China's Proposal for the Eastern Mediterranean Conflict Resolution: A "Developmental Peace"

The Eastern Mediterranean is one of the epicenters of Middle Eastern conflicts ranging from internal and bilateral to multilateral disputes. Outside powers adhere to diverse outlooks of peace initiatives. The western liberalists highlight "democratic peace", emphasizing that "democracy deficit" causes conflict. China favors the "developmental peace" proposal and argues that conflicting parties can achieve peace through domestic and regional development. China dispatched peacekeeping forces to Lebanon for humanitarian rescues for the Republic in 2020, offered developmental aid and economic assistance to Lebanon, Syria and Palestine to improve their capacity with key infrastructure and livelihood projects as the centerpiece, and participated in post-war reconstruction in the three war-torn countries as well. The "developmental peace" argument is based on China's four-decade-long Reform and Opening-up experience, a potentially new scenario for the Eastern Mediterranean conflict resolution

Kairos: Practical Intrusion Detection and Investigation using Whole-system Provenance

Provenance graphs are structured audit logs that describe the history of a system's execution. Recent studies have explored a variety of techniques to analyze provenance graphs for automated host intrusion detection, focusing particularly on advanced persistent threats. Sifting through their design documents, we identify four common dimensions that drive the development of provenance-based intrusion detection systems (PIDSes): scope (can PIDSes detect modern attacks that infiltrate across application boundaries?), attack agnosticity (can PIDSes detect novel attacks without a priori knowledge of attack characteristics?), timeliness (can PIDSes efficiently monitor host systems as they run?), and attack reconstruction (can PIDSes distill attack activity from large provenance graphs so that sysadmins can easily understand and quickly respond to system intrusion?). We present KAIROS, the first PIDS that simultaneously satisfies the desiderata in all four dimensions, whereas existing approaches sacrifice at least one and struggle to achieve comparable detection performance. Kairos leverages a novel graph neural network-based encoder-decoder architecture that learns the temporal evolution of a provenance graph's structural changes to quantify the degree of anomalousness for each system event. Then, based on this fine-grained information, Kairos reconstructs attack footprints, generating compact summary graphs that accurately describe malicious activity over a stream of system audit logs. Using state-of-the-art benchmark datasets, we demonstrate that Kairos outperforms previous approaches.Comment: 23 pages, 16 figures, to appear in the 45th IEEE Symposium on Security and Privacy (S&P'24

Design and synthesis of a new mannitol stearate ester-based aluminum alkoxide as a novel tri-functional additive for poly(vinyl chloride) and its synergistic effect with zinc stearate

Thermal stabilizers, lubricant, and plasticizers are three crucial additives for processing poly(vinyl chloride) (PVC). In this study, a new mannitol stearate ester-based aluminum alkoxide (MSE-Al) was designed and synthesized as a novel additive for PVC. The thermal stability and processing performance of PVC stabilized by MSE-Al were evaluated by the Congo red test, conductivity measurement, thermal aging test, ultravioletevisible (UV–Vis) spectroscopy test, and torque rheometer test. Results showed that the addition of MSE-Al could not only markedly improve the long-term thermal stability of PVC, but also greatly accelerate the plasticizing and decrease the balance torque, which demonstrated that MSE-Al possessed a lubricating property. Thus, MSE-Al was demonstrated to be able to provide tri-functional additive roles, e.g., thermal stabilizer, plasticizer, and lubricant. The test results for the thermal stability of PVC indicated that the initial whiteness of PVC stabilized by MSE-Al was not good enough, thus the synergistic effect of MSE-Al with zinc stearates (ZnSt2) on the thermal stability of PVC was also investigated. The results showed that there is an appreciable synergistic effect between MSE-Al and ZnSt2. The thermal stabilization mechanism and synergism effect of MSE-Al with ZnSt2 are then discussed

Profiling Good Leakage Models For Masked Implementations

Leakage model plays a very important role in side channel attacks. An accurate leakage model greatly improves the efficiency of attacks. However, how to profile a good enough leakage model, or how to measure the accuracy of a leakage model, is seldom studied. Durvaux et al. proposed leakage certification tests to profile good enough leakage model for unmasked implementations. However, they left the leakage model profiling for protected implementations as an open problem. To solve this problem, we propose the first practical higher-order leakage model certification tests for masked implementations. First and second order attacks are performed on the simulations of serial and parallel implementations of a first-order fixed masking. A third-order attack is performed on another simulation of a second-order random masked implementation. The experimental results show that our new tests can profile the leakage models accurately

Towards Optimal Pre-processing in Leakage Detection

An attacker or evaluator can detect more information leakages if he improves the Signal-to-Noise Ratio (SNR) of power traces in his tests. For this purpose, pre-processings such as de-noise, distribution-based traces biasing are used. However, the existing traces biasing schemes can\u27t accurately express the characteristics of power traces with high SNR, making them not ideal for leakage detections. Moreover, if the SNR of power traces is very low, it is very difficult to use the existing de-noise schemes and traces biasing schemes to enhance leakage detection. In this paper, a known key based pre-processing tool named Traces Linear Optimal Biasing (TLOB) is proposed, which performs very well even on power traces with very low SNR. It can accurately evaluate the noise of time samples and give reliable traces optimal biasing. Experimental results show that TLOB significantly reduces number of traces used for detection; correlation coefficients in $\rho$-tests using TLOB approach 1.00, thus the confidence of tests is significantly improved. As far as we know, there is no pre-processing tool more efficient than TLOB. TLOB is very simple, and only brings very limited time and memory consumption. We strongly recommend to use it to pre-process traces in side channel evaluations

