A distributed anomaly detection system for in-vehicle network using HTM

With the development of 5G and Internet of Vehicles technology, the possibility of remote wireless attack on an in-vehicle network has been proven by security researchers. Anomaly detection technology can effectively alleviate the security threat, as the first line of security defense. Based on this, this paper proposes a distributed anomaly detection system using hierarchical temporal memory (HTM) to enhance the security of a vehicular controller area network bus. The HTM model can predict the flow data in real time, which depends on the state of the previous learning. In addition, we improved the abnormal score mechanism to evaluate the prediction. We manually synthesized field modification and replay attack in data field. Compared with recurrent neural networks and hidden Markov model detection models, the results show that the distributed anomaly detection system based on HTM networks achieves better performance in the area under receiver operating characteristic curve score, precision, and recall

Accurate Sybil attack detection based on fine-grained physical channel information

With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless network

P‐64: UV‐Light‐Modified Polyimide Films for Liquid‐Crystal Alignment

Infrared, UV‐visible and X‐ray photoelectron spectroscopy measurements indicate that bond‐breaking and oxidation occur during broadband UV‐illumination of the polyimide film in the air. Surface tension and polarity are increased based on the measurements of contact angles. No obvious morphology change has been observed through atomic force microscopy analysis. While the polarized UV‐light generates a relatively small pretilt angle on a nonrubbed surface, it reduces the pretilt angle to some degree on a rubbed surface, depending upon the UV‐light polarization direction relative to the rubbing direction.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92039/1/1.1833863.pd

Cost–Benefit Analysis of a Trans-Arctic Alternative Route to the Suez Canal: A Method Based on High-Fidelity Ship Performance, Weather, and Ice Forecast Models

Climate change in recent years has produced viable shipping routes in the Arctic. However, critical uncertainties related to maritime operations in the Arctic make it difficult to predict ship speeds in ice and, thus, the voyage time and fuel costs. Cost–benefit analysis of alternative Arctic routes based on accurate environmental condition modeling is required. In this context, this paper presents a holistic approach that considers the major voyage-related costs of a trans-Arctic route as an alternative to the conventional routes via the Suez Canal Route (SCR) for existing merchant ships. This tool is based on high-fidelity models of ship performance, metocean forecasting, and a voyage optimization algorithm. Case studies are performed based on a general cargo vessel in operation to quantify realistic expenses inclusive of all the major operational, fuel, and voyage costs of the specific voyages. A comparison is made between the total costs of the trans-Arctic route and SCR for different seasons, which proves the economic feasibility of the trans-Arctic route. Overall, this work can provide valuable insights to help policymakers as well as shipbuilders, owners, and operators to assess the potential cost-effectiveness and sustainability of future Arctic shipping, thereby better developing future strategies

Robust Quantum State Transfer in Random Unpolarized Spin Chains

We propose and analyze a new approach for quantum state transfer between remote spin qubits. Specifically, we demonstrate that coherent quantum coupling between remote qubits can be achieved via certain classes of random, unpolarized (infinite temperature) spin chains. Our method is robust to coupling strength disorder and does not require manipulation or control over individual spins. In principle, it can be used to attain perfect state transfer over arbitrarily long range via purely Hamiltonian evolution and may be particularly applicable in a solid-state quantum information processor. As an example, we demonstrate that it can be used to attain strong coherent coupling between Nitrogen-Vacancy centers separated by micrometer distances at room temperature. Realistic imperfections and decoherence effects are analyzed.Comment: 4 pages, 2 figures. V2: Modified discussion of disorder, added references - final version as published in Phys. Rev. Let

Finding Multiple Roots of Nonlinear Equation Systems via a Repulsion-Based Adaptive Differential Evolution

Finding multiple roots of nonlinear equation systems (NESs) in a single run is one of the most important challenges in numerical computation. We tackle this challenging task by combining the strengths of the repulsion technique, diversity preservation mechanism, and adaptive parameter control. First, the repulsion technique motivates the population to find new roots by repulsing the regions surrounding the previously found roots. However, to find as many roots as possible, algorithm designers need to address a key issue: how to maintain the diversity of the population. To this end, the diversity preservation mechanism is integrated into our approach, which consists of the neighborhood mutation and the crowding selection. In addition, we further improve the performance by incorporating the adaptive parameter control. The purpose is to enhance the search ability and remedy the trial-and-error tuning of the parameters of differential evolution (DE) for different problems. By assembling the above three aspects together, we propose a repulsion-based adaptive DE, called RADE, for finding multiple roots of NESs in a single run. To evaluate the performance of RADE, 30 NESs with diverse features are chosen from the literature as the test suite. Experimental results reveal that RADE is able to find multiple roots simultaneously in a single run on all the test problems. Moreover, RADE is capable of providing better results than the compared methods in terms of both root rate and success rate