2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)最新文献

IDROP: Intelligently detecting Return-Oriented Programming using real-time execution flow and LSTM IDROP:使用实时执行流和LSTM智能检测面向返回的编程

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/TrustCom56396.2022.00033

Jie Li, Weina Niu, Ran Yan, Zhiqin Duan, Beibei Li, Xiaosong Zhang

{"title":"IDROP: Intelligently detecting Return-Oriented Programming using real-time execution flow and LSTM","authors":"Jie Li, Weina Niu, Ran Yan, Zhiqin Duan, Beibei Li, Xiaosong Zhang","doi":"10.1109/TrustCom56396.2022.00033","DOIUrl":"https://doi.org/10.1109/TrustCom56396.2022.00033","url":null,"abstract":"Return-Oriented Programming (ROP) has become one of the most widely used attack techniques for software vulnerability exploitation. Existing ROP detection methods fall into two types: hardware-based methods and software-based methods. The former is strongly dependent on specific hardware architectures and difficult to deploy. Although the latter can alleviate these problems, limited by the selection of features and thresholds, it cannot effectively discover neither variant ROP nor delayed ROP. In this work, we propose an intelligent detection method at runtime and implement the corresponding prototype system, IDROP, which uses real-time execution flow and LSTM to discovery ROP and its variants. Specifically, IDROP analyzes the differences between program execution flows that are independent of the ROP feature thresholds. Firstly, the Aspect Oriented Programming (AOP) is utilized to instrument the tested program, and the sliding window mechanism is applied to screen out suspicious program execution flow snapshots. Then, these suspicious execution flow snapshots are vectorized through data representation techniques. Finally, we build and train an LSTM model to discover ROP. Furthermore, we evaluate the performance of IDROP on a dataset consisting of 6000+ samples. The experimental results show that IDROP is effective in detecting ROP attacks, variant ROP and delayed ROP with an accuracy of 98%, 93% and 80%, respectively. In addition, IDROP has negligible space overhead and low performance overhead, which is similar to that of only using Pin for detection (about additional 2.5 times the program execution time before instrumentation).","PeriodicalId":276379,"journal":{"name":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127259245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on User Complaint Problem Location and Complaint Early Warning Stragegy Based on Big Data Analysis 基于大数据分析的用户投诉问题定位与投诉预警策略研究

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/trustcom56396.2022.00214

Jie Gao, Lixia Liu, Zhang Tao, Shenghao Jia, Chuntao Song, Lexi Xu, Yang Wu, Bei Li, Yunyun Wang, Xinjie Hou

{"title":"Research on User Complaint Problem Location and Complaint Early Warning Stragegy Based on Big Data Analysis","authors":"Jie Gao, Lixia Liu, Zhang Tao, Shenghao Jia, Chuntao Song, Lexi Xu, Yang Wu, Bei Li, Yunyun Wang, Xinjie Hou","doi":"10.1109/trustcom56396.2022.00214","DOIUrl":"https://doi.org/10.1109/trustcom56396.2022.00214","url":null,"abstract":"With the rapid development of mobile network, the use of mobile phones has become popular. People use mobile phones every day to surf the Internet, shop, socialize, work, etc. In the process of using mobile web services, users may be dissatisfied with the service perception, such as voice connectivity, Internet access, Slow Internet access and other common problems. If the customer is not satisfied with the communication service, the customer can usually complain about the quality of the communication service, so the frequency of the customer complaint has become an important evaluation index for the management of the operator. The quantity and frequency of customers ‘complaints about telecommunication service are increasing gradually, which brings challenges to the service quality and efficiency of telecommunication operators. This paper presents a methodology for customer complaints. The analysis system is based on the data of Horizontal pull- through, combined with big data analysis model, focus on the user’s response to the Internet slow, Internet access, voice access issues such as real-time positioning analysis, to provide customers with the first time solutions.","PeriodicalId":276379,"journal":{"name":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114167967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Improved Zero-Knowledge Proofs for Commitments from Learning Parity with Noise 基于噪声学习奇偶的承诺改进零知识证明