Facile synthesis of di-mannitol adipate ester-based zinc metal alkoxide as a bi-functional additive for poly(vinyl chloride)

A new di-mannitol adipate ester-based zinc metal alkoxide (DMAE-Zn) was synthesized as a bi-functional poly(vinyl chloride) (PVC) thermal stabilizer for the first time. The materials were characterized with Fourier transform infrared spectroscopy (FT-IR) and thermogravimetric analysis (TGA). Characterization results confirmed the formation of Zn–O bonds in DMAE-Zn, and confirmed that DMAE-Zn had a high decomposition temperature and a low melting point. The thermal stability of DMAE-Zn on PVC also was tested by a conductivity test, a thermal aging test, and a UV-visible spectroscopy (UV-VIS) test. PVC stabilized by DMAE-Zn had a good initial color and excellent long-term stability. UV-VIS also showed that the conjugated structure in PVC stabilized by DMAE-Zn was almost all of the triene, suggesting that the addition of DMAE-Zn would suppress the formation of conjugated structures above tetraene. The dynamic processing performance of PVC samples tested by torque rheometer indicated that, having a good compatibility with PVC chains in the amorphous regions, DMAE-Zn contributed a good plasticizing effect to PVC. DMAE-Zn thus effectively demonstrates bi-functional roles, e.g., thermal stabilizers and plasticizers to PVC. Furthermore, FT-IR, a HCl absorption capacity test, and a complex ZnCl2 test were also used to verify the thermal stability mechanism of DMAE-Zn for PVC

Hydrogenated vacancies lock dislocations in aluminium

Due to its high diffusivity, hydrogen is often considered a weak inhibitor or even a promoter of dislocation movements in metals and alloys. By quantitative mechanical tests in an environmental transmission electron microscope, here we demonstrate that after exposing aluminium to hydrogen, mobile dislocations can lose mobility, with activating stress more than doubled. On degassing, the locked dislocations can be reactivated under cyclic loading to move in a stick-slip manner. However, relocking the dislocations thereafter requires a surprisingly long waiting time of ~10³s, much longer than that expected from hydrogen interstitial diffusion. Both the observed slow relocking and strong locking strength can be attributed to superabundant hydrogenated vacancies, verified by our atomistic calculations. Vacancies therefore could be a key plastic flow localization agent as well as damage agent in hydrogen environment

Manifold Learning Towards Masking Implementations: A First Study

Linear dimensionality reduction plays a very important role in side channel attacks, but it is helpless when meeting the non-linear leakage of masking implementations. Increasing the order of masking makes the attack complexity grow exponentially, which makes the research of nonlinear dimensionality reduction very meaningful. However, the related work is seldom studied. A kernel function was firstly introduced into Kernel Discriminant Analysis (KDA) in CARDIS 2016 to realize nonlinear dimensionality reduction. This is a milestone for attacking masked implementations. However, KDA is supervised and noise-sensitive. Moreover, several parameters and a specialized kernel function are needed to be set and customized. Different kernel functions, parameters and the training results, have great influence on the attack efficiency. In this paper, the high dimensional non-linear leakage of masking implementation is considered as high dimensional manifold, and manifold learning is firstly introduced into side channel attacks to realize nonlinear dimensionality reduction. Several classical and practical manifold learning solutions such as ISOMAP, Locally Linear Embedding (LLE) and Laplacian Eigenmaps (LE) are given. The experiments are performed on the simulated unprotected, first-order and second-order masking implementations. Compared with supervised KDA, manifold learning schemes introduced here are unsupervised and fewer parameters need to be set. This makes manifold learning based nonlinear dimensionality reduction very simple and efficient for attacking masked implementations

SNR-Centric Power Trace Extractors for Side-Channel Attacks

The existing power trace extractors consider the case that the number of power traces owned by the attacker is sufficient to guarantee his successful attacks, and the goal of power trace extraction is to lower the complexity rather than increase the success rates. Although having strict theoretical proofs, they are too simple and leakage characteristics of POIs have not been thoroughly analyzed. They only maximize the variance of data-dependent power consumption component and ignore the noise component, which results in very limited SNR to improve and seriously affects the performance of extractors. In this paper, we provide a rigorous theoretical analysis of SNR of power traces, and propose a novel SNR-centric extractor, named Shortest Distance First (SDF), to extract power traces with smallest the estimated noise by taking advantage of known plaintexts. In addition, to maximize the variance of the exploitable component while minimizing the noise, we refer to the SNR estimation model and propose another novel extractor named Maximizing Estimated SNR First (MESF). Finally, we further propose an advanced extractor called Mean optimized MESF (MMESF) that exploits the mean power consumption of each plaintext byte value to more accurately and reasonably estimate the data-dependent power consumption of the corresponding samples. Experiments on both simulated power traces and measurements from an ATmega328p micro-controller demonstrate the superiority of our new extractors