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International Conference on Computer and Communications (ICCC)

作者： Kun Guo Dongbin Wang Hui Zhi Yibo Gao Tao Zhang Tiejun Lv Yueming Lu Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China National Engineering Laboratory for Mobile Network Beijing University of Posts and Telecommunications Beijing China TravelSky Technology Limited Beijing China Cyberspace Security Research Center Peng Cheng Laboratory Beijing University of Posts and Telecommunications Beijing China China Academy of Launch Vehicle Technology Beijing China

ISBN: (纸本)9781665409513

Existing routing algorithms in Flying Ad-Hoc Net- works (FANETs) lack the optimization consideration of destruction resistance cost caused by routing recovery when some nodes fail suddenly. In this paper, we propose a hybrid routing algorithm based on destruction resistance cost and reliability. Based on the real-time network topology and network state, the algorithm can provide a multi-parameters-based routing path with low destruction resistance cost for communication transmission. It can ensure that the main routing path can be quickly recovered after interruption and reduce the process of discovering new routing paths. We have constructed a variety of simulation scenarios to analyze the proposed algorithm and the existing algorithms. The simulation results show that the pro- posed algorithm has good performance in reducing destruction resistance cost.

关键词： Resistance Analytical models Costs Computer network reliability Simulation Routing Real-time systems

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Research on the Current State of Privacy Risks in Children’s Mobile Applications

Research on the Current State of Privacy Risks in Children’...

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Computer technology and Information Science (ISCTIS), International Symposium on

作者： Xinrui Geng Tao Liu Chong Shang Jianxiang Chen Yueran Lu Yan Zhang Lifeng Wang School of AI and Advanced Computing Xi’an Jiaotong-Liverpool University Suzhou China Key Laboratory of Mobile Application Innovation and Governance Technology MIIT Beijing China Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Agricultural Engineering Shanxi Agricultural University China School of Software Engineering Tianjin Normal University Tianjin China Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences Beijing China Shandong Yeda Smart City Operation Technology Co. Ltd. Shandong China

ISBN: (数字)9798350354560

ISBN: (纸本)9798350354577

In the digital age, children increasingly access a vast world of information through mobile applications. Despite global regulations and protective measures by app stores, privacy breaches in these apps persist. This study investigates privacy issues and threats in children’s mobile applications by comparing APKs and legal provisions across different countries. It examines 70 representative children’s apps from China, Europe, the U.S., and Japan through static code analysis and dynamic runtime testing. Using a mixed-methods approach, the research identifies integrated third-party services, data transmission protocols, permission requests, and conducts code audits to assess privacy compliance. It also simulates real usage scenarios to track data flow and detect unauthorized data collection and sharing practices. Furthermore, the study compares national privacy laws, focusing on data minimization, parental consent mechanisms, data encryption, and storage duration regulations. The goal is to provide empirical evidence and recommendations for optimizing global children’s online privacy protection policies.

关键词： Pediatrics Data privacy Codes Law Europe Privacy breach Regulation Mobile applications Protection Testing

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security and privacy for healthcare blockchains

arXiv

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arXiv 2021年

作者： Zhang, Rui Xue, Rui Liu, Ling State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China College of Computing Georgia Institute of Technology AtlantaGA30332 United States School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China

Healthcare blockchains provide an innovative way to store healthcare information, execute healthcare transactions, and build trust for healthcare data sharing and data integration in a decentralized open healthcare network environment. Although the healthcare blockchain technology has attracted broad interests and attention in industry, government and academia, the security and privacy concerns remain the focus of debate when deploying blockchains for information sharing in the healthcare sector from business operation to research collaboration. This paper focuses on the security and privacy requirements for medical data sharing using blockchain, and provides a comprehensive analysis of the security and privacy risks and requirements, accompanied by technical solution techniques and strategies. First, we discuss the security and privacy requirements and attributes required for electronic medical data sharing by deploying the healthcare blockchain. Second, we categorize existing efforts into three reference blockchain usage scenarios for electronic medical data sharing, and discuss the technologies for implementing these security and privacy properties in the three categories of usage scenarios for healthcare blockchain, such as anonymous signatures, attribute-based encryption, zero-knowledge proofs, verification techniques for smart contract security. Finally, we discuss other potential blockchain application scenarios in healthcare sector. We conjecture that this survey will help healthcare professionals, decision makers, and healthcare service developers to gain technical and intuitive insights into the security and privacy of healthcare blockchains in terms of concepts, risks, requirements, development and deployment technologies and systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Blockchain

