2021 International Conference on Smart Applications, Communications and Networking (SmartNets)最新文献

A Hybridized Approach for Testing Neural Network Based Intrusion Detection Systems 基于神经网络的入侵检测系统的混合测试方法

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/SmartNets50376.2021.9555416

Faqeer ur Rehman, C. Izurieta

{"title":"A Hybridized Approach for Testing Neural Network Based Intrusion Detection Systems","authors":"Faqeer ur Rehman, C. Izurieta","doi":"10.1109/SmartNets50376.2021.9555416","DOIUrl":"https://doi.org/10.1109/SmartNets50376.2021.9555416","url":null,"abstract":"Enhancing the trust of machine learning-based classifiers with large input spaces is a desirable goal; however, due to high labeling costs and limited resources, this is a challenging task. One solution is to use test input prioritization techniques that aim to identify and label only the most effective test instances. These prioritized test inputs can then be used with some popular testing techniques e.g., Metamorphic testing (MT) to test and uncover implementation bugs in computationally complex machine learning classifiers that suffer from the oracle problem. However, there are certain limitations involved with this approach, (i) using a small number of prioritized test inputs may not be enough to check the program correctness over a large variety of input scenarios, and (ii) traditional MT approaches become infeasible when the programs under test exhibit a non-deterministic behavior during training e.g., Neural Network-based classifiers. Therefore, instead of using MT for testing purposes, we propose a metamorphic relation to solve a data generation/labeling problem; that is, enhancing the test inputs effectiveness by extending the prioritized test set with new tests without incurring additional labeling costs. Further, we leverage the prioritized test inputs (both source and follow-up data sets) and propose a statistical hypothesis testing (for detection) and machine learning-based approach (for prediction) of faulty behavior in two other machine learning classifiers (Neural Network-based Intrusion Detection Systems). In our case, the problem is interesting in the sense that injected bugs represent the high accuracy producing mutated program versions that may be difficult to detect by a software developer. The results indicate that (i) the proposed statistical hypothesis testing is able to identify the induced buggy behavior, and (ii) Random Forest outperforms and achieves the best performance over SVM and k-NN algorithms.","PeriodicalId":443191,"journal":{"name":"2021 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121021439","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: 4

Cost effective and Accurate Vehicle Make/Model Recognition method Using YoloV5 基于YoloV5的高效准确的汽车品牌/车型识别方法

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/SmartNets50376.2021.9555409

Di Wang, Ahmad Al-Rubaie, Yaqoub Alsarkal, Sandra Stincic, John Davies

引用次数: 2

SmartNets 2021 Authors Index SmartNets 2021作者索引

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/smartnets50376.2021.9555413

引用次数: 0

[SmartNets 2021 Front cover] [SmartNets 2021年封面]

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/smartnets50376.2021.9555427

引用次数: 0

Using Deep Learning for COVID-19 Control: Implementing a Convolutional Neural Network in a Facemask Detection Application 将深度学习用于COVID-19控制:在面罩检测应用中实现卷积神经网络

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/SmartNets50376.2021.9555431

Caolan Deery, Kevin Meehan

{"title":"Using Deep Learning for COVID-19 Control: Implementing a Convolutional Neural Network in a Facemask Detection Application","authors":"Caolan Deery, Kevin Meehan","doi":"10.1109/SmartNets50376.2021.9555431","DOIUrl":"https://doi.org/10.1109/SmartNets50376.2021.9555431","url":null,"abstract":"The ongoing COVID-19 pandemic has changed people’s lives in ways that many would not have predicted. In the days, weeks and months since mandatory lockdowns and restrictions came into effect worldwide, people have had to adjust their daily lives in an effort to slow and restrict the spread of the virus -- like regularly sanitising their hands, maintaining social distancing in crowded places, and wearing facemasks. The latter is contentious for some but has been a necessary deterrent in slowing the spread of this virus. There is potential for utilising technology as a supplementary deterrent and monitoring tool to help detect non-compliance of mask wearing. This research investigates the efficacy of AI for such purposes, exploring the applicability of a Convolutional Neural Network (CNN), for predicting if a person in a real time video feed is wearing a facemask. A dataset of over 10,000 images was created to effectively evaluate this research. The CNN developed was tested against the validation dataset to evaluate its performance, the model demonstrated 98.47% accuracy on a varied and balanced dataset.","PeriodicalId":443191,"journal":{"name":"2021 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121604871","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

On Finger Stretching and Bending Dynamics as a Biometric Modality 手指伸展和弯曲动力学作为生物识别模态

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/SmartNets50376.2021.9555429

Sraddhanjali Acharya, Abdul Serwadda

{"title":"On Finger Stretching and Bending Dynamics as a Biometric Modality","authors":"Sraddhanjali Acharya, Abdul Serwadda","doi":"10.1109/SmartNets50376.2021.9555429","DOIUrl":"https://doi.org/10.1109/SmartNets50376.2021.9555429","url":null,"abstract":"Studies on the characterization of the dexterity of fingers and hands improve the understanding of how humans interact with computing devices. In this study, finger bending patterns captured by flex sensors worn on the fingers are characterized to build a biometric authentication system. The modality uses an array of resistive sensors fitted in a smart glove worn by users while typing. The study encompasses 55 users, 23 of them entered a 9-digit PIN on a laptop’s number pad, and 32 of them typed a 10-length alphanumeric password on the full-sized keyboard. The results demonstrate that the users are authenticated using features built from the flex sensors relating to their PIN and password with a mean EER score of 7.49% and 9.76%, respectively. We further assessed the potential of using individual fingers to authenticate users in both the biometric systems and found that even the fingers not used for typing exhibited discriminative patterns due to movement dynamics during the typing process. This assessment highlights the potential for designing lightweight biometric modalities utilizing dexterity and patterns based on fewer fingers.","PeriodicalId":443191,"journal":{"name":"2021 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122769817","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

