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.

Unmanned aerial vehicle (UAV) swarms require accurate relative localization to safeguard flight missions in the global navigation satellite system-denied environment due to a lack of absolute position information. The existing work of relative localization faces challenges, such as the ranging information loss and the low localization frequency caused by long-distance ranging and large-scale characteristic of the UAV swarm. This article proposes a clustering-based cooperative relative localization scheme for UAV swarm, which contains a two-level framework: inter/intra-cluster localization. In order to investigate the tradeoff between intracluster cooperation and intercluster packet loss, the clustering-based problem is constructed as a coalition formation game (CFG) model. Given the designed coalition value, preference relation, and the coalition formation principles, it is proved that the proposed CFG model has a Nash stable partition. The designed coalition formation algorithm includes coalition heads and beacon drones selection mechanism. Simulation results show that the proposed CFG algorithms shorten the ranging time compared with global localization and achieve better localization performance (localization error and success rate) than contrast algorithms.

In recent years, PowerShell has increasingly been reported as appearing in a variety of cyber attacks. However, because the PowerShell language is dynamic by design and can construct script fragments at different levels, state-of-the-art static analysis based PowerShell attack detection approaches are inherently vulnerable to obfuscations. In this paper, we design the first generic, effective, and lightweight deobfuscation approach for PowerShell scripts. To precisely identify the obfuscated script fragments, we define obfuscation based on the differences in the impacts on the abstract syntax trees of PowerShell scripts and propose a novel emulation-based recovery technology. Furthermore, we design the first semantic-aware PowerShell attack detection system that leverages the classic objective-oriented association mining algorithm and newly identifies 31 semantic signatures. The experimental results on 2342 benign samples and 4141 malicious samples show that our deobfuscation method takes less than 0.5 s on average and increases the similarity between the obfuscated and original scripts from 0.5% to 93.2%. By deploying our deobfuscation method, the attack detection rates for Windows Defender and VirusTotal increase substantially from 0.33% and 2.65% to 78.9% and 94.0%, respectively. Moreover, our detection system outperforms both existing tools with a 96.7% true positive rate and a 0% false positive rate on average.

The scheduling of data access plays a prominent part in a memory-based fast Fourier transform (FFT) processor. In this article, a conflict-free data-access scheme is proposed and applied to implement a radix-2k FFT processor with the computing parallelism being the power of 2. The proposed FFT module exploits single-port RAMs to retain the area efficiency, and it has the following hardware-friendly features. First, the memories are merged into four banks under the arbitrary computing parallelism, which helps to circumvent the complicated data-routing circuit. Second, the parallelism of the input/output (I/O) data can be enlarged to the internal computing parallelism, which accelerates the data update and enhances the throughput capability. Furthermore, the concurrent I/O operation that overlaps the storage of the FFT input with the supply of FFT output in the same memory sets is allowed, which minimizes the memory occupation for the management of continuous data flow. Based on the testing on the field-programmable gate array (FPGA) and ASIC implementation using the SMIC 40-nm CMOS technology, it is demonstrated that the proposed FFT processor can offer high throughput and simultaneously achieve remarkable area and power efficiency.

This paper presents an area-efficient radix-2kFFT processor employing single-port memory, where the deployed memory is merged into 4 banks for arbitrary 2k-parallel computation. The proposed design enables the FFT input/output to operate in the parallelism equal to that of internal processing, and it paves the way for gaining high-throughput capability. Moreover, the in-place data caching strategy is available to allow the overlap between caching input data and supplying FFT results, which can further enhance throughput without consuming additional area. Theoretical and experimental comparisons demonstrate the proposed FFT processor can surpass the published related work in throughput while preserving high area efficiency.

The problem of quantization for Log-likelihood ratios in the presence of a practical automatic-gain-control (AGC) is elaborated in this paper. A median based quantization approach is proposed, in which the median of the absolute value of loglikelihood ratios (LLRs) is set as the quantized midpoint. This approach can diminish the mutual information loss caused by quantization. When applied to bit-interleaved coded modulation scheme, the proposed quantizer proves to be robust to different transmission schemes in both AWGN and rayleigh channels. The implementation issue of median estimate using subset averaged median estimator is also covered in details.

Jointly detecting the signals from the source and relay in a spatial multiplexing (SM) multiple-input multiple-output (MIMO) relaying system improves the transmit reliability significantly. However, the existing joint detection schemes for SM MIMO relaying systems, which achieve full diversity, such as the near maximum likelihood (ML) decoder, suffer from high complexity. In this paper, we propose a weighted combining (WC) algorithm, which is applied before the detector in the SM MIMO decode-and-forward relaying system. The proposed algorithm merges the received signal vectors from the source and relay into a combined signal without expanding their dimension, and formulates an equivalent MIMO channel matrix for the combined signal, resulting in a lower complexity for the subsequent detection. We analyze the performance of the proposed WC algorithm with ML detection in terms of the diversity order and computational complexity. An approximate upper bound on the symbol error probability (SEP) for the proposed algorithm is also derived. Simulation results show that in symmetric networks, the proposed WC algorithm achieves substantially lower complexity, while maintaining an SEP performance similar to that of the benchmark NML decoder. The consistency of the derived upper bound on the SEP is also verified by simulations.

Jointly detecting signals from the source and relay in a multi-input multi-output (MIMO) relaying system can achieve lower symbol error probability (SEP) and higher diversity order. In the literature, the best detector for spatial multiplexing decode-and-forward (DF) MIMO relaying systems is the near maximum likelihood (NML) decoder. However, both NML decoder and its variation are computationally intensive, especially when high-order modulations and multiple data streams are adopted. In order to develop a more efficient detection scheme, we propose a weighted combining (WC) algorithm which is applied before the final detector. The proposed algorithm merges the signal vectors from the source and relay without expanding their dimension and formulates an equivalent MIMO channel matrix for the combined signal, resulting in a much lower complexity for the subsequent detection. Simulation results show that by using the proposed WC algorithm with the ML detector, the same diversity gain as that of the more complex NML detection scheme can be achieved. In particular, in a symmetric network topology, the performance of the proposed WC algorithm is comparable to that of NML.

This paper presents a mixed-decimation multipath delay feedback (M2 DF) approach for the radix-2kfast Fourier transform. We employ the principle of folding transformation to derive the proposed architecture, which activates the idle period of arithmetic modules in multipath delay feedback (MDF) architectures by integrating the decimation-in-time operations into the decimation-in-frequency-operated computing units. Furthermore, we compare the proposed design with other efficient schemes, namely, the MDF and the multipath delay commutator (MDC) scheme theoretically and experimentally. Relying on the obtained expressions and statistics, it can be concluded that the M2DF design serves as an efficient alternative to the MDF scheme, since it achieves improved efficiency in the utilization of arithmetic resources without deteriorating the superiorities of feedback structures. In addition, the recommended design performs better in memory requirement and computing delay compared with the MDC approach.