In modern software ecosystems, 1-day vulnerabilities pose significant security risks due to extensive code reuse. Identifying vulnerable functions in target binaries alone is insufficient; it is also crucial to determine whether these functions have been patched. Existing methods, however, suffer from limited usability and accuracy. They often depend on the compilation process to extract features, requiring substantial manual effort and failing for certain software. Moreover, they cannot reliably differentiate between code changes caused by patches or compilation variations.To overcome these limitations, we propose Lares, a scalable and accurate method for patch presence testing. Lares introduces Code Slice Semantic Search, which directly extracts features from the patch source code and identifies semantically equivalent code slices in the pseudocode of the target binary. By eliminating the need for the compilation process, Lares improves usability, while leveraging large language models (LLMs) for code analysis and SMT solvers for logical reasoning to enhance accuracy. Experimental results show that Lares achieves superior precision, recall, and usability. Furthermore, it is the first work to evaluate patch presence testing across optimization levels, architectures, and compilers. The datasets and source code used in this article are available at https://github.com/Siyuan-Li201/Lares.

One main drawback of using Time Difference of Arrival (TDOA) methods for source localization and navigation is that they require centralization of multiple copies of a signal. This paper considers blindly estimating the location of a Cyclic Prefix (CP) in an Orthogonal Frequency Division Multiplexing (OFDM) signal, enabling distributed TDOA computation up to an integer ambiguity. This ambiguity can be resolved using integer least-squares methods, if enough TDOAs are available. The contributions of this paper are derivation of the Cramer-Rao Lower Bound (CRLB) on locating the CP, and hence on the underlying source localization problem.

A technique that consists of correlation followed by thresholding is widely used to mitigate multipath effects, especially in the presence of non-line-of-sight (NLoS) effects, for TOA estimation. In practice, an accurate threshold that the technique relies on is difficult to obtain, since optimizing the threshold requires prior knowledge of channel statistics and signal/noise power, which are not always known a priori nor are easy to estimate. In this paper, we propose a new thresholding method that does not rely on such prior knowledge and is robust against an inaccurate threshold.

Non-GPS navigation techniques that use signals of opportunity (e.g. TV/AM broadcast signals with known source locations) without aid of satellite-based location systems (e.g. GPS) are promising since they use readily available strong signals that are not susceptible to blockage or jamming. However, problems such as large asynchronous clock offsets among receivers and large broadcast signal frequency offsets arise because broadcast signals are not dedicated for ranging purposes. In this paper, we propose an asynchronous differential time-difference-of-arrival (TDOA) positioning method to overcome the problems of biased signal frequencies and asynchronous receiver clocks. The proposed method eliminates the need for synchronous receiver clocks in the TDOA method and relaxes the tight timing constraint between receivers as required by the double-difference method in the differential GPS (dGPS).

Most methods for sensor self-localization require either synchronization or round trip communications among the networked sensors. A differential time-difference-of-arrival (dTDOA) method is proposed in this paper that does not require such time synchronization nor round trip communications, thus greatly reduces demand on sensor communications resources and makes implementation much easier. Theoretical results are presented for the principle of the new method and simulations are also given that confirm the effectiveness of the proposed method.

Large clock offsets and drifts impose many difficulties on sensor self-localization. We have proposed a differential time-difference-of-arrival (dTDOA) localization method in [1] to overcome the problem caused by asynchronous clock offsets. In this paper, the dTDOA method is extended to combat clock drifts by a two-stage clock-drift cancellation method. Furthermore, based on the clock-drift cancellation, a maximum likelihood estimation (MLE) method that is theoretically optimal for sensor locations is derived. The method can achieve sensor localization using a single round of time-of-arrival (TOA) measurements, and thus greatly reduces the communications burden and timing constraint.