|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | 基于区块链的5G物联网数据共享方案显示文摘海量的物联网数据拥有巨大价值,而现有基于云的数据共享机制,面临单点故障、内部泄露等问题,无法确保用户数据的安全共享。为实现高效可信的数据共享,利用区块链技术,提出了基于区块链的5G物联网数据共享方案。该方案首先设计了数据共享框架和数据共享流程;然后基于闪电网络方案,提出了面向物联网数据共享的链下交易机制。实验分析表明,基于区块链的5G物联网数据共享方案具有较强的抗攻击能力;基于闪电网络的交易机制,能够大幅提高交易吞吐量、降低交易时延。 | 乔康 游伟 王领伟 汤红波 | 2020 | 网络与信息安全学报2020,6,4: | 8 |
| 2 | HTDet:A Clustering Method Using Information Entropy for Hardware Trojan Detection显示文摘Hardware Trojans(HTs)have drawn increasing attention in both academia and industry because of their significant potential threat.In this paper,we propose HTDet,a novel HT detection method using information entropybased clustering.To maintain high concealment,HTs are usually inserted in the regions with low controllability and low observability,which will result in that Trojan logics have extremely low transitions during the simulation.This implies that the regions with the low transitions will provide much more abundant and more important information for HT detection.The HTDet applies information theory technology and a density-based clustering algorithm called Density-Based Spatial Clustering of Applications with Noise(DBSCAN)to detect all suspicious Trojan logics in the circuit under detection.The DBSCAN is an unsupervised learning algorithm,that can improve the applicability of HTDet.In addition,we develop a heuristic test pattern generation method using mutual information to increase the transitions of suspicious Trojan logics.Experiments on circuit benchmarks demonstrate the effectiveness of HTDet. | Renjie Lu Haihua Shen Zhihua Feng Huawei Li Wei Zhao Xiaowei Li | 2021 | Tsinghua Science and Technology2021,26,1: | 4 |
| 3 | EVchain: An Anonymous Blockchain-Based System for Charging–Connected Electric Vehicles显示文摘Purchases of electric vehicles have been increasing in recent years. These vehicles differ from traditional fossil-fuel-based vehicles especially in the time consumed to keep them running. Electric-Vehicle-charging Service Providers(EVSPs) must arrange reasonable charging times for users in advance. Most EVSP services are based on third-party platforms, but reliance on third-party platforms creates a lack of security, leaving users vulnerable to attacks and user-privacy leakages. In this paper, we propose an anonymous blockchain-based system for charging-connected electric vehicles that eliminates third-party platforms through blockchain technology and the establishment of a multi-party security system between electric vehicles and EVSPs. In our proposed system, digital certificates are obtained by completing distributed Public Key Infrastructure(distributed-PKI) identity registration,with the user registration kept separate from the verification process, which eliminates dependence on the EVSP for information security. In the verification process, we adopt smart contracts to solve problems associated with centralized verification and opaque services. Furthermore, we utilize zero-knowledge proof and ring-signature superposition to realize completely anonymous verification, which ensures undeniability and unforgeability with no detriment to anonymity. The evaluation results show that the user anonymity, information authenticity, and system security of our system fulfill the necessary requirements. | Shiyuan Xu Xue Chen Yunhua He | 2021 | Tsinghua Science and Technology2021,26,6: | 2 |
| 4 | Dataflow Management in the Internet of Things: Sensing,Control, and Security显示文摘The pervasiveness of the smart Internet of Things(IoTs) enables many electric sensors and devices to be connected and generates a large amount of dataflow. Compared with traditional big data, the streaming dataflow is faced with representative challenges, such as high speed, strong variability, rough continuity, and demanding timeliness, which pose severe tests of its efficient management. In this paper, we provide an overall review of IoT dataflow management. We first analyze the key challenges faced with IoT dataflow and initially overview the related techniques in dataflow management, spanning dataflow sensing, mining, control, security, privacy protection,etc. Then, we illustrate and compare representative tools or platforms for IoT dataflow management. In addition,promising application scenarios, such as smart cities, smart transportation, and smart manufacturing, are elaborated,which will provide significant guidance for further research. The management of IoT dataflow is also an important area, which merits in-depth discussions and further study. | Dawei Wei Huansheng Ning Feifei Shi Yueliang Wan Jiabo Xu Shunkun Yang Li Zhu | 2021 | Tsinghua Science and Technology2021,26,6: | 2 |