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/TrustCom56396.2022.00064

Mengfan Wang, Guifang Huang, Hongmin Gao, Lei Hu

{"title":"Improved Zero-Knowledge Proofs for Commitments from Learning Parity with Noise","authors":"Mengfan Wang, Guifang Huang, Hongmin Gao, Lei Hu","doi":"10.1109/TrustCom56396.2022.00064","DOIUrl":"https://doi.org/10.1109/TrustCom56396.2022.00064","url":null,"abstract":"Zero-knowledge proof for any relation amongst committed values is crucial and widely applicable in the design of high level cryptographic schemes, especially in privacy-preserving protocols. Besides quantum resistance, efficiency is what we are most concerned about, including asymptotic efficiency and concrete efficiency. Jain et al. proposed a simple string commitment scheme based on the Learning Parity with Noise (LPN) problem (JKPT12), and then designed zero-knowledge proofs for valid opening, linear relation and multiplicative relation of committed values. As a result, they got an efficient zero-knowledge proof for any circuit C, with communication complexity $mathcal{O}(t|C|ell log ell )$, where t is a security parameter measuring soundness and ℓ is the secret length of the LPN problem. In this work, we improve the concrete communication complexity by combining some commitments in JKPT12 together. The proofs of linear relation and multiplicative relation are shortened by (6α + 4)ℓ and (42α+28)ℓ respectively, where ℓ is the size of LPN secret. As a result, the communication cost of the protocol proving arbitrary relation is reduced by a constant level.","PeriodicalId":276379,"journal":{"name":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122171785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Telecom Customer Chum Prediction based on Half Termination Dynamic Label and XGBoost 基于半端动态标签和XGBoost的电信客户忠诚度预测

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/TrustCom56396.2022.00224

Yi Zhang, Fan Zhang, Chuntao Song, Xinzhou Cheng, Chen Cheng, Lexi Xu, Tian Xiao, Bei Li

引用次数: 0

AI based Collaborative Optimization Scheme for Multi-Frequency Heterogeneous 4G/5G Networks 基于AI的多频异构4G/5G网络协同优化方案

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/trustcom56396.2022.00155

Tian Xiao, Guo-Min Xu, Bei Li, Lexi Xu, Xinzhou Cheng, Feibi Lyu, Guanghai Liu, Yi Zhang, Qingqing Zhang

{"title":"AI based Collaborative Optimization Scheme for Multi-Frequency Heterogeneous 4G/5G Networks","authors":"Tian Xiao, Guo-Min Xu, Bei Li, Lexi Xu, Xinzhou Cheng, Feibi Lyu, Guanghai Liu, Yi Zhang, Qingqing Zhang","doi":"10.1109/trustcom56396.2022.00155","DOIUrl":"https://doi.org/10.1109/trustcom56396.2022.00155","url":null,"abstract":"With the continuous expansion of network construction, 4G/5G networks have gradually developed into hybrid multi-frequency heterogeneous networks, while the difficulty of inter-RAT mobility assurance is gradually increasing. Traditional interoperability optimization requires enormous labor costs, and the accuracy is low. This paper proposes an AI-based collaborative optimization scheme under multi-frequency heterogeneous 4G/5G networks based on the XGBoost prediction model and DNN algorithm. It aims to comprehensively improve the performance of different users in multi-frequency heterogeneous 4G/5G networks in terms of 4G/5G neighborhood re-organization and intelligent optimization of 4G/5G interoperability parameters. The results show that the proposed scheme has high accuracy and strong generalization, which is critical in improving user mobility perception under complex network structures. The scheme contributes to the network operators’ efficiency improvement and intelligent transformation process.","PeriodicalId":276379,"journal":{"name":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129878844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TECS: A Trust Model for VANETs Using Eigenvector Centrality and Social Metrics 基于特征向量中心性和社会度量的vanet信任模型

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/TrustCom56396.2022.00016

Yu’ang Zhang, Yujie Song, Yu Wang, Yue Cao, Xuefeng Ren, Fei Yan

{"title":"TECS: A Trust Model for VANETs Using Eigenvector Centrality and Social Metrics","authors":"Yu’ang Zhang, Yujie Song, Yu Wang, Yue Cao, Xuefeng Ren, Fei Yan","doi":"10.1109/TrustCom56396.2022.00016","DOIUrl":"https://doi.org/10.1109/TrustCom56396.2022.00016","url":null,"abstract":"Vehicular Ad Hoc Networks (VANETs) rely heavily on trustworthy message exchanges between vehicles to enhance traffic efficiency and transport safety. Although cryptography-based methods are capable of alleviating threats from unauthenticated attackers, they can not prevent attacks from those legitimate network participants. This paper proposes a trust model to deal with attackers from the latter case, who can tamper with their received messages and deliberately decrease the trust value of benign vehicles. The trust evaluation process is formed by two stages: (i) the local trust evaluation at vehicles and (ii) trust aggregation on Road Side Units (RSUs). In the local trust evaluation stage, vehicles detect attacks and calculate the trust value for others in a distributed manner. Also, the social metrics of vehicles are calculated based on interaction records and trajectories. In the trust aggregation stage, each RSU collects local data from nearby vehicles and derives aggregation weights from the eigenvector centrality of the local trust network and social metrics. Then the RSU broadcasts the aggregated trust value towards vehicles in proximity. These vehicles can thus obtain a more accurate and comprehensive view. Vehicles with trust value below a preset threshold will be considered malicious. Extensive simulations based on the ONE simulator show that the proposed model (TECS) outperforms another benchmark model (IWOT-V) regarding the malicious vehicle detection and the delivery rate of authentic messages.","PeriodicalId":276379,"journal":{"name":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128998542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Flow Attack Strategy based on Critical Links for Cyber-attack 一种基于关键环节的网络攻击流策略

