Integrate the Blockchain and Lightweight Cryptography for Real-Time Threat Identification: Improving Cybersecurity in Internet of Things Networks

At the same time, the Internet of Things (IoT) phenomenon has recently emerged as a very beneficial enabler of automation, real-time monitoring as well as intelligent data processing. But such interconnected systems usually run in resource constrained environments and are threatened by various attacks. ZAMF AC (Joint Second Prize Human Impact Award) Attacks on the Internet of Things (IoT) ecosystem are becoming more complex as well as targeted, making the implementations that are based on traditional security models and cryptographic techniques inadequate for them. The proposed framework integrates blockchain and lightweight in order to provide a real-time threat detection and improve IoT security. Blockchain features a decentralized taming a distributed digital ledger with a rugged consensus, where all participants in the system trust each other, and establishes trust and tamper-resistance and can greatly improve the trust and robustness of the interaction between IOT nodes [12]. Smart contracts facilitate for the system to automatically detect anomalies and raise threat alerts on the network. Lightweight cryptography LWC: Customized for low power, lightweight cryptography is good for devices with limited resources on the area and power consumption of the encryption and authentication to the computing as small as possible, but for secure robust operation. The proposed system architecture is based on the combined security platform that device level data security is protected by lightweight cryptographic algorithms and network level secure and auditable communication is supported using blockchain. Data obtained from IoT sensors are hashed in real time and verified through the use of Blockchain that results in a quick detection of malicious patterns or an unauthorized access. Decentralized threat intelligence sharing also enables the nodes to learn from historic attacks with distributed cooperation, which reinforces the system's tolerance. We experiment with a smart home IoT network to check the efficiency of our model under different attack scenarios like man-in-the-middle, replay, and spoofing attacks. Experimental results show a significantly enhancement on the accuracy of threat detection, the time to alert and the False Positive Rate (FPR) over the traditional practice. Energy consumption is also limited, as optimized cryptographic primitives are involved. This work emphasizes the importance and integration of blockchain and lightweight cryptography in the scalable, reliable and intelligent IoT architectures. Not only the integrated model provides solutions to current cybersecurity problems, but also it paves the way for future developments of autonomous threat mitigation and secure IoT communication architecture.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.