Search

Ensuring the integrity of outsourced data is one of several functional requirements in cloud storage services, although designing an effective and secure public auditing scheme remains an ongoing research challenge. For example, a number of existing schemes are designed based on symmetric bilinear pairing, which are computationally expensive. While certificate-based auditing schemes can simplify certificate management and mitigate key escrow concern, such schemes are not popular in the literature. Therefore, we propose a lightweight certificate-based public/private auditing scheme based on asymmetric bilinear pairing for cloud storage. Specifically, we describe a new method of designing lightweight auditing schemes. Additionally, our proposed scheme is proven to be secure in the random oracle model. We then implement our scheme by using type D curve of the pairing-based library. The findings demonstrate that our auditing scheme significantly reduces client's computation cost in the tag-generation (TagGen) phase, particularly in comparison to several other competing schemes. For example, when the block size is 10 KB, our on-line computation cost in the TagGen phase takes only 0.45 seconds, while it requires at least 62.83 seconds in other schemes. Furthermore, the findings show that when the number of blocks is fixed, the on-line computation cost in our TagGen phase is constant despite varying file sizes.

In order to realize the accurate recognition of American license plate, an algorithm based on multi-model fusion is proposed. The algorithm divides the task of license plate recognition into two steps: first, the license plate number and the state name are located, and then the regions are recognized. On the basis of YOLO v3, the feature extraction network is redesigned. Combined with the depthwise separable convolution and attention mechanism, a lightweight object detection network is proposed to locate license plate number and state name. For the license plate number, the Convolutional Recurrent Neural Network (CRNN) is used to recognize the license plate number, and transfer learning is introduced to solve the problem of insufficient data in license plate number training set. For the state names, ResNet-50 is used for classification model. Finally, the feasibility of the algorithm is verified by the experiment.

The wireless transmission of home area networks contributes to the vulnerabilities of smart homes. As a result, smart homes are vulnerable to malicious attacks like eavesdropping. To secure the transmissions, secret keys should be established for smart home devices. In practical smart home applications, smart home devices might be resource-constrained devices. Thus, the lightweight key establishment schemes are preferred. Typically, lightweight physical layer key extraction schemes can be employed by the smart home devices. However, the key generation rate of the schemes is low. To improve the key generation rate, in this paper we propose an adaptive physical layer key extraction scheme for smart homes by making use of the Received Signal Strength (RSS). Specifically, in our scheme, two smart home devices collect the RSS measurements by probing with each other. Then, the collected measurements are quantized by running the proposed Self-adaptive Lossless Quantization algorithm. Completing these operations, the two smart home devices can obtain the secret key. In our scheme, we design the self-adaptive lossless quantization algorithm to improve the key generation rate. To show the practicality of the new scheme, we implement it using the Ralink WiFi cards. Additionally, we analyse the performance of our scheme and compare it with that of other related works.

The characteristics of wireless transmission make the smart homes become vulnerable to kinds of malicious attacks, such as eavesdropping. To ensure the security of home area networks, cryptographic keys need to be established for smart home devices. Specifically, the lightweight physical layer key extraction schemes can be implemented. In practice, however, the key generation rate of the state-of-the-art schemes is low. To improve the rate, in this paper we propose an adaptive secret key establishment scheme for smart homes using the Received Signal Strength (RSS) measurements. Two smart home devices can adaptively quantize the collected RSS measurements and obtain the secret key. To illustrate the practicality of our scheme, we experimentally implement it using the Ralink WiFi cards based on the RT2870 chipset. In addition, we evaluate the randomness of the generated key by conducting the NIST randomness test experiment.

The vibration of vehicle is most governed by the load generated of the road roughness, which can affect comfort of vehicle and cause fatigue damage of the vehicle suspension. So knowledge of the load is very important for vehicle control systems to enhance vehicle stability and safety. During the process of the estimation, noise affects the identification accuracy, and maybe cause divergence. The cubature Kalman filter (CKF) has good accuracy performance, numerical stability and computational costs. So this paper presented a new methodology based on CKF and a recursive least-squares algorithm for estimating wheel-road vertical load. The state equations and measurement equations were established according to the second order vibration system, and RK4 was employed to discretize the continuous-time equations. The CKF was used to calculate the residual innovation sequences and the residual innovation sequences were used to calculate the vertical load. To verify the effectiveness of the identification method, numerical simulations of the five degrees of freedom vehicle vibration system subjected to white noises and four types of forces were employed. Simulation results validated and proved the feasibility of this approach.

