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Machine Learning DDoS Detection for Generated Internet of Things Dataset (IoT Dat) 生成物联网数据集(IoT data)的机器学习DDoS检测
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257714
Ibrahim Ahmed Alnuman, M. Al-Akhras
{"title":"Machine Learning DDoS Detection for Generated Internet of Things Dataset (IoT Dat)","authors":"Ibrahim Ahmed Alnuman, M. Al-Akhras","doi":"10.1109/ICCIS49240.2020.9257714","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257714","url":null,"abstract":"Network infrastructure faces a lot of attacks, including attacks on integrity and confidentiality of the network packets along with their destinations and sources as well as attacks on network availability. Distributed Denial of Service (DDoS) emanates from various attack sources and focuses on the network, services, and hosts' availability. DDoS attacks are difficult to trace back to actual attackers, can lead to catastrophic service loss, and are launched with ease, making them one of the most dangerous attacks. This research simulates an Internet of Things network in-home setting of 100 nodes using OMNeT++ simulation tool, including a DDoS attack. Regular and attack-injected traffic is generated to evaluate the accuracy of detecting DDoS attacks in IoT networks using machine learning technqiues. A new IoT Dataset called IoT Dat is generated with different scenarios of normal traffic and traffic with attacks of different intensities of 5, 10, and 20. The authors will make this dataset publicly available. Moreover, machine learning techniques are used to assess the efficiency of attack detection.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115936139","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: 3
Visibile Light Communication Technology For Data Transmission Using Li-Fi 利用Li-Fi传输数据的可见光通信技术
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257654
R. Hassan, Mamoon Salam Flayyih, A. Mahdi, Arbaiah Inn, Abdulrahman Sameer Sadeq, D. F. Murad
{"title":"Visibile Light Communication Technology For Data Transmission Using Li-Fi","authors":"R. Hassan, Mamoon Salam Flayyih, A. Mahdi, Arbaiah Inn, Abdulrahman Sameer Sadeq, D. F. Murad","doi":"10.1109/ICCIS49240.2020.9257654","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257654","url":null,"abstract":"Handling data transmission for radio signals became one of the most important concerns, giving birth to Light as a significant alternative. Visible Light Communication (VLC) arose as an effective option for data communication. Light Fidelity (Li- Fi) is one of VLC technologies and represents a new technique operating with light signals in order to transmit data a source to a destination. It guarantees several benefits and can overcome different limitations of Wi-Fi technologies including security issues, media obstacles, and radio interference. Li-Fi technologies are adopted for experimental usage and does not extensively arise in industry. The adoption of Li-Fi technology in industry, it is necessary to measure the performance of data transmission several data types requiring to be supported. The purpose of this paper is to investigate the performance of data communication using VLC. This research is based on an implementation for different types of data transmission through Li-Fi. The methodology that has been adopted for this study consists on a simulation topology by NS-3 which has been built to study the performance TCP and UDP protocols in Li-Fi environment for VLC communication. Various types of data have been transmitted through an appropriate designed model. The simulation results show the differences between the two common algorithms. The implementation explained the needs for Li-Fi data transmission. Indeed, this work show a successful audio, text, and images transfer through VLC technology.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115502870","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: 3
Energy Efficient Least Edge Computation LEACH in Wireless sensor network 无线传感器网络的能量高效最小边缘计算LEACH
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257649
Najm Us Sama, Kartinah Bt Zen, Atiq Ur Rahman, Baseerat Bibi, A. U. Ur Rahman, Ikra Afzal Chesti
{"title":"Energy Efficient Least Edge Computation LEACH in Wireless sensor network","authors":"Najm Us Sama, Kartinah Bt Zen, Atiq Ur Rahman, Baseerat Bibi, A. U. Ur Rahman, Ikra Afzal Chesti","doi":"10.1109/ICCIS49240.2020.9257649","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257649","url":null,"abstract":"Due to the energy resource restriction, the sensor nodes drain out their power. Therefore the routing mechanism among nodes and sink need to consider the balanced energy utilization. Low-Energy Adaptive Clustering Hierarchy (LEACH) consider direct data communication from source cluster head to sink, which results unbalanced energy consumption of cluster heads CHs and leads to routing holes in the network. For balanced energy consumption and maximum network lifetime an Energy efficient Least Edge Computation routing protocol (ELEC) is proposed in literature. The simulation results show better performance of ELEC as compared to LEACH. Therefore, an energy-efficient least edge computation multi-hop clustering LEACH (ELEC-LEACH) is proposed, where the LEACH routing protocol is modified by merging the ELEC multi-hop routing protocol with it. Simulation results prove that ELEC-LEACH enhance lifetime, residual energy, reduce the percentage of node failure and packet drop as compared to MR-LEACH. The result shows that the ELEC-LEACH routing protocol almost doubles the network lifetime, in addition just 9% of total energy left squander.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114254951","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: 6
