The integration of satellite and terrestrial networks effectively addresses geographical limitations, providing extensive and seamless connectivity. Despite robust security measures implemented in both terrestrial networks and satellite communication systems, certain inherent vulnerabilities in LTE/5G protocols can still be exploited, potentially compromising security. In this paper, we propose a security evaluation model, SigOverlay, which targets both terrestrial cellular networks and satellite communication networks. By exploiting the inherent openness of the Physical Broadcast Channel, SigOverlay can stealthily disrupt regular communication without incurring substantial additional power consumption. Experiments with commercial software-defined radios demonstrated the feasibility and effectiveness of this strategy, revealing security risks in integrated satellite-terrestrial networks.

Current research on the security of radio access networks (RAN) mainly focuses on constructing and analyzing attack models that target individual layers of the protocol stack. However, such attack methods often overlook the inherent vulnerabilities arising from interactions between different layers, which can be exploited to launch more effective attacks. We propose a novel control-plane cross-layer attack, called CLAS (Cross-Layer Attack System), which enables an attacker to use a single device to stealthily spoof the target user, interrupt its existing connection, and hijack it to a fake base station. This results in a covert and persistent Denial-of-Service (DoS) attack. Through experiments on commercial off-the-shelf (COTS) devices, we demonstrate that by collaboratively exploiting vulnerabilities across multiple protocol layers, the proposed CLAS only requires 4dB higher transmit power than a legitimate base station to achieve a 100% success rate. The attack effect can persist for up to 760.2 seconds, while simultaneously doubling the energy consumption rate of the victim device. This paper highlights critical security gaps in the current architecture of RAN, particularly in cross-layer protocol vulnerability management.

The security of Radio Access Network (RAN) is increasingly becoming a focal point of attention. The lack of integrity protection and encryption mechanisms in the Radio Resource Control (RRC) protocol before the establishment of a security context poses a significant security threat that cannot be overlooked. Unlike traditional full-band radio jamming and Fake Base Station (FBS) attacks, Signal Overshadowing can precisely target specific time-frequency resource blocks, offering stronger stealth and energy efficiency. In this paper, we propose two novel attack patterns targeting System Information Block type 1 (SIB1) by leveraging Signal Overshadowing. These attacks achieve precise and stealthy signal injection through high-precision time-frequency synchronization. Experimental results demonstrate that both attack patterns can effectively cause Denial of Service (DoS) while maintaining stable characteristics of the received signal, such as Reference Signal Received Power (RSRP), with no significant fluctuations observed. These innovative attack strategies provide valuable insights into the vulnerabilities of the RAN protocols and contribute to the development of further security enhancement mechanisms.

MOTIVATION: Low-frequency DNA mutations are often confounded with technical artifacts from sample preparation and sequencing. With unique molecular identifiers (UMIs), most of the sequencing errors can be corrected. However, errors before UMI tagging, such as DNA polymerase errors during end repair and the first PCR cycle, cannot be corrected with single-strand UMIs and impose fundamental limits to UMI-based variant calling. RESULTS: We developed smCounter2, a UMI-based variant caller for targeted sequencing data and an upgrade from the current version of smCounter. Compared to smCounter, smCounter2 features lower detection limit that decreases from 1 to 0.5%, better overall accuracy (particularly in non-coding regions), a consistent threshold that can be applied to both deep and shallow sequencing runs, and easier use via a Docker image and code for read pre-processing. We benchmarked smCounter2 against several state-of-the-art UMI-based variant calling methods using multiple datasets and demonstrated smCounter2's superior performance in detecting somatic variants. At the core of smCounter2 is a statistical test to determine whether the allele frequency of the putative variant is significantly above the background error rate, which was carefully modeled using an independent dataset. The improved accuracy in non-coding regions was mainly achieved using novel repetitive region filters that were specifically designed for UMI data. AVAILABILITY AND IMPLEMENTATION: The entire pipeline is available at https://github.com/qiaseq/qiaseq-dna under MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.