ABSTRACT To address the limitations of conventional reactive log anomaly detection in high‐availability systems, this paper presents OADS—an online anomaly detection system that synergizes time‐series prediction with real‐time detection. The system features LSP‐Informer, a multivariate log sequence predictor built upon Informer architecture and enhanced by a novel weighted combination loss (WCL) that simultaneously optimizes both prediction accuracy and semantic consistency. Furthermore, OADS implements a unique prediction‐detection cascade by integrating LSP‐Informer with a Temporal Convolutional Network + Attention (TCNA)‐based Log Anomaly Detection Model (LADM), enabling proactive anomaly forecasting 5–10 steps ahead. Experimental results on HDFS logs demonstrate exceptional performance: The TCNA‐based LADM achieves an F1‐score of 0.9860, while LSP‐Informer maintains a 0.9801 F1‐score for 5‐step‐ahead prediction. The complete OADS system successfully predicts potential anomalies in advance, maintaining a robust 0.73+ Jaccard index under heavy masking conditions while preserving interpretability in real‐world deployments.

With the rapid advancement of 5G technology, the tactile Internet is emerging as a novel paradigm of interaction, particularly in fields like healthcare, where stringent demands for real-time and precise performance are prevalent. During the transmission and storage of medical data, malicious adversaries may attempt to compromise sensitive patient information or even disrupt the normal operation of medical devices, posing a threat to patient safety. Many existing authentication schemes claim and prove to resist various known attacks. However, subsequent research has uncovered security vulnerabilities in these schemes, primarily due to their oversight of implicit attacks, which stem from different combinations or inferences of known attacks. In this context, the design of a lightweight authentication scheme that is secure against implicit attacks becomes crucial. This paper proposes IAR-AKA, an authentication scheme for the healthcare tactile Internet environment that surpasses conventional security. We conduct formal security proofs based on session key security and its corresponding implicit attacks, and also perform non-formal security analysis based on the relationship between implicit attacks and security goals. The output of AVISPA tool indicates IAR-AKA is secure. Furthermore, detailed performance analysis results indicate that IAR-AKA not only possesses more security attributes against implicit attacks compared to similar solutions in comparable contexts but also exhibits lower communication and computation costs.

The insufficient trustworthiness of fog nodes in fog computing leads to new security and privacy problems in communication between entities. Existing authentication schemes rely on a trusted third party, or assume that fog nodes are trustworthy, or the authentication overhead is high, which is inconsistent with the characteristics of fog computing. To solve the problem of secure communication in the fog computing environment, we propose an efficient blockchain-based secure remote authentication protocol for the fog-enabled Internet of Things (BSRA). Specifically, blockchain is introduced to construct distributed trust for the fog computing environment. Only lightweight cryptographic primitives, such as physical unclonable functions (PUFs) and cryptographic hash functions, are exploited to design the authentication scheme. In addition, we use temporary identities and the authentication-piggybacking-synchronization to ensure the anonymity and effectiveness of the authentication scheme. We conduct security analysis to demonstrate that BSRA can provide guarantees against various known attacks. We also evaluate the performance of BSRA from several aspects, and the results show that BSRA is effective.

Designing an efficient and secure authentication scheme is an significant means to ensure the security of IoT systems. Hundreds of authentication schemes tailored for IoT environments have been proposed in recent years, and regrettably, many of them were soon found to have succumbed to security vulnerabilities. In an effort to investigate the underlying reason for this, Wang et al. (at TIFS’23) recently analyzed the vulnerability of authentication schemes from the perspective of provable security. However, we observe that some authentication schemes with sound security proofs and heuristic security analysis are also not resistant to certain attacks, and even those that have been improved several times are still not immune. To explore the deep-seated reasons for security vulnerabilities in IoT authentication schemes, we divide security attacks into explicit and implicit attacks and find that many authentication schemes exhibit security under explicit attacks but are rendered vulnerable under implicit attacks. Further, we propose the relationship between the design goals of security attributes of authentication schemes and implicit attacks, analyze the vulnerability of three typical authentication schemes under implicit attacks, and find that only the security attributes capable of resisting the strongest implicit attacks are secure. Finally, we offer some specific suggestions on how to achieve the security attribute goals.

Anonymity, robust synchronization, and perfect forward secrecy are the most important security properties of authenticated key agreement (AKA) protocols. Designing AKA protocols that simultaneously achieve these security properties and availability in the IoT environment is a challenging task. AKA protocols built using public key cryptographic primitives have advantages in achieving these critical security properties, but performing expensive public-key cryptographic operations is inefficient for resource-constrained IoT devices. The authentication protocols based on symmetric cryptographic primitives are often subject to various attacks. This paper proposes a secure lightweight AKA protocol with critical security properties (called CS-LAKA) for IoT environments without using public-key cryptographic primitives. LAKA cleverly achieves the security goals of anonymity, robust synchronization, and perfect forward secrecy by embedding dynamic identities in authenticators, and a few additional exchange messages are added. This enables LAKA to have both robust security and high efficiency. Subsequently, we perform a formal security analysis to prove that LAKA is secure, and compared with existing related schemes, LAKA has obvious advantages in terms of security, functionality and running performance.

Wearable computing has been used in a wide range of applications. But wearable computing often suffers from various security and privacy issues. To solve these issues, many effective authentication schemes have been proposed. However, most of the existing schemes are vulnerable to various known attacks (such as desynchronization attack, privileged-insider attack, and anonymity attack), or require high computation and communication costs, and are not suitable for resource-constrained wearable devices, or simultaneous verification of multiple wearable devices is not supported. Therefore, in this paper, we propose a new anonymous authentication and group proof protocol for wearable computing, which achieves mutual authentication between the wearable device and user and between user and cloud server, and generates a group proof for multiple wearable devices. Further, we extend the Real-Or-Random (ROR) model to support anonymity and group proof, and formally prove that the proposed scheme is provably secure under the extended security model. In addition, the informal security analysis is demonstrated that the proposed scheme is more resilient against known attacks. Finally, compared with some existing schemes, the proposed scheme offers more functionality features and requires less communication and computation costs.

Tag cloning attack is a serious threat to the radio‐frequency identification (RFID) applications. Cloned tags detection is an effective security mechanism to prevent the attacks. To improve the accuracy and efficiency of detection for cloned tags, this study presents a deterministic cloned tags detection (DCTD) protocol for anonymous RFID systems to detect cloned tags, using a tree‐based anti‐collision algorithm to find irreconcilable collisions. This protocol, which uses the pseudonym of tags in the detecting process, can quickly detect all the cloned tags with a deterministic time without revealing the sensitive information. Experiments show that DCTD protocol, with less detection time and higher accuracy, outperforms the known detection protocols.