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Electric Vehicles' Controller Area Network (CAN) bus serves as a legacy protocol for in-vehicle network communication. Simplicity, robustness, and suitability for real-time systems are the salient features of CAN bus. Unfortunately, the CAN bus protocol is vulnerable to various cyberattacks due to the lack of a message authentication mechanism in the protocol itself, paving the way for attackers to penetrate the network. This paper proposes a new effective anomaly detection model based on a modified one-class support vector machine in the CAN traffic. The proposed model makes use of an improved algorithm, known as the modified bat algorithm, to find the most accurate structure in the offline training. To evaluate the effectiveness of the proposed method, CAN traffic is logged from an unmodified licensed electric vehicle in normal operation to generate a dataset for each message ID and a corresponding occurrence frequency without any attacks. In addition, to measure the performance and superiority of the proposed method compared to the other two famous CAN bus anomaly detection algorithms such as Isolation Forest and classical one-class support vector machine, we provided Receiver Operating Characteristic (ROC) for each method to quantify the correctly classified windows in the test sets containing attacks. Experimental results indicate that the proposed method achieved the highest rate of True Positive Rate (TPR) and lowest False Positive Rate (FPR) for anomaly detection compared to the other two algorithms. Moreover, in order to show that the proposed method can be applied to other datasets, we used two recent popular public datasets in the scope of CAN bus traffic anomaly detection. Benchmarking with more CAN bus traffic datasets proves the independency of the proposed method from the meaning of each message ID and data field that make the model adaptable with different CAN datasets.INDEX TERMS Electric vehicles, controller area network (CAN Bus), anomaly detection, one-class support vector machine, optimization algorithm.

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Plant-based synthesis of eco-friendly nanoparticles has widespread applications in many fields, including medicine. Biofilm—a shield for pathogenic microorganisms—once formed, is difficult to destroy with antibiotics, making the pathogen resistant. Here, we synthesized gold nanoparticles (AuNPs) using the stem of an Ayurvedic medicinal plant, Tinospora cordifolia, and studied the action of AuNPs against Pseudomonas aeruginosa PAO1 biofilm. The synthesized AuNPs were characterized by techniques such as ultraviolet-visible spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, energy-dispersive X-ray diffraction, X-ray diffraction, scanning electron microscopy (SEM), and transmission electron microscopy. The AuNPs were spherically shaped with an average size of 16.1 nm. Further, the subminimum inhibitory concentrations (MICs) of AuNPs (50, 100, and 150 µg/mL) greatly affected the biofilm-forming ability of P. aeruginosa, as observed by crystal violet assay and SEM, which showed a decrease in the number of biofilm-forming cells with increasing AuNP concentration. This was further justified by confocal laser scanning microscopy (CLSM), which showed irregularities in the structure of the biofilm at the sub-MIC of AuNPs. Further, the interaction of AuNPs with PAO1 at the highest sub-MIC (150 µg/mL) showed the internalization of the nanoparticles, probably affecting the tendency of PAO1 to colonize on the surface of the nanoparticles. This study suggests that green-synthesized AuNPs can be used as effective nano-antibiotics against biofilm-related infections caused by P. aeruginosa.

Rotor active magnetic bearings system is the most efficient supporting technique of high-speed rotating machinery. This work aims to explore the dynamical behaviors of the 6-pole rotor active magnetic bearings system for the first time. Two different control strategies are introduced to mitigate the considered system lateral vibrations and the corresponding whirling motions. The first control technique (Radial control) is suggested such that the attractive magnetic force in each pole is proportional to both the radial displacement and radial velocity of the rotating disk toward that pole. The second control strategy (Cartesian control) is proposed such that the controlled magnetic force in each pole is designed to be proportional to both the cartesian displacement and cartesian velocity of the rotating disk in two perpendicular directions. Based on the proposed control strategies, two nonlinear dynamical models are derived and then analyzed by applying perturbation methods. Different response-curves and bifurcation diagrams are plotted utilizing the disk spinning-speed and the disk eccentricity as bifurcation control parameters. The main obtained analytical and numerical results illustrated that the considered system can perform a circular forward whirling motion only under the first control technique, while four whirling modes (that are forward whirling , backward whirling, both forward and backward whirling, and oscillation along a straight line) are noticed in the second control method depending on the disk spinning speed. Moreover, it is found that the radial control method is robust against the system instability than the cartesian control one, especially at large disk eccentricity. However, the cartesian control method could exhibit a vibration suppression efficiency higher than the radial control one at small disk eccentricity.