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Privacy-Preserving Multi-keyword Search over Outsourced Data for Resource-Constrained Devices 2nd

Privacy-Preserving Multi-keyword Search over Outsourced Data...

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2nd International Conference on Blockchain and Trustworthy Systems, Blocksys 2020

作者： Liu, Lin-Gang Zhao, Meng Ding, Yong Wang, Yujue Deng, Hua Wang, Huiyong Guangxi Key Laboratory of Cryptography and Information Security School of Computer Science and Information Security Guilin University of Electronic Technology Guilin541004 China School of Mechanical and Electrical Engineering Guilin University of Electronic Technology Guilin541004 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin541004 China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen518055 China

ISBN: (纸本)9789811592126

With the rapid development of cloud computing, a variety of cloud-based applications have been developed. Since cloud computing has the features of high capacity and flexible computing, more and more users are motivated to outsource their data to the cloud server for economic savings. Users are able to search over outsourced data according to some keywords with the help of the cloud server. During data searching, the confidentiality of the relevant data could be compromised since the keywords may contain some sensitive information. However, existing privacy-preserving keyword search proposals have high computation complexity, which are not applicable to IoT-related scenarios. That is, the data processing and search trapdoor generation procedures require the users to take resource-intensive computations, e.g., high-dimensional matrix operations, which are unaffordable by resource-constrained devices. To address this issue, we propose a light-weight privacy-preserving multi-keyword search scheme. The security and performance analyses demonstrate that our scheme outperforms existing solutions and is practical in applications. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Imperceptible diffusion modification for facial privacy protection

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Neurocomputing 2025年 649卷

作者： Jia Li Junhao Dong Jianhuang Lai Xiaohua Xie School of Computer Science and Engineering Sun Yat-sen University Guangzhou China College of Computing and Data Science Nanyang Technological University Singapore Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing (Sun Yat-sen University) Ministry of Education Guangzhou China

The remarkable success of Face Recognition (FR) systems has raised significant privacy concerns, particularly the potential for unauthorized tracking of individuals on social media. To mitigate these risks, various adversarial attack methods have been proposed to protect individuals from unauthorized identification by FR systems. In this work, we propose a novel A dversarial F ace generation method via D iffusion M odification (AFDM), designed for imperceptible and transferable attacks against FR systems. The AFDM operates in the diffusion latent space of the face image, leveraging DDIM inversion and the DDIM process to achieve precise modifications. To ensure high visual fidelity, we propose a self-attention structure loss and a perceptual loss, effectively constraining the extent of diffusion-based alterations. Additionally, to enhance transferability, we introduce a face attribute loss that aligns the attribute embeddings of the protected face with those of the target face. Extensive experiments demonstrate that the proposed AFDM achieves state-of-the-art performance in attacking various FR models, with an average Protect Success Rate (PSR) of 93.32% on the CeleA-HQ and LADN datasets, while maintaining a more natural-looking protected face image with an FID score of 22.96. Through our systematic analysis, we justify the efficacy and generality of the proposed method.

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Constructing benchmarks for supporting explainable evaluations of static application security testing tools 13

Constructing benchmarks for supporting explainable evaluatio...