Forecasting a Small-Scale Hydrogen Leakage in Air using Machine Learning Techniques 利用机器学习技术预测空气中的小规模氢气泄漏
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257718
M. El-Amin, A. Subasi
{"title":"Forecasting a Small-Scale Hydrogen Leakage in Air using Machine Learning Techniques","authors":"M. El-Amin, A. Subasi","doi":"10.1109/ICCIS49240.2020.9257718","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257718","url":null,"abstract":"Hydrogen leakage is a serious safety issue of pure hydrogen energy usage, since if it mixes with air, fire or explosion can be produced. In this study, the turbulent flow of hydrogen buoyant jet resulting from hydrogen leakage has been investigated using machine learning techniques. A mixed empirical-analytical-numerical model has been developed to describe the problem under consideration. The mass, momentum and concentration fluxes are represented by integral formulae and transformed into a set of ordinary differential equations, which are solved numerically. Therefore, important physical quantities such as the hydrogen mass fraction have been determined. Some machine learning techniques have been selected to forecasting the concentration distribution of hydrogen in air, including Linear Regression (LR), Artificial Neural Networks (ANNs), Support Vector Regression (SVR), k-Nearest Neighbour (k-NN), Random Forest (RF), Random Tree (RT) and REP Tree (REPT) techniques. It was found that the RF method is the best technique to predict the hydrogen leakage distribution in air.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114314825","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
Investigation on 6LoWPAN Data Security for Internet of Things 物联网6LoWPAN数据安全研究
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257661
Norsuhaila binti Hj Kasah, A. Aman, Z. S. Attarbashi, Yousef Fazea
{"title":"Investigation on 6LoWPAN Data Security for Internet of Things","authors":"Norsuhaila binti Hj Kasah, A. Aman, Z. S. Attarbashi, Yousef Fazea","doi":"10.1109/ICCIS49240.2020.9257661","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257661","url":null,"abstract":"Low-power wireless network technology is one of the main key characteristics in communication systems that are needed by the Internet of Things (IoT). Nowadays, the 6LoWPAN standard is one of the communication protocols which has been identified as an important protocol in IoT applications. Networking technology in 6LoWPAN transfer IPv6 packets efficiently in link-layer framework that is well-defined by IEEE 802.14.5 protocol. 6Lo WPAN development is still having problems such as threats and entrust crises. The most important part when developing this new technology is the challenge to secure the network. Data security is viewed as a major consideration in this network communications. Many researchers are working to secure 6LoWPAN communication by analyzing the architecture and network features. 6LoWPAN security weakness or vulnerability is exposed to various forms of network attack. In this paper, the security solutions for 6LoWPAN have been investigated. The requirements of safety in 6LoWPAN are also presented.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116046451","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
Recommendation system for human physical activities using smartphones 使用智能手机的人体运动推荐系统
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257671
Nesrine Kadri, A. Ellouze, M. Ksantini
{"title":"Recommendation system for human physical activities using smartphones","authors":"Nesrine Kadri, A. Ellouze, M. Ksantini","doi":"10.1109/ICCIS49240.2020.9257671","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257671","url":null,"abstract":"Important information can be obtained from smartphone users data such as profile modeling, behavior recognition, geolocalization, etc. Human activity recognition (HAR) from sensor smartphone data is a field which has garnered a lot of attention due to its high application in various domains such as the user health. In this paper, we will consider data from accelerometer to recognize the kind of user movements that we will classify to six kinds using machine and deep learning algorithms. Then, based on these results, we will make a recommendation system to inform the users of smartphone about their healthy behavior related to their physical activities.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114688650","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: 9
SCNN: A Secure Convolutional Neural Network using Blockchain SCNN:使用区块链的安全卷积神经网络
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257635
Inzamam Mashood Nasir, M. A. Khan, Ammar Armghan, M. Javed
{"title":"SCNN: A Secure Convolutional Neural Network using Blockchain","authors":"Inzamam Mashood Nasir, M. A. Khan, Ammar Armghan, M. Javed","doi":"10.1109/ICCIS49240.2020.9257635","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257635","url":null,"abstract":"Real-time applications like object detection, fire detection, face recognition and cancer detection are solely or partially relying on deep learning algorithms. Any tempering in these models can cause huge damages in many ways, therefore an utter need to secure these deep learning models is critically required. Blockchain technology has gained a wide popularity in tractability and security. In this article, the properties of blockchain are applied on the CNN models to produce secure CNN models. Each layer of a CNN model relates to a block, which contains the hash keys, public and private keys of their neighbors, while there exists a ledger block, which contains the detailed information about each layer of the model. The proposed SCNN model is tested using SVGG19 and SInceptionV3 models on publicly available datasets, which provides satisfactory results.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127392128","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: 6
