2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)最新文献

Multi-channel Walk Embedding Based Ethereum Phishing Scam Detection Method 基于多通道行走嵌入的以太坊网络钓鱼诈骗检测方法

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00045

Jinghao Li, Hexiao Li, Na Cheng, Wuqing Zhang, Ya Xu, Hengyang Zhang, Jianbin Li

{"title":"Multi-channel Walk Embedding Based Ethereum Phishing Scam Detection Method","authors":"Jinghao Li, Hexiao Li, Na Cheng, Wuqing Zhang, Ya Xu, Hengyang Zhang, Jianbin Li","doi":"10.1109/ICPADS56603.2022.00045","DOIUrl":"https://doi.org/10.1109/ICPADS56603.2022.00045","url":null,"abstract":"With the prevalent adoption of blockchain in the financial system, there has been an increase in phishing scams on cryptocurrency platforms such as Ethereum, and an effective anomaly detection method is urgently required. The latest studies have focused on anomaly identification using natural language processing techniques or constructing simple static graphs. However, the existing methods are insufficient to convey the diversity of connectivity patterns in the Ethereum transaction network concerning amount and time. To this end, we proposed a novel transaction network embedding algorithm transE based on the multi-channel random walk to model the detection of Ethereum phishing scam accounts as a multigraph node classification task. Specifically, we first model the Ethereum transaction as a time-amount directed multigraph. Then, the hybrid feature representation of network nodes is learned via transE from their local and global neighbours, which uses the attention mechanism to maximize the probability of preserving node network neighbours. Ultimately, we employ visualization techniques and machine learning models to validate the effectiveness of the algorithms, and the model with the top performance is picked for Ethereum account classification. Experimental results indicate that the embedding vector extracted by transE improves the detection accuracy of Ethereum phishing accounts in the different classification tasks.","PeriodicalId":335451,"journal":{"name":"2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116614889","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

Automatic Operator Performance Tumng in a Machine Learning System on Edge 边缘机器学习系统中的自动操作员性能变化

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00109

Peng Xu, Xinyu Chang, Jianxin R. Zhao, Chi Harold Liu

引用次数: 0

An Improved Least-square based Jammer Localization Algorithm 一种改进的基于最小二乘的干扰机定位算法

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00041

Ruiqiong Tong, Yicong Du, Hongbo Liu, Yingying Chen

{"title":"An Improved Least-square based Jammer Localization Algorithm","authors":"Ruiqiong Tong, Yicong Du, Hongbo Liu, Yingying Chen","doi":"10.1109/ICPADS56603.2022.00041","DOIUrl":"https://doi.org/10.1109/ICPADS56603.2022.00041","url":null,"abstract":"Due to the shared nature of wireless mediums, jamming attacks have long been a great hazard to the security of wireless networks. A plethora of efforts have been spent to mitigate the impact of jamming attacks, and especially the localization technique of malicious jammer emerges in the last decade and enables us to remove the interfering devices from the physical layer. Since it is impossible to directly measure the interfering signal in a jamming scenario, many existing methods rely on inaccurate ranging estimation to locate the jammers. In this paper, we propose an improved least-square jammer localization method leveraging the network distribution properties. Specifically, we exploit the stochastic geometry theory to analyze the coverage changes of wireless devices around the jammer, which are then used to improve the accuracy of ranging estimation. Extensive numerical results demonstrate the effectiveness and robustness of the proposed jammer localization methods under various scenarios. Notably, the improved leastsquares method has a decreasing of 35 % on the mean localization error comparing to the traditional least-square method.","PeriodicalId":335451,"journal":{"name":"2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124305438","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

Fingersound: A Low-cost and Deployable Authentication System with Fingertip Sliding Sound 指尖滑动声:一种低成本、可部署的认证系统

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00013

Zhanglei Shu, Zhangsen Wang, Guozheng Yang, Cheng Zang, Zhe Ma, Feng Lin, Kui Ren