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13th International Symposium on Theoretical Aspects of Software Engineering, TASE 2019

作者： Hao, Gaojian Li, Feng Huo, Wei Sun, Qing Wang, Wei Li, Xinhua Zou, Wei Institute of Information Engineering Chinese Academy of Sciences China Key Laboratory of Network Assessment Technology Chinese Academy of Sciences Beijing Key Laboratory of Network Security and Protection Technology China School of Cyber Security University of Chinese Academy of Sciences China

ISBN: (纸本)9781728133423

When evaluating Static Application security Testing (SAST) tools, benchmarks based on real-world softwares are considered more representative than synthetic micro benchmarks. Generated from real-world software, the test cases in such kind of benchmarks usually contain multiple syntactic features which affect the vulnerability detection results reflecting SAST tools' capabilities in real-world settings. However, most existing benchmarks based on real-world software pay little attention to these syntactic features so that only limited information about the capabilities of SAST tools can be obtained from the evaluation results. In this paper, we provide a method of constructing benchmarks and evaluating SAST tools, which leverages the syntactic features to support the evaluation to be more explainable. To demonstrate the effectiveness, we applied our method to the benchmark built by Misha Zitser et al., generated 10 groups of test cases, and evaluated 2 SAST tools with them. The result shows that, with the benchmark constructed by our method, the evaluation could be more explainable which helps us to gain more information about the SAST tools' capabilities of vulnerability detection. © 2019 IEEE.

关键词： Software testing

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AndroCreme: Unseen Android Malware Detection Based on Inductive Conformal Learning

AndroCreme: Unseen Android Malware Detection Based on Induct...

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IEEE International Conference on Trust, security and Privacy in computing and Communications (TrustCom)

作者： Gang Zhang Hao Li Zhenxiang Chen Lizhi Peng Yuhui Zhu Chuan Zhao Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan China School of Information Science and Engineering University of Jinan China School of cyber science and technology Shandong University China

ISBN: (纸本)9781665416597

Android platform is facing serious malware threats due to its popularity, as evidenced by the drastic increase on the number of mobile malware families and variants in recent years. Detecting malware variants and zero-day malware is a critical challenge that must be addressed to protect mobile devices against malware attacks. In this study, we present AndroCreme, a novel network intrusion detection system (NIDS) that can identify unseen malware by analyzing the network behavior of Android malware. To address the temporal bias issue in NIDS, we propose a method for rapid iterative update of the model based on data selection and data size limitation. The selection of effective data is carried out by induction and conformal technology, and the data scale is controlled by the method of time window and data cycle selection. To further achieve fast training speed and high efficiency, we leverage a gradient boosting framework that uses a tree-based learning algorithm, namely, LightGBM, as the meta predictor. We evaluate the performance of AndroCreme over 400K real-world network flows, which are collected from over 30K Android benignware and 21K malware applications. The experimental results show that, compared with the retraining method using all data, AndroCreme requires only a small amount of datareduce more than 3x to obtain better detection performance, which effectively solves the temporal bias.

关键词： Training Privacy network intrusion detection Prediction algorithms Malware Data models Stability analysis

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Assessing Carbon Emission Mitigation Potential of Greening Vegetation and Distributed Photovoltaic Along Highway:A Case in Guangdong, China

SSRN

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SSRN 2024年

作者： Zhang, Haitao Zhang, Xinying Liu, Nieyangzi Yu, Qian Fu, Zishi Wang, Yuanqing Engineering Research Center of Road Transportation Decarbonization Ministry of Education Shaanxi Province Xi’an710064 China College of Transportation Engineering Chang’an University Shaanxi Province Xi’an710064 China Engineering Research Center of Road Transportation Decarbonization Ministry of Education Chang’an University Shaanxi Province Xi’an710064 China Key Laboratory of Transport Industry of Management Control and Cycle Repair Technology for Traffic Network Facilities in Ecological Security Barrier Area Shaanxi Province Xi’an710064 China Guangzhou Lvzhineng Technology Co. Ltd. Guangdong Province Guangzhou510700 China

