How to achieve secure content distribution and accountability in information-centric networking (ICN) is a crucial problem. Subscribers need to verify whether the data came from a reliable source, rather than from a spoofing adversary. Public key cryptography was introduced to achieve a method of authentication that binds the data packet to its owner. In existing prototypes, PKIs, identity-based signatures (IBSs) and recommendation networks are the common schemes used to ensure the authenticity and availability of public keys. However, CA-based PKIs and KGC-based IBSs have been proven to be weak when it comes to resisting security attacks, with recommendation networks being too complex to deploy. In this respect, we designed a novel distributed authentication model as a secure scheme to support public key cryptography. Our model establishes a decentralized public key infrastructure by combining the smart contracts of blockchain and optimized zero-knowledge proof-verifiable presentations by utilizing the DID project, which realizes the management of public key certificates through blockchain and ensures the authenticity and availability of public keys in decentralized infrastructure. Our scheme fundamentally solves the issues of security and feasibility in existing schemes and provides a more scalable solution with respect to authenticating data sources. An experiment demonstrated that our proposal is 20% faster than the original zero knowledge proof scheme in registration.

The various integration systems of blockchain and information-centric network (ICN) have been applied to provide a trusted and neutral approach to cope with large-scale content distribution in IoT, AR/VR, or 5G/6G scenarios. As a result, the scalability problem of blockchain has been an increasing concern for researchers. The sharding mechanism is recognized as a promising approach to address this challenge. However, there are still many problems in the existing schemes. Firstly, real-time processing speed trades off security of validation. Secondly, simply randomly assigning nodes to the shards may make nodes located very far from each other, which increases the block propagation time and reduces the efficiency advantage brought by the sharding mechanism. Therefore, we optimize a reputation-based sharding consensus model by multi-dimension trust and leverage the affinity propagation (AP) algorithm for gathering consensus nodes into shards. Given the minimal possibility to be at fault in the security of validation, clients can achieve real-time processing speed with assurance. The evaluation results show that the normalized mean square error (NMSE) between the estimated reputation value and the real reputation value of our reputation scheme is less than 0.02. Meanwhile, compared with the classical sharding scheme Omniledger, TPS performance can achieve 1.4 times promotion in the case of a large-scale blockchain network of 1000 nodes.

Research on underwater networks has been ongoing for decades. Nevertheless, the evolving operational requirements for highly dynamic and reconfigurable underwater systems demonstrate the insufficiency of traditional network studies constrained to either fixed infrastructure or hybrid topologies with minimal AUV participation, they often fail to address the challenges of fully mobile ad-hoc configurations. Therefore, this paper makes three key contributions to advance research on ad-hoc mobile underwater acoustic networks (AMUAN). First, we present a comprehensive analysis of current limitations and establish the dedicated solution for critical AMUAN needs. Second, we propose a novel lightweight dynamic adaptive routing algorithm specifically optimized for underwater environments with limited communication conditions. Our approach features include a delay/disruption-tolerant protocol based on opportunistic routing principles, and an innovative multi-parameter fusion equilibrium algorithm for neighborhood management and forwarding strategy optimization. Third, through extensive simulations evaluating delay, energy efficiency, security, and network lifetime, we demonstrate our scheme’s superior performance compared to existing solutions. The results particularly highlight exceptional adaptability in dynamic high-load conditions (achieving 15% lower latency than conventional methods) and robust malicious node detection (with 25% security improvement), showcasing its significant advantages and potential for broader application.

Standalone Name Resolution (SNR) is an essential component of many Information-Centric Networking (ICN) infrastructures that maps and stores the mappings of IDs and locators. The delivery of data can be realized only when the name resolution process is completed correctly. It also makes the SNR become the key target of network attackers. In this paper, our research focuses on the more covert and complex Content Pollution Attack (CPA). By continuously sending invalid content to the network at a low speed, attackers will consume a lot of the resources and time of the SNR system, resulting in a serious increase in the resolution delay of normal users and further cache pollution in ICN. It is difficult to be quickly detected because the characteristics of attack are inconspicuous. To address the challenge, a register access control scheme for an SNR system based on a malicious user blacklist query is proposed. A neighbor voting algorithm is designed to discover possible attacks in the network quickly and build a blacklist of malicious users reasonably. Users on the blacklist will be restricted from accessing the ICN network during the registration phase with the resolution system. Incentives and punishments for network users are introduced to automate responses about the potential malicious behavior reports. Our scheme is more efficient as users do not have to wait for an additional system component to perform operations. In addition, our algorithm can better solve the collusion problem in the voting process when compared with the others. We experimentally evaluate our protocol to demonstrate that the probability of successful collusion attack can be reduced to less than 0.1 when the attacker ratio is 0.5.