Abstract Currently, the rapid development of Internet of Things (IoT) technology and the deepening digital transformation of traditional industries have driven substantial growth in the Machine Learning as a Service (MLaaS) market to meet massive data processing demands. Principal Component Analysis (PCA), as a widely used dimensionality reduction algorithm in fields such as image processing and finance, involves multiple matrix operations with high computational complexity. As a result, clients with low-capability devices often choose to outsource these computations to cloud servers. However, the privacy and security issues during data outsourcing have become critical challenges that need to be addressed urgently. In this paper, we propose a secure outsourcing computation scheme for PCA based on Householder matrix transformation and Double Random Perturbation Encryption (DRPE) techniques, aiming to protect the privacy of user inputs and outputs. The proposed scheme not only significantly reduces the computational complexity on the client side but also enables the client to detect malicious behaviors from the cloud server with a non-negligible probability, thereby enhancing the security of the data during the outsourcing process and the reliability of the computation results. Furthermore, the proposed scheme adopts a non-interactive design, effectively reducing communication overhead. Through comprehensive security analysis and performance evaluation, we demonstrate the superiority of the proposed scheme in terms of privacy protection, computational efficiency, and verification capability, providing a novel solution for secure outsourcing computing in IoT environments.

In an open and complex environment of drone service collaboration scenarios, efficient identity authentication is essential for secure service interactions. Traditional schemes suffer from high computational costs, low communication efficiency, and vulnerability to single-point failures. This paper presents a new lightweight authentication scheme (BDP-Auth) based on blockchain decentralized identity (DID) and physically unclonable functions (PUFs). PUF enables low-power, low-cost identity key generation without relying on complex computation or large storage, ensuring tamper-proof identifiers while reducing hardware and energy overhead. Using blockchain decentralization, the DID mechanism securely registers and stores drone identities, offering transparency and integrity. Security analysis shows that BDP-Auth achieves forward and backward security, meaning that the compromise of the current session key does not reveal past or subsequent session communications, and also resists physical capture and impersonation attacks. Experiments demonstrate that, compared to PRLAP-IoD, BDP-Auth reduces the computation overhead by 38.3% and 45.0% on the STM32F4 and NodeMCU platforms, respectively, decreases communication overhead by 36.9%, and reduces storage overhead by 27.5%, significantly improving overall efficiency.

The emergence of unmanned aerial vehicle (UAV)-enabled Internet of Things (IoT) represents a new paradigm of intelligent monitoring that transcends geographical limitations. However, UAVs are highly sensitive to disruptive factors, and their failure can easily trigger cascading failures due to a surge in traffic. To address this, this article proposes a cascading failure model to help understand cascading risks, incorporating the unique online and offline modes of UAVs. For the issue of IoT devices not being fully covered after a cascading failure, a topology-control-based recovery scheme is proposed. Surviving UAVs are divided into two categories, where backbone UAVs (BUAVs) hover at specific positions to form a reliable backbone network spanning the service area, and cruising UAVs patrol nearby to achieve extensive coverage. To provide a solution, the optimization model is transformed into two stages, and approximate algorithms are developed separately. The improved combination of cuckoo search and a density-based clustering algorithm is employed to determine the positions for BUAVs. Meanwhile, a multistep approach utilizing the nondominated sorting genetic algorithm II is introduced to optimize the cruising paths of UAVs. Case study shows that the proposed cascading failure model is reasonable; the proposed recovery scheme can achieve up to 91% coverage, with most IoT devices covered by cruising UAVs maintaining more than half of their service time; the recovered network can still maintain 50% of IoT devices within coverage under up to 20% link failure. These findings offer network managers practical insights for enhancing network resilience.

The advancement of space technology has positioned LEO satellite networks as a pivotal solution for global digitalization. However, satellites can fail due to various internal and external threats. Their limited buffer capacity and processing ability can exacerbate failures, posing a risk of cascading failures to the entire network. To delve deeper into the cascading process of LEO satellite networks, we have developed a dynamic cascading failure model. We propose a method to calculate the minimum time required for satellite movement to cover discrete zone units on Earth. By considering the dynamic changes in satellite coverage, we model the probability of user data reaching satellites using a Poisson process. Additionally, we have established models for satellites’ processing ability and buffer capacity to depict a more realistic satellite state transition. Satellites can become congested or even overloaded when they receive an excessive amount of data and require a corrective phase before returning to standard operations. We present a dynamic cascading algorithm, ensuring that the sequence of observations doesn’t impact the final cascading process outcome. Through detailed case studies involving three constellations, we found that cascading failures tend to propagate mainly to satellites within two hops. Smaller constellations are more susceptible to periodic cascading failures, while mega-constellations might experience rapid, severe avalanche effects. These findings offer practical insights for satellite network managers aiming to mitigate cascading risks.

Currently, space information network (SIN) has become an increasingly important role in real life. As a large heterogeneous wireless network, SIN can better provide global mobile services to users anytime and anywhere, even in extreme geographic environments. In addition, there is no need to build the communication base-stations every few kilometers on the ground to ensure high service quality, which greatly reduces the construction costs and can be used as an economical communication method in sparsely populated areas. So there is a trend that more and more end users are more likely to get SIN services than traditional terrestrial cellular networks. However, due to the openness and publicity of the satellite wireless channel and the limited resources of the satellite nodes, the privacy and security cannot be perfectly guaranteed and may even be vulnerable to attacks initiated by the adversary such as replay attacks, impersonation attacks, and eavesdropping attacks. To improve the access security of SIN, researchers have proposed a series of authentication protocols based on different cryptographic assumptions. Nevertheless, existing research shows that these protocols cannot meet the requirements of higher and higher security and short authentication delay. In addition, these protocols are mainly based on public key cryptography mechanisms such as DLP and ECDLP, which can be solved by postquantum computers in polynomial time, so these protocols will no longer be secure. To solve the vulnerability of these protocols, in this paper, we propose a new RLWE-based anonymous mutual authentication and key agreement protocol, which guarantees higher security with low computational overhead even in the postquantum era. Detailed security analysis shows that our protocol meets security requirements and is resistant to a variety of known attacks. Besides, combining security comparison and performance analysis, our proposed protocol is more practical than other protocols in SIN.