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/TrustCom56396.2022.00126

Jiming Qi, Jiazheng Zhang, Qingxia Liu, Bang Wang

{"title":"A Flow Attack Strategy based on Critical Links for Cyber-attack","authors":"Jiming Qi, Jiazheng Zhang, Qingxia Liu, Bang Wang","doi":"10.1109/TrustCom56396.2022.00126","DOIUrl":"https://doi.org/10.1109/TrustCom56396.2022.00126","url":null,"abstract":"Whether it be congestion control in cities or massive access in the Internet, these dynamic behaviors can be abstracted as flow demand between origin-destination node pairs (OD pairs) in the network. Links in complex systems are with notable heterogeneity, which means the volume of flow varies greatly, resulting in some critical links being more likely to congest under the flow attack, reducing the service capability of the system, and even causing network collapses. To explore how flow dynamics influences the network functionality and stability under congestion, we propose a link-based flow attack strategy that significantly degrades the service capability between OD pairs. In this approach, we first extract the routing paths and score the vulnerability of links between OD pairs, then an attack flow allocation rule based on critical links is designed to efficiently attack the target flow between OD pairs. Experiments on real-world networks show that the proposed strategy can quickly identify critical links and accurately attack the target flow. Besides, the proposed method provides positive and unique insights for defense strategy and network topology optimization.","PeriodicalId":276379,"journal":{"name":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129336432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multidimensional Blockchain Framework For Mobile Internet of Things 面向移动物联网的多维区块链框架

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/TrustCom56396.2022.00129

H. Zangoti, Alex Pissinou Makki, N. Pissinou, A. Shahid, Omar J. Guerra, Joel Rodriguez

{"title":"A Multidimensional Blockchain Framework For Mobile Internet of Things","authors":"H. Zangoti, Alex Pissinou Makki, N. Pissinou, A. Shahid, Omar J. Guerra, Joel Rodriguez","doi":"10.1109/TrustCom56396.2022.00129","DOIUrl":"https://doi.org/10.1109/TrustCom56396.2022.00129","url":null,"abstract":"The adoption of blockchain in the Internet of Things (IoT) has been increasing due to the various benefits that blockchain brings, such as security and privacy. Current blockchain models for mobile IoT assume there are fixed, powerful edge devices capable of providing global communication to all the nodes in the network. However, due to the mobile nature of IoT or network partitioning problems (NPP), nodes can move out of a cell area and split into smaller independent peer-to-peer subnetworks. Existing blockchain structures either do not support the network partitioning problem or have limitations. This paper introduces a multidimensional, graph-based blockchain structure, that utilizes k-dimensional spatiotemporal space, to address the challenges of applying blockchain in mobile networks with limited resources. Experimental results show that a multidimensional blockchain structure can improve scalability and efficiency as the blockchain grows in size, similar to logarithmic growth, and reduce the longest chain length by more than 99.99% compared to the traditional chain-based blockchain structure.","PeriodicalId":276379,"journal":{"name":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124628525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Deceiving Learning-based Sketches to Cause Inaccurate Frequency Estimation 欺骗基于学习的草图导致不准确的频率估计

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/TrustCom56396.2022.00038

Xuyang Jing, Xiaojun Cheng, Zheng Yan, Xian Li

{"title":"Deceiving Learning-based Sketches to Cause Inaccurate Frequency Estimation","authors":"Xuyang Jing, Xiaojun Cheng, Zheng Yan, Xian Li","doi":"10.1109/TrustCom56396.2022.00038","DOIUrl":"https://doi.org/10.1109/TrustCom56396.2022.00038","url":null,"abstract":"Learning-based sketches have been widely studied as an improvement of traditional sketches that achieves high efficiency in terms of both time and space. It uses a learning model to reveal and exploit underlying patterns of input data for helping traditional sketches obtain accurate frequency estimation with memory efficient. However, recent studies only focus on the performance improvement of learning-based sketches and pay little attention to security. The potential security problems can be easily exploited by an adversary to make learning-based sketches inaccurate. In this paper, we firstly explore the security issues of learning-based sketches with regard to estimation accuracy and memory overhead. Some adversarial scenarios of learning model and backup sketch are modeled according to the knowledge and capabilities of an adversary. Then, we propose four attacks to deceive learning-based sketch, namely counterfeit attack, targeted point attack, memory occupation attack, and blind increment attack. We conduct a series of experiments based on real-world datasets and verify that the proposed attacks highly degrade the performance of learning-based sketch even when the adversary knows nothing about it.","PeriodicalId":276379,"journal":{"name":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"30 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124653687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Heart Sound Classification Method Based on Residual Block and Attention Mechanism 基于残块和注意机制的心音分类方法

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2022-12-01 DOI: 10.1109/TrustCom56396.2022.00145

Yujie Chen, Wenliang Zhu, Jinke Xu, Junwei Zhang, Zhanpeng Zhu, Lirong Wang

引用次数: 0