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We consider a discrete-time system where a resource-constrained source (e.g., a small sensor) transmits its time-sensitive data to a destination over a time-varying wireless channel. Each transmission incurs a fixed transmission cost (e.g., energy cost), and no transmission results in a staleness cost represented by the Age-of-Information. The source must balance the tradeoff between transmission and staleness costs. To address this challenge, we develop a robust online algorithm to minimize the sum of transmission and staleness costs, ensuring a worst-case performance guarantee. While online algorithms are robust, they are usually overly conservative and may have a poor average performance in typical scenarios. In contrast, by leveraging historical data and prediction models, machine learning (ML) algorithms perform well in average cases. However, they typically lack worst-case performance guarantees. To achieve the best of both worlds, we design a learning-augmented online algorithm that exhibits two desired properties: (i) consistency: closely approximating the optimal offline algorithm when the ML prediction is accurate and trusted; (ii) robustness: ensuring worst case performance guarantee even ML predictions are inaccurate. Finally, we perform extensive simulations to show that our online algorithm performs well empirically and that our learning augmented algorithm achieves both consistency and robustness. 

To facilitate dynamic spectrum sharing, the FCC has designated certified SAS administrators to implement their own spectrum access systems (SASs) that manage the shared spectrum usage in the novel CBRS band. As a premise, different SAS servers must conduct periodic inter-SAS coordination to synchronize service states and avoid allocation conflicts. However, SAS servers may inevitably stop service for regular upgrades, crash down, or even perform maliciously that deviate from the normal routines, posing a fundamental operation security problem — the system shall be robust against these faults to guarantee secure and efficient spectrum sharing service. Unfortunately, the incumbent inter-SAS coordination mechanism, CPAS, is prone to SAS failures and does not support real-time allocation. Recent proposals that rely on blockchain smart contracts or state machine replication mechanisms to realize fault-tolerant inter-SAS coordination require all SASs to follow a unified allocation algorithm. They however face performance bottlenecks and cannot accommodate the current fact that different SASs hold their own proprietary allocation algorithms. In this work, we propose TriSAS—a novel inter-SAS coordination mechanism to facilitate secure, efficient, and dependable spectrum allocation that is fully compatible with the existing SAS infrastructure. TriSAS decomposes the coordination process into two phases including input synchronization and decision finalization. The firstphase ensures participants share a common input set while the second one fulfills a fair and verifiable spectrum allocation selec- tion, which is generated efficiently via SAS proposers’ proprietary allocation algorithms and evaluated by a customized designed allocation evaluation algorithm (AEA), in the face of no more than one-third of malicious participants. We implemented a prototype of TriSAS on the AWS cloud computing platform and evaluated its throughput and latency performance. The results show that TriSAS achieves high transaction throughput and low latency under various practical settings. 

Dynamic spectrum sharing has emerged as a promising solution to address the spectrum scarcity challenge. Currently, the FCC has designated several Spectrum Access Systems (SAS) administrators to deploy their SAS that coordinates the usage of the certificated shared band(s) such as the 3.55-3.7 GHz CBRS band. The SAS ensures that the incumbent’s access to the shared band is guaranteed while also granting commercial users access rights when the incumbents are not present. However, explicitly sharing the spectrum band(s) information among participants raises privacy concerns. Certain participants, such as curious SAS administrators, have the ability to deduce the confidential operational patterns of the incumbents through the Environmental Sensing Capability (ESC) or Incumbent Informing Capability (IIC) notifications. Additionally, a curious SAS administrator may obtain the client’s operational information of other SAS administrators throughout the process of inter-SAS coordination. We propose Pri-Share, a novel privacy-preserving spectrum sharing paradigm that tailors the threshold-based private set union (PSU) and homomorphic encryption (HE) techniques to address the aforementioned privacy problems. Specifically, it enables all parties to jointly compute a unified spectrum allocation plan to resolve the potential conflicts between different parties while safeguarding the confidentiality of each stakeholder’s spectrum requirements and usage. Pri-Share also ensures that while a curious participant might ascertain the usage of a particular spectrum band, they are unable to deduce the precise identity of the party utilizing it. Besides, Pri-Share adheres to the key spectrum allocation regulations outlined by FCC (part 96), such as assurance of access rights for various priority levels. Our implementation result shows that Pri-Share can be achieved with notable computational and communication efficiency, 

Mobile tracking has long been a privacy problem, where the geographic data and timestamps gathered by mobile network operators (MNOs) are used to track the locations and movements of mobile subscribers. Additionally, selling the geolocation information of subscribers has become a lucrative business. Many mobile carriers have violated user privacy agreements by selling users’ location history to third parties without user consent, exacerbating privacy issues related to mobile tracking and profiling. This paper presents AAKA, an anonymous authentication and key agreement scheme designed to protect against mobile tracking by honest-but-curious MNOs. AAKA leverages anonymous credentials and introduces a novel mobile authentication protocol that allows legitimate subscribers to access the network anonymously, without revealing their unique (real) IDs. It ensures the integrity of user credentials, preventing forgery, and ensures that connections made by the same user at different times cannot be linked. While the MNO alone cannot identify or profile a user, AAKA enables identification of a user under legal intervention, such as when the MNOs collaborate with an authorized law enforcement agency. Our design is compatible with the latest cellular architecture and SIM standardized by 3GPP, meeting 3GPP’s fundamental security requirements for User Equipment (UE) authentication and key agreement processes. A comprehensive security analysis demonstrates the scheme’s effectiveness. The evaluation shows that the scheme is practical, with a credential presentation generation taking∼ 52 ms on a constrained host device equipped with a standard cellular SIM. 

Recent studies have shown that compromising Bitcoin’s peer-to-peer network is an effective way to disrupt the Bitcoin service. While many attack vectors have been uncovered such as BGP hijacking in the network layer and eclipse attack in the application layer, one significant attack vector that resides in the transport layer is largely overlooked. In this paper, we investigate the TCP vulnerabilities of the Bitcoin system and their consequences. We present Bijack, an off-path TCP hijacking attack on the Bitcoin network that is able to terminate Bitcoin connections or inject malicious data into the connections with only a few prior requirements and a limited amount of knowledge. This results in the Bitcoin network topology leakage, and the Bitcoin nodes isolation.