{"title":"Fingersound: A Low-cost and Deployable Authentication System with Fingertip Sliding Sound","authors":"Zhanglei Shu, Zhangsen Wang, Guozheng Yang, Cheng Zang, Zhe Ma, Feng Lin, Kui Ren","doi":"10.1109/ICPADS56603.2022.00013","DOIUrl":"https://doi.org/10.1109/ICPADS56603.2022.00013","url":null,"abstract":"Fingerprint recognition technology is the most widely used technology in the field of biometrics and is also the preferred solution for mobile devices and the financial industry. However, traditional fingerprint recognition technology requires expensive sensors on the one hand and risks leaking fingerprint images on the other hand. In this paper, we propose Fingersound, a low-cost and deployable authentication system that utilizes the sound generated by finger sliding as an identity feature. We use a microphone array to record continuous sliding sound and extract multiple features in the frequency and time domains. Then we use various algorithms including a deep neural network to perform user authentication. We also design a mobile phone application that can interact with the embedded system to manage users and record authentication history. In our experiments, 100 participants used this system and achieved an equal error rate of 5.2%. Additionally, we investigate the system’s robustness within different sliding materials, texturesand under noise disturbances. We further demonstrate the resistance of Fingersound to replay attack.","PeriodicalId":335451,"journal":{"name":"2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127878446","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

Causal Ordering in the Presence of Byzantine Processes 拜占庭过程存在下的因果排序

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00025

Anshuman Misra, A. Kshemkalyani

引用次数: 7

Context-Adaptive Online Reinforcement Learning for Multi-view Video Summarization on Mobile Devices 移动设备上多视点视频摘要的上下文自适应在线强化学习

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00060

Jingyi Hao, Sicong Liu, Bin Guo, Yasan Ding, Zhiwen Yu

{"title":"Context-Adaptive Online Reinforcement Learning for Multi-view Video Summarization on Mobile Devices","authors":"Jingyi Hao, Sicong Liu, Bin Guo, Yasan Ding, Zhiwen Yu","doi":"10.1109/ICPADS56603.2022.00060","DOIUrl":"https://doi.org/10.1109/ICPADS56603.2022.00060","url":null,"abstract":"The huge amount of video data produced by ubiqui tous cameras imposes significant challenges for users to efficiently obtain useful video information. Multi-view video summarization (MVS) aggregates multi-view videos into information-rich video summaries by considering content correlations within each view and between multiple views. Existing MVS methods fail to concentrate on performance across scenarios and usually achieve satisfactory performance on specific training datasets. However, when faced with unseen video scenarios, the quality of the summaries generated by existing methods may degrade. Moreover, they usually only use cameras for data acquisition, which require a large amount of network bandwidth to transfer the data to the server for processing. To bridge this gap, we propose a context-adaptive online reinforcement learning multi-view video summarization framework (COORS) that meets the low response latency performance requirements of context adaptation while ensuring camera hardware compatibility. Specifically, COORS enables retraining in new contexts by extracting contextindependent rewards, while improving model convergence speed based on representation learning and replica playback. Extensive experiments show that COORS has better performance compared to the state-of-the-art baselines.","PeriodicalId":335451,"journal":{"name":"2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134025773","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

Tereis: A Package-Based Scheduling in Deep Learning Systems 深度学习系统中基于包的调度

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00117

Chen Chen, Sen Wang, Yingwen Chen, Jianchen Han

{"title":"Tereis: A Package-Based Scheduling in Deep Learning Systems","authors":"Chen Chen, Sen Wang, Yingwen Chen, Jianchen Han","doi":"10.1109/ICPADS56603.2022.00117","DOIUrl":"https://doi.org/10.1109/ICPADS56603.2022.00117","url":null,"abstract":"Deep learning (DL) systems are typically used to accelerate training DL jobs. Training DL models requires feeding mass input data. It takes a long time to transfer training data from the storage nodes to the compute nodes. However, the computational resources of the GPUs are idle during the data transmission period, which results in a waste of computing resources. In DL systems, a large number of short-term jobs are queuing longer than their own execution times. Meanwhile, many multi-GPU jobs are suffering a long-queuing time due to not enough free GPU. To the best of our knowledge, no studies try to use the idle computation resources of GPU in the data transmission period.We propose Tereis, a package-based scheduler to make full use of GPU. Tereis predicts a DL job’s execution time and data transmission time, then safely package two jobs on the same GPU. One of the packaged jobs will be completed before the other job ends transferring data, which is what ‘safely’ means. This ‘safe’ Packaging does not cause GPU contention. Tereis also designs multi-level queues to prevent starvation. We implemented Tereis in python on the actual cluster and evaluated its performance. The experiment results show that Tereis decreases the average waiting time by 3.2× to10.5×, and has an improvement of 18% to 42% on makespan compared to other methods. Furthermore, we have made large-scale simulations to explore the sensitivities of Tereis. We find that Tereis performs better in the scenario where the job set has a distribution of large dataset size and jobs are submitted frequently.","PeriodicalId":335451,"journal":{"name":"2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125214898","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

