Recent operating systems (OSs) have adopted a defense mechanism called kernel page table isolation (KPTI) for protecting the kernel from all attacks that break the kernel address space layout randomization (KASLR) using various side-channel analysis techniques. In this paper, we demonstrate that KASLR can still be broken, even with the latest OSs where KPTI is applied. In particular, we present a novel memory-sharing-based side-channel attack that breaks the KASLR on KPTI-enabled Linux virtual machines. The proposed attack leverages the memory deduplication feature on a hypervisor, which provides a timing channel for inferring secret information regarding the victim. By conducting experiments on KVM and VMware ESXi, we show that the proposed attack can obtain the kernel address within a short amount of time. We also present several countermeasures that can prevent such an attack.
Meltdown is a microarchitectural side-channel attack that extracts sensitive data in the kernel space of operating systems (OSs). Meltdown deliberately creates transient executions by exploiting an out-of-order execution technique and obtains the execution results through a cache covert channel. In a previous attack, an OS signal handler and hardware transactional memory support (i.e., Intel TSX) were used to establish the cache covert channel. However, both methods restricted the effectiveness of the attack owing to the large amount of system noise caused by the context switching of signal handlers and the narrow range of TSX-enabled processors. Hence, we propose a new variant of the Meltdown attack using a return stack buffer (RSB). The RSB enables the establishment of a low-noise cache covert channel without relying on processor-specific hardware features, such as TSX. The wide usage of the RSB in commodity processors further improves the effectiveness of the proposed attack. We present the details of our implementation of the attack and evaluate the performance. Furthermore, we overview several existing countermeasures against the proposed attack.
The purpose of this study is to analyze middle school teachers' concern about and implementation degree of performance assessment in China. The research questions are as follows: First, what kind of concern is held by middle school teachers who implement performance assessment? Second, is there any significant difference in stages of concern the teachers on performance assessment according to their gender, education level and teaching career? Third, which level of use is shown by middle school teachers who implement performance assessment? Fourth, what is the correlation between middle school teachers' Stages of Concern and Levels of Use on performance assessment? This study was conducted based on a Concerns-Based Adoption Model (Hall, 1973; CBAM) that viewed teachers as the most primary factor of the execution of innovation, in this case, performance assessment. Performance assessment is assessment based on observation and judgement (Stiggins, 1994), and require test takers to complete a process or produce a product in a context that closely resembles real-life situations. The subjects of this study were randomly sampled from 120 middle school teachers throughout Bei-Jing, China. The questionnaires were distributed to them by mail, and they were asked to return their questionnaire by mail. The collect data were analyzed by SPSS/WIN 18.0 program in terms of frequency, correlation, or MANOVA. Frequency analysis was used to analyze concern of middle school teachers on performance assessment. To gain an frequency of the individuals in each stage, we regarded the stage in which a teacher had his/her highest score as his/her relevant stage. Correlation analysis was adopted to identify the correlation between teachers' stage of concern and level of use. To analyze the difference of the concern of China middle school teachers on performance assessment according to their individual background variables such as gender, education level, and teaching career, MANOVA was performed.
In this paper, comparative analysis on the characteristics of the Pseudo Random Sequence(PRS) and the Normal Random Sequence(NRS) which are used as a watermark for copyright protection and authentication about digital media in the conventional digital watermarking systems. From the analysis, it is found that in case of the NRS, the detection of the watermark might be difficult by many crosscorrelation peak values from other NRS codes because of the non-uniform distribution of 1 and 0 in those codes. However, in case of the PRS, since it has the uniform distribution of the random number in the generated codes, there exists very few crosscorrelation peaks. So the PRS is analyzed to be more robust against possible attacks such as JPEG image compression and Gaussian noise compared with the case of the NRS. Finally, in this paper, simulation results on the robustness of the PRS and NRS against some attacks such as JPEG compression, Gaussian noise are also suggested.
In this paper, a new digital watermarking scheme based-on the random casting method in the DCT domain is proposed. In the conventional watermarking methods, the DCT-transformed watermark is casting to the high frequency coefficients of the original cover image and the watermark is sequentially embedded in the casting frequency. But this kind of watermarking scheme can be attacked easily by the pirates and unlawful users, because these methods might have some structured patterns by the sequential embedding and the fixed casting domain. Also this method might get the damaged stego-image and is not robust to the image compression algorithms. Therefore, in this paper, a new robust digital watermarking scheme is proposed. In this algorithm, the frequency coefficients of the DCT-transformed original cover-image in which the watermark is inserted are randomly selected. These random position values of the casting frequencies can be used as another secret-key together with the watermark-key. From some experimental results the proposed method is found to be more robust to the possible attacks than those of the conventional methods.
Recently, a considerable number of studies have been conducted on pairing based cryptosystems. The efficiency of pairing based cryptosystems depends on finite fields, similar to existing public key cryptosystems. In general, pairing based ctyptosystems are defined over finite fields of chracteristic three, GF(), based on trinomials. A multiplication in GF() is the most dominant operation. This paper proposes a new most significant digit(MSD)-first digit- serial multiplier. The proposed MSD-first digit-serial multiplier has the same area complexity compared to previous multipliers, since the modular reduction step is performed in parallel. And the critical path delay is reduced from 1MUL+(log +1)ADD to 1MUL+(log )ADD. Therefore, when the digit size is not , the time delay is reduced by one addition.
Graph Neural Networks (GNNs) are increasingly popular for various prediction and recommendation tasks. Unfortunately, the graph datasets for practical GNN applications are often too large to fit into the memory of a single GPU, leading to frequent data loading from host memory to GPU. This data transfer overhead is highly detrimental to the performance, severely limiting the training throughput.
Cache side channel attacks extract secret information by monitoring the cache behavior of a victim. Normally, this attack targets an L3 cache, which is shared between a spy and a victim. Hence, a spy can obtain secret information without alerting the victim. To resist this attack, many detection techniques have been proposed. However, these approaches have limitations as they do not operate in real time. This article proposes a real-time detection method against cache side channel attacks. The proposed technique performs the detection of cache side channel attacks immediately after observing a variation of the CPU counters. For this, Intel PCM (Performance Counter Monitor) and machine learning algorithms are used to measure the value of the CPU counters. Throughout the experiment, several PCM counters recorded changes during the attack. From these observations, a detecting program was implemented by using these counters. The experimental results show that the proposed detection technique displays good performance for real-time detection in various environments.
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