By: Gonipalli Bharath, Vel Tech University, Chennai, India,& International Center for AI and Cyber Security Research and Innovations, Asia University, Taiwan, gonipallibharath@gmail.com
Abstract:
The Internet of Things (IoT) has enabled a new paradigm in how devices interact with each other and has brought seamless connectivity and automation in most fields. Once again, globalization contributes to several serious security issues. Consequently, the cyber-attack, integrity and privacy of valuable data, and resilience against attacks on IoT systems are important for IoT protection. In this article, procedures, contemporary research activities, and other measures to protect IoT ecosystem will be discussed.
Introduction:
The IoT world is growing fast, linking many smart gad͏gets to homes, businesses, health care, and transport setups. These gadgets need connection through networks for gathering data, sharing info, and checking data. In this way the rise of linking has made IoT systems a likely target for cyberattacks! Some gaps are weak passwords; old firmware; and encryption that might cause big problems: data leak and wrong access! Fixing these safety worries is more important for keeping up the growth and trust of IoT tech.
Methodology:
IoT security is a multi-layered approach, from hardware-based solutions and improved software to network protocols. In this regard, such a methodological approach would encompass three key components:
- Device-Level Retina: Secure booting, hardware encryption, and routine firmware updates.
- Network Security: Employing encrypted communication channels using TLS/SSL protocols and deploying firewalls and intrusion detection systems to monitor traffic flow on the network.
- User Awareness: Educating users to follow secure practices like strong passwords and phishing
This implies the convergence of cryptographic algorithms, blockchain technology, and AI in threat detection to enable holistic security. When integrated with such technologies, it can help in monitoring and responding to potential threats at the earliest.
Figure (1)
Literature Review:
The literature has identified a few methods to improve IoT security, such as:
Cryptographic Solutions: Identified lightweight encryption algorithms like ECC (or) Elliptic Curve Cryptography, that work well for resource-constrained IoT devices. These can protect data robustly without affecting performance [[1]].
Integration of Blockchain: Pointed the possibility of blockchain for securing IoT networks. Blockchain decentralizes data storage, and the integrity and trust in the data are achieved through tamper-proof ledgers [[2]].
AI-Based Threat Detection: The application of machine learning algorithms in detecting anomalies within the IoT network. The algorithm detects abnormal patterns in activities and can predict possible attacks so that effective proactive security can be deployed [[3]].
Security Frameworks: NIST has a general IoT security framework that can present guidelines on how to securely design, implement, and maintain IoT devices [[4]]. Even with such progress, challenges remain regarding the trade-off between security and device performance, and scalability in diverse IoT ecosystems.
Conclusion:
IoT security will act as an enabler for the continued growth and wide-scale adoption of smart devices. By addressing this vulnerability, putting in place a strong security mechanism, the entire ecosystem of IoT will have a safeguard against the continuously evolving cyber threats. The important things in building resilient infrastructure in IoT are continuous research, educating users, and following security frameworks. With more and more devices joining this revolution, proactive security best practices will assure benefits from IoT are achieved with no compromise on safety and trust.
References:
- Gudala, Leeladhar, Mahammad Shaik, Srinivasan Venkataramanan, and Ashok Kumar Reddy Sadhu. “Leveraging Artificial Intelligence for Enhanced Threat Detection, Response, and Anomaly Identification in Resource-Constrained IoT Networks.” Distributed Learning and Broad Applications in Scientific Research 5 (July 5, 2019): 23–54.
- Karie, Nickson M., Nor Masri Sahri, Wencheng Yang, Craig Valli, and Victor R. Kebande. “A Review of Security Standards and Frameworks for IoT-Based Smart Environments.” IEEE Access 9 (2021): 121975–95. https://doi.org/10.1109/ACCESS.2021.3109886.
- Kumar, Rajesh, and Rewa Sharma. “Leveraging Blockchain for Ensuring Trust in IoT: A Survey.” Journal of King Saud University – Computer and Information Sciences 34, no. 10, Part A (November 1, 2022): 8599–8622. https://doi.org/10.1016/j.jksuci.2021.09.004.
- Prakash, M., and K. Ramesh. “ECAUT: ECC-Infused Efficient Authentication for Internet of Things Systems Based on Zero-Knowledge Proof.” The Journal of Supercomputing 80, no. 17 (November 1, 2024): 25640–67. https://doi.org/10.1007/s11227-024-06427-9.
- AlZu’bi, S., Shehab, M., Al-Ayyoub, M., Jararweh, Y., & Gupta, B. (2020). Parallel implementation for 3d medical volume fuzzy segmentation. Pattern Recognition Letters, 130, 312-318.
- Lu, J., Shen, J., Vijayakumar, P., & Gupta, B. B. (2021). Blockchain-based secure data storage protocol for sensors in the industrial internet of things. IEEE Transactions on Industrial Informatics, 18(8), 5422-5431.
- Cajes N. (2025) Redefining IoT Security: Hybrid Deep Learning Against DDoS Attacks, Insights2Techinfo, pp.1
Cite As
Bharath G. (2025) IoT Security: Safeguarding the Smart Devices Revolution, Insights2Techinfo, pp.1