The promotion of distributed photovoltaics (PV) along highways helps to advance the clean energy transition in the transportation industry. By combining road space photovoltaic systems (RSPV) and road space vegetation (RSV), the RSPV-RSV system makes it possible for multifunctional use of road space, giving both PV and greening benefits. This study finds and analyzes the potential for PV generation and carbon sequestration in highway greening zones by combining data from highway construction projects, solar radiation, and numerical models. In addition, three spatial use scenarios were developed: Scenario 1 (S1): no road PV facilities installed;Scenario 2 (S2): greening plants prioritized;and Scenario 3 (S3): PV generation facilities prioritized. A new highway in Guangdong Province is selected as an example. The assessment indicates that the available greening area is 240.87 hectares. Under S1, the first-year carbon storage of RSV amounts to 2,296.23 t, while the net carbon sequestration from trees can reach 8,893.97 t. Additionally, by year 9, the carbon storage of the RSV will equal the carbon emissions produced during the analysis period. Total electricity generation from RSPV in S2 and S3 is less than the highway system's energy consumption demand, with S3 reaching the highest self-sufficiency rate (5.5%). However, S2 has the highest total carbon storage in the RSV system. The results contribute to a better knowledge of the potential carbon emission linkages between roadside vegetation and highway distributed PV systems, which will help to build feasible strategies for integrating road infrastructure and clean energy development. © 2024, The Authors. All rights reserved.

关键词： Carbon sequestration

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Concept-aware denoising graph neural network for micro-video recommendation

arXiv

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arXiv 2021年

作者： Liu, Yiyu Liu, Qian Tian, Yu Wang, Changping Niu, Yanan Song, Yang Li, Chenliang Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University Wuhan430072 China Kuaishou Technology Co. Ltd. Beijing10010 China

Recently, micro-video sharing platforms such as Kuaishou and Tiktok have become a major source of information for people’s lives. Thanks to the large traffic volume, short video lifespan and streaming fashion of these services, it has become more and more pressing to improve the existing recommender systems to accommodate these challenges in a cost-effective way. In this paper, we propose a novel concept-aware denoising graph neural network (named Conde) for micro-video recommendation. Conde consists of a three-phase graph convolution process to derive user and micro-video representations: warm-up propagation, graph denoising and preference refinement. A heterogeneous tripartite graph is constructed by connecting user nodes with video nodes, and video nodes with associated concept nodes, extracted from captions and comments of the videos. To address the noisy information in the graph, we introduce a user-oriented graph denoising phase to extract a subgraph which can better reflect the user’s preference. Despite the main focus of micro-video recommendation in this paper, we also show that our method can be generalized to other types of tasks. Therefore, we also conduct empirical studies on a well-known public E-commerce dataset. The experimental results suggest that the proposed Conde achieves significantly better recommendation performance than the existing state-of-the-art solutions. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost effectiveness

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Optimal logistics transportation and route planning based on fpga processor real-time system and machine learning

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Microprocessors and Microsystems 2021年 80卷 103621-103621页

作者： Dai, Xuezhen Chen, Meiqi Zhou, Yanan College of Transportation Engineering Chang'an University Xi'anShaanxi710064 China Key Laboratory of Transport Industry of Management Control and Cycle Repair Technology for Traffic Network Facilities in Ecological Security Barrier Area Chang'an University Xi’ anShaanxi710064 China

The shared bus's development requirements, relief of traffic congestion in urban areas, and improved utilization of the road resources providing the transport mode of the excellent user experience neotype are very urgent. To predict precise travel needs, the key for planning a dynamic routing lie a lie of the shared bus implementation. However, the shared bus data's sparse and high volatility will require a lot of resistance to predict travel accurately. Based on the user experience, very different from the traditional public transportation that is far more challenging to the relatively high number of optimization goals is because passengers of the shared bus route planning and shared bus route planning. This article, based on the shared bus data from different audiences sources, travel demand prediction and dynamic route planning in "the last mile", and a two-step process that consists of the shared bus dynamic routing (sub-bus), proposed and your scene. First of all, such traffic, time, week, location, and five of the prediction function such as a bus, to analyze residents' travel behavior to prepare the travel demand based on them precisely the machine learning model used to predict. Secondly, dynamically and predict the results of multiple operations bus optimal routing, designed to generate a fixed based on the shared bus destinations' operating characteristics, a dynamic programming algorithm wants below. Several experiments, based on the shared subway shuttle bus of evidence that people of the data and the reality has been purchased, the sub-bus is better than the method of dynamic route planning, etc. for the scene of such a "last mile". © 2020

关键词： Machine learning

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