Dependency-Aware Traffic Management for Configuring On-demand in Service Meshes 基于依赖感知的流量管理，用于配置按需服务网格

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00065

L. Wang, Xin Li, Ning Wang, Hao Li, X. Qin, Jie Wu

{"title":"Dependency-Aware Traffic Management for Configuring On-demand in Service Meshes","authors":"L. Wang, Xin Li, Ning Wang, Hao Li, X. Qin, Jie Wu","doi":"10.1109/ICPADS56603.2022.00065","DOIUrl":"https://doi.org/10.1109/ICPADS56603.2022.00065","url":null,"abstract":"Service mesh is a promising micro-services architecture due to its excellent governance capabilities. Unlike traditional service invocation, configurations for governance need to be issued in the service mesh. However, we find that the control-plane traffic of governance is distributed in full by default, i.e., each service in the data plane receives all configurations. The vast majority of the configurations are redundant for a specific service. Hence, it is important and challenging to make the control plane aware of the calling relationships between services. In this paper, we propose a traffic management mechanism named DATM. Using this mechanism, the entire cluster can be dynamically controlled and services can be configured on demand. It is implemented through a dependency-aware controller and monitors. The controller first processes the information listened to by the monitors and then analyzes the connection between the metrics and the service requests through intelligent algorithms. Finally, the control traffic for regulating the control plane is generated. Our proposed mechanism is experimentally compared with the default strategy and existing work across a wide set of load scenarios in a testbed based on Istio service mesh and Kubernetes. Experimental results demonstrate that our mechanism can save the storage resources of a single agent by 40% to 60%, and the number of cluster updates can be greatly reduced. From the perspective of the whole cluster, the optimization results are even better.","PeriodicalId":335451,"journal":{"name":"2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132177477","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

A Heat-Recirculation-Aware Data Placement Strategy towards Data Centers 数据中心热再循环感知数据放置策略

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00081

Zijie Zhong, Yuhui Deng, J. Li

引用次数: 0

Dynamic Adaptive Checkpoint Mechanism for Streaming Applications Based on Reinforcement Learning 基于强化学习的流应用动态自适应检查点机制

2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2023-01-01 DOI: 10.1109/ICPADS56603.2022.00076

Zhan Zhang, Tianming Liu, Yanjun Shu, Siyuan Chen, Xian Liu

{"title":"Dynamic Adaptive Checkpoint Mechanism for Streaming Applications Based on Reinforcement Learning","authors":"Zhan Zhang, Tianming Liu, Yanjun Shu, Siyuan Chen, Xian Liu","doi":"10.1109/ICPADS56603.2022.00076","DOIUrl":"https://doi.org/10.1109/ICPADS56603.2022.00076","url":null,"abstract":"For a stream processing system that uses checkpoints as a fault-tolerant method, selecting the appropriate checkpoint period is the key to ensuring the efficient operation of streaming applications. State-of-art stream processing systems currently only support fixed-cycle checkpoints, which is difficult to make a good trade-off between fault-tolerant processing and the cost of failure recovery in dynamically changing streaming application scenarios. Moreover, in a complex distributed streaming application environment, the dynamic environmental indicators (e.g., the values of workloads and failure rates) are not in coincidence with the model assumptions, such as the dynamics of Twitter’s hot events data changing quickly. In this paper, we consider the dynamic changes of environmental indicators and adaptively optimize the processing delay and fault recovery time. Then, we propose a dynamic adjustment method for the checkpoint interval by reinforcement learning, which is named DACM. DACM adaptively optimizes the processing delay and fault recovery time, while avoiding the overall environment modeling of streaming applications. The experiments conducted on the Flink platform show that DACM reduces the processing delay by 10% and the failure recovery time by 37% compared with the existing checkpoint interval optimization models.","PeriodicalId":335451,"journal":{"name":"2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127098199","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