following its development from simple defense techniques to more complex, sophisticated approaches. IoT security was first concentrated on simple encryption and authentication methods, but as cyber threats have grown more sophisticated, sophisticated strategies like blockchain, machine learning-based intrusion detection, and quantum-resistant algorithms have surfaced. The purpose of this article is to draw attention to the necessity of ongoing security protocol innovation in order to protect IoT networks from new threats and maintain user privacy and data integrity.

Introduction

The term “Internet of Things” refers to a network of linked devices that communicate with one another and exchange information via the internet. The Internet of Things is revolutionizing a number of industries, including manufacturing, healthcare, home automation, and agriculture. At the same time, this increases in the number of devices being connected over the internet increased security concerns. Because IoT devices collect sensitive data, such as personal information, health metrics, and environmental data, they easily become the prime targets for malicious attacks[1].

Thus, the evolution of IoT security has been consistent with the growth in these devices, from very simple protection measures to more advanced, complex security defense mechanisms[2]. The paper aims at looking at the historical steps of IoT security practices, noting how different obstacles came about with each step and how the cybersecurity community reacted towards curbing those threats. Only through an analysis of how IoT security has developed will we better position ourselves to handle future challenges for securing both devices and connected networks.

Literature Review

Early IoT Security (Basic Protection Measures)

Security in the early stages of IoT development was often an afterthought, and most devices were released without proper protection mechanisms. Basic security features, such as password protection, secure booting, and encryption, were the primary means of securing devices. However, these approaches were often insufficient since many IoT devices had limited processing power and storage, making it difficult to implement robust security measures[3].

Different researchers have pointed to a lack of standardization and poor implementation as major challenges for early IoT security. Many devices were shipped with default, weak passwords, while in most cases encryption algorithms were either missing or poorly implemented, hence creating enormous vulnerabilities that hackers frequently used in their advantage.

Intermediate IoT Security (Network and Data Protection)

As IoT technology matured, security practices evolved to focus on protecting the network and the data that was being passed between devices as opposed to protecting the devices themselves. SSL encryption, firewalls, and intrusion detection systems (IDS) were some of the common techniques. At this stage, the focus began to evolve to a more holistic perspective of security, not just on the device but what data was being transmitted and in many cases was vulnerable[4].

During this period, the internet of things (IoT) network security challenges included managing disparate devices that often had various capabilities and operating systems. These IoT devices’ lack of uniformity made it challenging to apply standard security techniques across networks.

A diagram of a network and data flow

AI-generated content may be incorrect.

Advanced IoT Security (Intelligent and Adaptive Protection)

With the rise in the number of cyberattacks against IoT networks, more sophisticated security solutions began to emerge. This includes machine learning-based intrusion detection systems, blockchain for secure device authentication and data integrity, and quantum-resistant encryption protocols. Machine learning thus lets an IoT system dynamically detect and respond to anomalous activities, therefore making a system more adaptive to new evolving threats[5].

Also, the concept of Zero Trust security architecture has gained prominence in the IoT landscape. Zero Trust assumes that no device or user should be trusted by default, and access is granted only after continuous authentication and authorization processes. This approach is increasingly being applied in advanced IoT systems to safeguard against internal and external threats[6].

Future Trends and Challenges

IoT security will continue to evolve in the future with the integration of new technologies like AI and 5G networks. AI will definitely improve security by automating threat detection and response, while 5G, with its higher bandwidth and greater connectivity, makes the landscape of IoT security even more complex. Securing a hyper-connected world with billions of devices remains an ongoing challenge.

Conclusion

It is a major leap in IoT security, evolving each day in light of the challenge posed by it. IoT security has moved on from mere simple protection techniques, integrating machine learning, blockchain, and Zero Trust architectures into an advanced phase of security measures. While these strides have grown, so also the challenges of fast growth of devices demand more and more innovative methods in the protocols of security.

The future for the security of IoT lies with integrating AI and quantum computing together over next-generation networks such as 5G. However, all this has to be correctly premised on security being recognized as a never-stop process that shall require proactive IoT system security for emerging cyber-attacks. Only then, several years into the future, with the required unity between industries and governments together along with cybersecurity experts, security and privacy for the IoT network might be attained.

References

  1. A. Wakili and S. Bakkali, “Privacy-preserving security of IoT networks: A comparative analysis of methods and applications,” Cyber Secur. Appl., vol. 3, p. 100084, Dec. 2025, doi: 10.1016/j.csa.2025.100084.
  2. E. Schiller, A. Aidoo, J. Fuhrer, J. Stahl, M. Ziörjen, and B. Stiller, “Landscape of IoT security,” Comput. Sci. Rev., vol. 44, p. 100467, May 2022, doi: 10.1016/j.cosrev.2022.100467.
  3. A. Rayes and S. Salam, “Internet of Things Security and Privacy,” in Internet of Things from Hype to Reality: The Road to Digitization, A. Rayes and S. Salam, Eds., Cham: Springer International Publishing, 2022, pp. 213–246. doi: 10.1007/978-3-030-90158-5_8.
  4. A. Rayes and S. Salam, Internet of Things from Hype to Reality: The Road to Digitization. Cham: Springer International Publishing, 2022. doi: 10.1007/978-3-030-90158-5.
  5. M. M. Rahman, S. A. Shakil, and M. R. Mustakim, “A survey on intrusion detection system in IoT networks,” Cyber Secur. Appl., vol. 3, p. 100082, Dec. 2025, doi: 10.1016/j.csa.2024.100082.
  6. S. Li, M. Iqbal, and N. Saxena, “Future Industry Internet of Things with Zero-trust Security,” Inf. Syst. Front., vol. 26, no. 5, pp. 1653–1666, Oct. 2024, doi: 10.1007/s10796-021-10199-5.
  7. Bhatti, M. H., Khan, J., Khan, M. U. G., Iqbal, R., Aloqaily, M., Jararweh, Y., & Gupta, B. (2019). Soft computing-based EEG classification by optimal feature selection and neural networks. IEEE Transactions on Industrial Informatics, 15(10), 5747-5754.
  8. Singh, A., & Gupta, B. B. (2022). Distributed denial-of-service (DDoS) attacks and defense mechanisms in various web-enabled computing platforms: issues, challenges, and future research directions. International Journal on Semantic Web and Information Systems (IJSWIS), 18(1), 1-43.

Cite As

Karthik V. (2025) The Evolution of IoT Security : From Basic to Advanced Protection, Insights2techinfo pp.1

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