Container technology plays an essential role in many Information and Communications Technology (ICT) systems. However, containers face a diversity of threats caused by vulnerable packages within ...container images. Previous vulnerability scanning solutions for container images are inadequate. These solutions entirely depend on the information extracted from package managers. As a result, packages installed directly from the source code compilation, or packages downloaded from the repository, etc., are ignored. We introduce DAVS–A Dockerfile analysis-based vulnerability scanning framework for OCI-based container images to deal with the limitations of existing solutions. DAVS performs static analysis using file extraction based on Dockerfile information to obtain the list of Potentially Vulnerable Files (PVFs). The PVFs are then scanned to figure out the vulnerabilities in the target container image. The experimental shows the outperform of DAVS on detecting Common Vulnerabilities and Exposures (CVE) of 10 known vulnerable images compared to Clair– the most popular container image scanning project. Moreover, DAVS found that 68% of real-world container images are vulnerable from different image registries.
Advances in speech synthesis have exposed the vulnerability of spoofing countermeasure (CM) systems. Adversarial attacks exacerbate this problem, mainly due to the reliance of most CM models on deep ...neural networks. While research on adversarial attacks in anti-spoofing systems has received considerable attention, there is a relative scarcity of studies focused on developing effective defense techniques. In this study, we propose a defense strategy against such attacks by augmenting training data with frequency band-pass filtering and denoising. Our approach aims to limit the impact of perturbation, thereby reducing the susceptibility to adversarial samples. Furthermore, our findings reveal that the use of Max-Feature-Map (MFM) and frequency band-pass filtering provides additional benefits in suppressing different noise types. To empirically validate this hypothesis, we conduct tests on different CM models using adversarial samples derived from the ASVspoof challenge and other well-known datasets. The evaluation results show that such defense mechanisms can potentially enhance the performance of spoofing countermeasure systems.
Nowadays, Android malware uses sensitive APIs to manipulate an Android device’s resources frequently. Conventional malware analysis uses hooking techniques to detect this harmful behavior. However, ...this approach is facing many problems, such as low coverage rate and computational overhead. To solve this problem, we proposed HALWatcher, an alternative technique to monitor resource manipulation on Android Open Source Project (AOSP). By modifying Hardware Abstract Layer (HAL) resource accessing interfaces and their implementation, we can embed more monitoring functions at critical methods that are in charge of transferring data between the Hardware Driver and the Framework Layer. Hence, HALWatcher provides a lightweight and high coverage rate system that can perform resource manipulation monitoring for Android OS. In this paper, we prove that the hooking technique is limited in detecting resource manipulation attacks. Besides that, HALWatcher shows an outperform detection rate with a low computational effort.
Voice phishing (vishing) is increasingly popular due to the development of speech synthesis technology. In particular, the use of deep learning to generate an arbitrary-content audio clip simulating ...the victim's voice makes it difficult not only for humans but also for automatic speaker verification (ASV) systems to distinguish. Countermeasure (CM) systems have been developed recently to help ASV combat synthetic speech. In this work, we propose BTS-E, a framework to evaluate the correlation between Breathing, Talking (speech), and Silence sounds in an audio clip, then use this information for deepfake detection tasks. We argue that natural human sounds, such as breathing, are hard to synthesize by Text-to-speech (TTS) system. We conducted a large-scale evaluation using ASVspoof 2019 and 2021 evaluation set to validate our hypothesis. The experiment results show the applicability of the breathing sound feature in detecting deepfake voices. In general, the proposed system significantly increases the performance of the classifier by up to 46%.
In recent years, container technology has caught the attention of the communities by its performance and compactness. Although the design of modern container tools (e.g., Docker and podman) serves as ...a single-purpose application provider, existing deployed containers still contain extra tools that are unnecessary for a single-purpose process. The existence of unnecessary files and tools is directly proportional to higher security risk. Besides, extraneous files often make the container heavier and slow down its performance. This paper introduces a novel Lightweight Virtualization packaging model for creating profiles for a single-purpose application from an existing multi-purpose container environment, called AppPACK. Specifically, the model can generate a package containing minified versions of images, kernel, and virtual machine profiles from a target application. The experiment results show that AppPACK can provide an image of 1.1 to 37 times smaller in size compared to the original version. The experiment on execution shows that using AppPACK profiles could fasten the booting process from 1.1 to 6 times compared to the non-AppPACK version. The comparison between AppPACK and previous approaches shows that proposed model can provide more compatible and smaller versions in most cases.
Herein, selenium doped‐zinc oxide decorated in graphene (Se@ZnO/Gr ‐ SZG) was facilely synthesized via the hydrothermal method with orange peel extract as a reducing agent. The composite was well ...characterized by various modern analytical methods. In terms of the characterization analysis, the synthesized Se@ZnO with high crystallinity has a hamburger‐like structure uniformly distributed on the graphene sheets. The effects of catalyst dosage, H2O2 volume, and pH on the photodegradation of para‐nitrophenol are studied. Besides, the investigation of the photodegradation performance revealed a 99.22 % elimination under treatment of 15 mg of SZG catalyst in the presence of 1.25 mL H2O2 at pH 9 for 100 min UV irradiation. Accordingly, the results express the potentiality of the material in organic matter treatment.
The purpose of this study was to research about supplementation of different concentrations of the substrate on the degradation rate of xenobiotic and to determine the optimal concentrations of the ...auxiliary substrates that are most beneficial of xenobiotic degradation rate. 2,4-dichlorophenol acid (2,4-D) was used representative xenobiotic organic compounds, while peptone and sugar used for auxiliary substrates. The activated sludge was completely break down 100 mg/l of 2,4-D for three consecutive times. The different concentrations between biogenic substracts of sucrose and peptone were fed separately or combined into the medium containing 200 mg/l of 2,4-D and 140 mg SS/l of activated sludge. The results showed that sugar and peptone could affect 2,4-D degradation rate to several different degree at different concentrations. In separate supplementation, 2,4-D degradation completed within 25 hours, 40 mg/l sugar and 150 mg/l peptone concentrations were found to be the optimal concentrations. In combined case, 2,4-D was consumed totally within 20 hours and the optimal concentration of the combined sugar and peptone concentrations were 40 and 150 mg/l, respectively.
In this study, silver/graphene oxide nanocomposites (Ag/GO) was synthesized via in situ method for antibacterial application. Silver/graphene oxide cotton fabric(Ag/GO/cotton fabric) was then ...synthesized via the dip ‐ coating method. The characteristics of GO, Ag/GO, and Ag/GO/cotton fabric were investigated with Fourier transform infrared spectroscopy, X‐ray diffraction, transmission electron microscopy, Raman spectroscopy, and energy ‐ dispersive X‐ray spectroscopy. The results showed that the distribution of silver particles with an average size of 17.41±4.55 nm was uniformed on the GO sheets. The Ag/GO mounted on the fabric surface after coated. Pseudomonas aeruginosa ATCC 27853 (P. aeruginosa) and Staphylococcus aureus ATCC 25923 (S. aureus) were used to test the antibacterial activity of Ag/GO and Ag/GO/cotton fabric by disk diffusion method. The results demonstrated that Ag/GO displayed high antibacterial activity with minimum inhibitor concentration (MIC) value was 2.0 and 50.0 μg/mL with P. aeruginosa and S. aureus, respectively. The Ag/GO/cotton fabric was able to against two types of bacteria P. aeruginosa and S. aureus with diameter of inhibition zone was 5.00 and 2.50 mm, respectively. The results had prospective applications in a lot of fields like clothing, mask, and protective gear.
PDF