How to achieve continuous, reliable and accurate positioning performance using low-cost sensors is one of the main challenges for aviation navigation system. Global Positioning System (GPS) can provide the primary means of navigation in a number of aviation navigation applications (e.g., manned and unmanned aircraft vehicle, airport ground vehicle). However, GPS signal deteriorations typically occur due to aircraft itself during maneuvering, ionospheric scintillation, Doppler shift, multipath and so on. Thus, there is a need to research GPS augmentation strategies which can be used in the Communication, Navigation, Surveillance/Air Traffic Management. GPS integration with Inertial Navigation system (INS) is one of the key strategies. But once GPS signal outages, the integrated navigation system works in pure INS, and positioning accuracy deteriorates with time. When using low cost GPS/INS integration, a primary problem is the rapid performance deteriorate during GPS outages. To provide continuous, accurate and reliable positioning information in aviation, discrete grey prediction model (DGPM) aided fusion methodology is proposed. The DGPM provides pseudo-GPS position information for INS during GPS outages. The mathematical model of integrated navigation system is established, including INS error equations, Kalman filter and DGPM. The model works in the update mode when there is no GPS failure, whereas it switches to the prediction mode in case of GPS outages. To verify the feasibility and effectiveness of the proposed methodology, real road test is performed. The comparison results show that accuracy of longitude and latitude are improved by more than 80% and 70%, respectively. The DGPM can effectively provide position corrections for standalone INS during GPS outages.

Various wireless communication technologies have been developed and deployed because of the increasing access requirements. As a result, it brings a great challenge for designing seamless handover authentication protocols in wireless networks, especially in ensuring security and efficiency. The innocent users in wireless networks hope that the Mobile Internet Service Provider can not only provide efficient Internet access, but also protect their privacy. To provide trust and privacy preserving services, in this paper, we propose a new handover authentication protocol for wireless networks. Specifically, the new protocol provides user anonymity and untraceability, and it achieves high efficiency. Compared with other handover authentication protocols, our proposed mechanism achieves outstanding features of security and efficiency.

The T-style discontinuous micro strip lines is a special configuration in the layout of printed circuit boards (PCBs). In this work, the electromagnetic field distribution around micro strip line and the signal reflection characteristics of the transition section are simulated by using the finite-deference time-domain method (FDTD), a powerful tool for electromagnetic simulation. The T-style micro strip lines with different transition shapes are modeled and simulated respectively and the obtained results show that they have various effects on the transmitted signals with different frequencies, especially in the high frequency range. The results are helpful for guiding the design of traces in PCBs.

The nature of wireless transmission leads to vulnerabilities to many malicious activities, and communication in wireless mesh networks (WMNs) must be protected by proper security measures. This paper focuses on symmetric pair wise key establishment and presents a new matrix-based pair wise key establishment scheme for mesh clients. In WMNs, mesh routers are much more powerful than mesh clients, both in communication and computation. By taking advantage of this heterogeneity, our new scheme delegates energy-consuming operations to mesh routers when establishing pair wise keys for mesh clients. Additionally, neighbor mesh clients in our scheme can directly establish pair wise keys with significantly reduced communication and storage costs, due to the use of both pre and post deployment knowledge.

Due to the nature of wireless transmission, communication in wireless mesh networks (WMNs) is vulnerable to many adversarial activities including eavesdropping. Pair-wise key establishment is one of the fundamental issues in securing WMNs. This paper presents a new matrix-based pairwise key establishment scheme for mesh clients. Our design is motivated by the fact that in WMNs, mesh routers are more powerful than mesh clients, both in computation and communication. By exploiting this heterogeneity, expensive operations can be delegated to mesh routers, which help alleviate the overhead of mesh clients during key establishment. The new scheme possesses two desirable features: (1) Neighbor mesh clients can directly establish pairwise keys; and (2) Communication and storage costs at mesh clients are significantly reduced.

Software as a Service (SaaS) provides a useful and convenient way for cloud users to enjoy cloud service, but security problems have caused great influence on the development and popularization of SaaS. As a commercial model, SaaS involves different roles of participants who could be dishonest and malicious. This paper presents a security protocol to address several security issues in SaaS and protect the rights and interests of all participants. Our design is based on identity-based proxy signatures from pairings. The analysis shows that the presented protocol can effectively strengthen the security of SaaS in cloud computing.