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Due to the limited computation resources and lifetime of user equipment, we study the energy minimization problem for computation offloading in cognitive radio networks (CRNs). This work proposes a device-to-device (D2D)-assisted computation offloading scheme for non-orthogonal multiple access (NOMA)-enabled CRNs. Specifically, the secondary user (SU) can provide computation resources for the primary user (PU) to access the spectrum owned by the PU. With the constraints of task deadline and maximum transmit power, offloading decision and power control of PU and SU are optimized to minimize the energy consumption of CRNs. The solution is obtained by deploying the block coordinate descent method and successive convex approximation. Simulation results show the improvement of the proposed scheme in terms of energy consumption and computing performance compared with other methods. [ABSTRACT FROM AUTHOR]

Abstract Transmissible cyber threats have become one of the most serious security issues in cyberspace. Many techniques have been proposed to model, simulate and identify threats' sources and their propagation in large-scale distributed networks. Most techniques are based on the analysis of real networks dataset that contains sensitive information. Traditional in-memory analysis of these dataset often causes data leakage due to system vulnerabilities. If the dataset itself is compromised by adversaries, this threat cost would be even higher than the threat being analysed. In this paper, we propose a new distributed shielded execution framework (Disef) for cyber threats analysis. The Disef framework enables efficient distributed analysis of network dataset while achieves security guarantees of data confidentiality and integrity. In-memory dataset is protected by using a new encrypted key–value format and could be efficiently transferred into Intel SGX enabled enclaves for shielded execution. Our experimental results showed that the proposed framework supports secure in-memory analysis of large network dataset and has comparable performance with systems that have no confidentiality and integrity guarantees. Highlights • A distributed shielded execution framework for network cyber threats analysis is presented. • A brief secure partition mechanism is proposed to decouple secure and normal spaces. • A context-switch secure interface is proposed to reduce Iago attacks. • New key–value encryption operations are integrated to prevent rollback and replay attacks. [ABSTRACT FROM AUTHOR]

The fault-tolerance property in most cloud storage systems are designed within the scale of a single datacenter. The single datacenter as a whole may be unreachable or crashed due to severe problems, such as broken network links, power supply interruptions, and natural disasters, etc. Therefore, the design of an effective cross-datacenter fault-tolerant storage system is important to protect data security in the cloud. However, building a cross-datacenter fault-tolerant system faces great challenges, such as high latency, low throughput, high costs of bandwidth resources between datacenters. In this paper, we propose a practical cross-datacenter fault-tolerant (CDFT) algorithm in the cloud storage system. Our fault-tolerant algorithm design considers the difficult tradeoffs among fault tolerance, latency, throughput, network and storage costs. We propose the Domain Fault Codes (DFC) and the topology-aware scheduling techniques, which can tolerate the whole datacenter breakdown. We implemented the DFC-CDFT algorithm in a prototype cloud storage system. The experimental results showed that the proposed DFC-CDFT algorithm can effectively recover data blocks from the single datacenter failure while achieves low storage and bandwidth costs. [ABSTRACT FROM AUTHOR]

Multicore systems are widely deployed in both the embedded and the high end computing infrastructures. However, traditional virtualization systems can not effectively isolate shared micro architectural resources among virtual machines (VMs) running on multicore systems. CPU and memory intensive VMs contending for these resources will lead to serious performance interference, which makes virtualization systems less efficient and VM performance less stable. In this paper, we propose a contention-aware performance prediction model on the virtualized multicore systems to quantify the performance degradation of VMs. First, we identify the performance interference factors and design synthetic micro-benchmarks to obtain VM’s contention sensitivity and intensity features that are correlated with VM performance degradation. Second, based on the contention features, we build VM performance prediction model using machine learning techniques to quantify the precise levels of performance degradation. The proposed model can be used to optimize VM performance on multicore systems. Our experimental results show that the performance prediction model achieves high accuracy and the mean absolute error is 2.83%. [ABSTRACT FROM AUTHOR]

The article presents a study on the expression of CD109 in endothelial cells of cutaneous cavernous haemangioma. Topics discussed include the medical threat posed by cutaneous haemangioma, its emergence due to deregulated proliferation and differentiation of endothelial cells, and origins of squamous cell carcinomas observed in elevated CD109 expression. The pattern of CD109 expression is discussed.

With the rapid development of Internet of Things technology and the promotion of embedded devices' computation performance, smart devices are probably open to security threats and attacks while connecting with rich and novel Internet. Attracting lots of attention in embedded system security community recently, Trusted Execution Environment (TEE), allows for the execution of arbitrary code within environments completely isolated from the rest of a system. However, existing memory protection methods in a TEE are inadequate. In general, the software-based formal methods are not practical and the hardware-based implementation approaches lack of theoretical proof. To address the memory isolation and protection problems in TEE, in this paper, we propose a practical memory integrity protection method on an ARM-based platform, called MIPE, to defend against security threats including kernel data attacks and direct memory access attacks. MIPE utilizes TrustZone technique to create a isolated execution environment, which can protect the sensitive code and data against attacks. To present the integrity protection strategies, we provide the design of MIPE using B method, which is a practical formal method. We also implement MIPE on the Xilinx Zynq ZC702 evaluation board. The evaluation results show that the automatic proof rate of machines using B method is about 78.32%, and the proposed method is effective and feasible in terms of both load time and overhead. [ABSTRACT FROM AUTHOR]

Semi-interpenetrating polymer networks (Semi-IPNs) based on fluorine-containing polyacrylate and epoxy resin were synthesized by the simultaneous polymerization of fluorine-containing acrylate and epoxy resin. Fourier transform infrared (FTIR) spectrometry and X-ray photoelectron spectroscopy (XPS) analyses proved that the fluorine-containing groups have been introduced into Semi-IPNs successfully. In addition, XPS analysis intuitively showed that the fluorine content of the film-air interface of the interpenetrating fluorine-containing polyacrylate and epoxy resin networks (FPAER-SIPNs) film was much higher than that of the film-glass interface. It is noted that the introduction of fluorine-containing groups significantly improved the hydrophobic property of polymer networks. Moreover, when the fluorine content increased, the contact angle of water on FPAER-SIPNs film was increased obviously and the water uptake was decreased gradually. These results indicated that introducing fluorine-containing groups to SIPNs has potential advantage for improving the surface properties of epoxy resin. [ABSTRACT FROM AUTHOR]