In the era of increasingly complex and covert network attack on Internet of Things (IoT), existing anomaly detection paradigms often exhibit limitations in characterizing the dynamic evolution and cross-source dependencies inherent in multi-source threat scenarios. Most current approaches rely on static graph structures or single-modal features, failing to fully capture the temporal evolution of topology and heterogeneous information within network traffic. To address these challenges, this work has proposed a novel Anomaly Detection method based on Dynamic Graph structure and Multi-Modal Fusion (DGMF-Net) for IoT. First, we have adopted a Conditional Denoising Diffusion Probabilistic Model (CDDPM) to generate high-quality minority class samples, effectively mitigating data imbalance. Second, we have introduced a sliding time window mechanism to construct dynamic graphs, explicitly modeling the temporal dependencies and evolving correlations among traffic features. Furthermore, we have designed a multimodal feature extraction module that learns representations from three dimensions: statistical patterns (via 1D-CNN), temporal sequences (via GRU), and graph structures (via DGCN). Finally, a cross-modal attention fusion mechanism is adopted to dynamically integrate these heterogeneous features, thereby enhancing our model's perception of complex abnormal patterns. Experimental results on the UNSW-NB15 and CIC-IDS-2017 datasets have demonstrated that our proposed method has achieved superior performance, generalization, and robustness compared to state-of-the-art approaches for anomaly detection in a dynamic network environment of IoT with low false alarm rates.

Due to the shortage of IPv4 addresses, many hosts are currently assigned to a single IPv4 address by using one or a number of NAT devices. However, numerous NAT devices cannot be upgraded for executing 6to4 due to technical and/or economic reasons. Solutions depending on Double Network Address Translation 64 are a good way to utilise shared IP4 addressing. Mapping of address and port using translation (MAP-T) is a technique that accomplishes double translation on Border Relay (BR) and customer edge (CE) devices. IPv4 and IPv6 forwarding, IPv4 and IPv6 fragmentation functions, and NAT64 translation functions are used by MAP-T. This enables increasing numbers of IPv6 in both clients and servers in order to possess the best defence against certain attacks, such as routing loop attacks, spoofing attacks, denial-of-service attacks. We have here proposed some procedures for creating frameworks and sustaining secure IPv6 networks according to applications, environs and architecture.

In future internet architectures, end-to-end (E2E) secured personal messaging is essential. So here an E2E user two-way authenticated double encrypted messaging architecture based on hybrid RSA for private messaging is proposed. Our P2P protocol works over TCP protocol for creating direct connections in between, with IPv4 broadcast options to discover peers on the same LAN. Our protocol implements perfect forward secrecy using Diffie-Hellman key exchange with renegotiation capability in every session with optimal asymmetric encryption padding and random salts. For making hybrid RSA with double encryption, in encryption level, main RSA is integrated with efficient RSA to give more statistical complexity. In the decryption process, the CRT is used for very high efficiency with integration with shared RSA. Our architecture also gives a hassle-free, secure, peer-to-peer, strong and reliable platform with E2E encryption for private messaging and it can also work with future internet architectures.

Efficient balancing of privacy and strong authentication in end-to-end (E2E) security constitutes a challenging task in the field of personal messaging. Since RSA is a ubiquitous approach, we here propose a hybrid RSA-based, highly efficient, reliable and strong personal full mesh networked messaging scheme. M-prime RSA and CRT-RSA with shared RSA makes our hybrid RSA decryption much more secure and efficient and protects our users with complete privacy. However, computational modular exponentiation complexity and partial key exposure vulnerability of RSA present two major obstacles. Low modular complexity and asymptotic very slow speed of decryption of RSA, with the ease and speed problem in encryption of RSA are also problems to be solved. Our hybrid RSA cipher resolves all of the above issues and provides protection against exploitation of multiplicative property and homomorphic property of RSA. Our full mesh networking scheme also ensures E2E encryption for all peers. So, our three-way authenticated hybrid RSA messaging scheme achieves a perfect balance of efficiency, security, authentication, reliability and privacy. Consequently, our scheme offers a smarter choice for private messaging in existing, as well as future, internet architectures.