Vulnerable GPU Memory Management: Towards Recovering Raw Data from GPU

In this paper, we present that security threats coming with existing GPU memory management strategy are overlooked, which opens a back door for adversaries to freely break the memory isolation: they enable adversaries without any privilege in a computer to recover the raw memory data left by previous processes directly. More importantly, such attacks can work on not only normal multi-user operating systems, but also cloud computing platforms. To demonstrate the seriousness of such attacks, we recovered original data directly from GPU memory residues left by exited commodity applications, including Google Chrome, Adobe Reader, GIMP, Matlab. The results show that, because of the vulnerable memory management strategy, commodity applications in our experiments are all affected

An Empirical Study on Android for Saving Non-shared Data on Public Storage

With millions of apps that can be downloaded from official or third-party market, Android has become one of the most popular mobile platforms today. These apps help people in all kinds of ways and thus have access to lots of user's data that in general fall into three categories: sensitive data, data to be shared with other apps, and non-sensitive data not to be shared with others. For the first and second type of data, Android has provided very good storage models: an app's private sensitive data are saved to its private folder that can only be access by the app itself, and the data to be shared are saved to public storage (either the external SD card or the emulated SD card area on internal FLASH memory). But for the last type, i.e., an app's non-sensitive and non-shared data, there is a big problem in Android's current storage model which essentially encourages an app to save its non-sensitive data to shared public storage that can be accessed by other apps. At first glance, it seems no problem to do so, as those data are non-sensitive after all, but it implicitly assumes that app developers could correctly identify all sensitive data and prevent all possible information leakage from private-but-non-sensitive data. In this paper, we will demonstrate that this is an invalid assumption with a thorough survey on information leaks of those apps that had followed Android's recommended storage model for non-sensitive data. Our studies showed that highly sensitive information from billions of users can be easily hacked by exploiting the mentioned problematic storage model. Although our empirical studies are based on a limited set of apps, the identified problems are never isolated or accidental bugs of those apps being investigated. On the contrary, the problem is rooted from the vulnerable storage model recommended by Android. To mitigate the threat, we also propose a defense framework

HIPTrack: Visual Tracking with Historical Prompts

Trackers that follow Siamese paradigm utilize similarity matching between template and search region features for tracking. Many methods have been explored to enhance tracking performance by incorporating tracking history to better handle scenarios involving target appearance variations such as deformation and occlusion. However, the utilization of historical information in existing methods is insufficient and incomprehensive, which typically requires repetitive training and introduces a large amount of computation. In this paper, we show that by providing a tracker that follows Siamese paradigm with precise and updated historical information, a significant performance improvement can be achieved with completely unchanged parameters. Based on this, we propose a historical prompt network that uses refined historical foreground masks and historical visual features of the target to provide comprehensive and precise prompts for the tracker. We build a novel tracker called HIPTrack based on the historical prompt network, which achieves considerable performance improvements without the need to retrain the entire model. We conduct experiments on seven datasets and experimental results demonstrate that our method surpasses the current state-of-the-art trackers on LaSOT, LaSOText, GOT-10k and NfS. Furthermore, the historical prompt network can seamlessly integrate as a plug-and-play module into existing trackers, providing performance enhancements. The source code is available at https://github.com/WenRuiCai/HIPTrack.Comment: Accepted by CVPR202

経尿道的結石破砕術における精密レーザー照射のための形状記憶合金を用いた多方向屈曲デバイス

Tohoku University芳賀洋一課

Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild

In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild. In particular, we focus on four popular obfuscation approaches: identifier renaming, string encryption, Java reflection, and packing. To obtain the meaningful statistical results, we designed efficient and lightweight detection models for each obfuscation technique and applied them to our massive APK datasets (collected from Google Play, multiple third-party markets, and malware databases). We have learned several interesting facts from the result. For example, malware authors use string encryption more frequently, and more apps on third-party markets than Google Play are packed. We are also interested in the explanation of each finding. Therefore we carry out in-depth code analysis on some Android apps after sampling. We believe our study will help developers select the most suitable obfuscation approach, and in the meantime help researchers improve code analysis systems in the right direction

Experimental Investigations into Failures and Nonlinear Behaviors of Structural Membranes with Open Cuttings

Featured Application: Failure modes of structural membrane with open cuttings have been identified. The new insights can be applicable to structural health monitoring of the thin-walled shell structures.The nonlinear relationship between cutting angle and the force strongly relates to the ultimate limit state of the structural membranes.A new formula has been proposed to help engineering design and evaluate the ultimate capacity of the structural membranes with and without open cuttings.Abstract: Reportedly, structural failures in membrane structures have occurred frequently, mostly originating from localized damage caused by intense loads on the membrane surface. It is thus necessary to investigate the nonlinear behaviors and load-carrying capacity of membranes with local damage. This study has conducted uniaxial tensile tests for membranes with a variety of original defects by using a specialized experimental setup and photogrammetry technique. The nonlinear relationship between the mechanical properties and the deforming angle of membranes, which portrays the principal axis, tensor, tensile stress, and position of the original defects, is investigated. The entire process of membrane failure has been recorded, and the strain and stress during each test specimen are compared. The new results indicate that the membranes exhibit predominantly elastic deformation before failure but surprisingly impart brittle fracture upon failure. Finally, a novel approach for estimating the load-bearing capacity of initially damaged membranes was proposed through the analysis of the load-bearing capacity of the damaged membranes under various conditions, positions, angles, and other influential factors

An innovative binocular vision-based method for displacement measurement in membrane structures

This article presents a new binocular vision method for accurate deformation measurements of flexible membrane structures. Using enhanced marker points on the membrane, the method identifies areas for displacement measurements, filtering out unwanted image features with scale-invariant feature transform and threshold correlation. It integrates Canny edge recognition and quadratic weighted averaging for precise positioning of measurement points. By comparing reference images and utilizing the principle of minimum distance between matching points, the method achieves fast matching and determines the three-dimensional coordinates of marker points, enhancing measurement efficiency and robustness. This approach has been empirically tested on membrane structures, providing new insights. The results highlight that our novel algorithm can achieve high-precision measurements down to millimeters, and its accuracy increases with the actual displacement of the membrane structure. Notably, this groundbreaking measurement method remains unaffected by the form of the membrane surface, addressing a long-standing challenge in the field