An Eye on Riyadh Tourist Season: Using Geo-tagged Snapchat Posts to Analyse Tourists Impression 着眼于利雅得旅游季节:使用地理标记的Snapchat帖子来分析游客的印象
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257676
Najwa Alghamdi, Nourah Alageeli, Doaa Abu Sharkh, Maram Alqahtani, Muna S. Al-Razgan
{"title":"An Eye on Riyadh Tourist Season: Using Geo-tagged Snapchat Posts to Analyse Tourists Impression","authors":"Najwa Alghamdi, Nourah Alageeli, Doaa Abu Sharkh, Maram Alqahtani, Muna S. Al-Razgan","doi":"10.1109/ICCIS49240.2020.9257676","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257676","url":null,"abstract":"Social media has changed how individuals interact and communicate with others. It has become one of the essential communication platforms as users share their thoughts, ideas, and daily activities. Individuals like to socialize at their attended events publicly. Snapchat is a perfect platform that allows sharing ephemeral life-events via video or photo. Recently, Snapchat released the ability to access web-based SnapMap, which offers a real-time heat map of all snaps posted to “Our Story.” This paper will present the use of geo-tagged Snapchat posts (snaps) that are published on Snapchat public stories (i.e., SnapMap) to analyze tourists' impressions of selected Riyadh seasonal events using spatial, temporal, thematic, and sentiment descriptors. The initial results suggest the high potential for Snapchat to be used as a platform for preforming tourist event analysis such as crowd behaviour analysis, tourist preferences analysis and impression analysis.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122452999","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
Bitcoin Price Forecasting: A Comparative Study Between Statistical and Machine Learning Methods 比特币价格预测:统计方法与机器学习方法的比较研究
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257664
Waddah Saeed, H. Shah, M. Jabreel, D. Puig
{"title":"Bitcoin Price Forecasting: A Comparative Study Between Statistical and Machine Learning Methods","authors":"Waddah Saeed, H. Shah, M. Jabreel, D. Puig","doi":"10.1109/ICCIS49240.2020.9257664","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257664","url":null,"abstract":"This paper presents a comparative study between statistical and machine learning methods in forecasting Bitcoin's closing prices. Thirteen forecasting methods namely average, naive, drift, auto-regressive integrated moving-average, simple exponential smoothing (SES), Holt, and damped exponential smoothing, the average of SES, Holt and damped methods, exponential smoothing (ETS), bagged ETS, Theta, multilayer perceptron, and extreme learning machines (ELM) were used to forecast the closing prices for the next 14 days. The findings of this study are three folds. First, there are seven forecasting methods outperformed the naive method namely MLP, ELM, damped exponential smoothing, simple exponential smoothing, Theta, ETS, and ARIMA. Second, MLP and ELM showed better forecasting accuracy on both validation and out-of-sample data among the forecasting methods used in this study. Third, the size of the training data is essential factor that should be considered when training forecasting methods.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122562447","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: 3
Human detection in surveillance videos using MobileNet 利用MobileNet进行监控视频中的人体检测
2020 2nd International Conference on Computer and Information Sciences (ICCIS) Pub Date : 2020-10-13 DOI: 10.1109/ICCIS49240.2020.9257662
Bouafia Yassine, Guezouli Larbi, Lakhlef Hicham
{"title":"Human detection in surveillance videos using MobileNet","authors":"Bouafia Yassine, Guezouli Larbi, Lakhlef Hicham","doi":"10.1109/ICCIS49240.2020.9257662","DOIUrl":"https://doi.org/10.1109/ICCIS49240.2020.9257662","url":null,"abstract":"Video surveillance is of paramount importance. Surveillance systems are being developed to perform surveillance tasks automatically. Human detection process allows to build effective surveillance system and several approaches exist in literature for detection tasks that can be divided mainly in traditional machine learning approaches. The learned features are extracted automatically. They give most accurate results in image recognition tasks but they need more computing power and large space memory which is challenging for embedded devices. Ex: VggNet, ResNet. In this paper, we used MobileNet deep convolution neural network with transfer learning approach to build deep learning model for human classification. We used INRIA person dataset to train and test our model. We achieved a good accuracy and comparative precision.","PeriodicalId":425637,"journal":{"name":"2020 2nd International Conference on Computer and Information Sciences (ICCIS)","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122045769","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
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