Decentralized Computation Offloading in Mobile Edge Computing Systems 移动边缘计算系统中的分散计算卸载

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/SmartNets50376.2021.9553007

Rohan Sharma, Kushaal Gummaraju, Pranav Anantharam, Ojaswi Saraf, Vamsi Krishna Tumuluru

{"title":"Decentralized Computation Offloading in Mobile Edge Computing Systems","authors":"Rohan Sharma, Kushaal Gummaraju, Pranav Anantharam, Ojaswi Saraf, Vamsi Krishna Tumuluru","doi":"10.1109/SmartNets50376.2021.9553007","DOIUrl":"https://doi.org/10.1109/SmartNets50376.2021.9553007","url":null,"abstract":"Existing works on mobile edge computing (MEC) which operate under multi-user and multi-server scenarios often assume centralized computation offloading. This paper proposes a decentralized computation offloading scheme where a user does not require information about other users and about the MEC network (e.g., number of servers, network topology). Under the proposed computation offloading scheme, a user infers the transmission delay from the link rate assigned by its associated base station (BS). Further, each user privately deploys a moving average model to estimate the network delay after transmission. Using such information and its own information (i.e., local computing resource and energy availability), the user decides whether to offload its task to the MEC network via the BS. In case, a user decides to offload its task then the task deadline is not revealed to the MEC network to maintain fairness. Thereafter, the central controller of the MEC network performs optimal task allocation and notification of the computation results to the users. The impact of various user-parameters such as task generation probability, deadline, task size and processing density on the users and the MEC network are analyzed using extensive simulations.","PeriodicalId":443191,"journal":{"name":"2021 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133625729","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: 2

Privacy-aware Robust Proactive Content Caching using Edge Service Providers 使用边缘服务提供商的具有隐私意识的健壮的主动内容缓存

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/SmartNets50376.2021.9555417

Rishi Kashyap, Manasa Bhat, Deepa Umashankar, Vamsi Krishna Tumuluru

{"title":"Privacy-aware Robust Proactive Content Caching using Edge Service Providers","authors":"Rishi Kashyap, Manasa Bhat, Deepa Umashankar, Vamsi Krishna Tumuluru","doi":"10.1109/SmartNets50376.2021.9555417","DOIUrl":"https://doi.org/10.1109/SmartNets50376.2021.9555417","url":null,"abstract":"In this paper, we propose a novel proactive content caching problem in which a set of contending edge service providers (ESPs) in a given region offer their storage and link capacities to the content provider (CP). The privacy of each contending ESP is preserved in the proposed caching problem. Each ESP independently determines the amount of storage and link capacity it can offer to the CP based on the local forecast of the content requests and its local edge resources. Unlike existing works, an ESP’s decision making problem is modeled as a robust mixed integer problem due to the uncertain storage capacity. Based on the offers made by the ESPs and its own prediction of the content requests, the CP determines the optimal content placement decisions while reserving the storage and link capacities under the ESPs in order to serve its clients at different bit rates. The CP also finds the optimal allocation of predicted requests across the ESPs. The decisions of the CP are found using a separate mixed integer problem which minimizes the payments given by the CP to the ESPs for their service. We show the impact of the robust parameter on the content placement decisions. We also perform sensitivity analysis of the CP’s decisions.","PeriodicalId":443191,"journal":{"name":"2021 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134344331","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

Fault Prediction in HVAC Chillers by Analysis of Internal System Dynamics 基于内部系统动力学分析的暖通空调制冷机故障预测

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/SmartNets50376.2021.9555424

K. Padmanabh, Ahmad Al-Rubaie, John Davies, Sandra Stincic, A. Aljasmi

{"title":"Fault Prediction in HVAC Chillers by Analysis of Internal System Dynamics","authors":"K. Padmanabh, Ahmad Al-Rubaie, John Davies, Sandra Stincic, A. Aljasmi","doi":"10.1109/SmartNets50376.2021.9555424","DOIUrl":"https://doi.org/10.1109/SmartNets50376.2021.9555424","url":null,"abstract":"The Chiller of a Heating, Ventilation, and Air-Conditioning (HVAC) system is a complex and expensive multicomponent appliance that is not impervious to failure. Predicting, or even identifying, a fault at its inception, can reduce the scale of the damage and mitigate the potential losses to be incurred, both financial and operational. This paper presents a systematic approach for the analysis of multiple streams of data from chillers to identify potential failures as soon as they become detectable from the data. The data streams are received from sensors in the IoT ecosystem of chillers to monitor the multitude of processes and parameters that are vital to their operation. Chillers have built-in mechanisms to generate alarms when key sensor values go beyond designated limits. A certain combination of these alarms is responsible for chiller failure, therefore, our proposed method needs to first predict these alarms using multi-sensor data fusion. Thus, in this IoT ecosystem there are two levels of sensor fusion for our predictive models: at the sensor level and at the derived alarms level. The final objective is to determine “time-time-to-next-alarm” TA). The model for TTA is built using time-shifted sensor values. Since chiller failure is a function of sensor alarms, and both are binary in nature, a special technique of logistic circuits is used to mimic the combination logical circuit to predict the failure of the chiller.","PeriodicalId":443191,"journal":{"name":"2021 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132347026","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

Challenges and Approaches to Time-Series Forecasting for Traffic Prediction at Data Centers 数据中心流量预测中时间序列预测的挑战和方法

2021 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2021-09-22 DOI: 10.1109/SmartNets50376.2021.9555422

Shruti Jadon, A. Patankar, Jan Kanty Milczek

引用次数: 1