2019 International Conference on Computing, Networking and Communications (ICNC)最新文献

{"title":"Integrated Node Authentication and Key Distribution Method for Body Area Network","authors":"Zhouzhou Li, Hua Fang, Honggang Wang","doi":"10.1109/ICCNC.2019.8685559","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685559","url":null,"abstract":"Node Authentication and Key Distribution are two tightly correlated security tasks for a secure Body Area Networks (BAN) system. Handling them separately may cause many practical issues. Based on the recent advances on node authentication and (shared) key distribution (including key generation), we propose a new integrated method to securely and efficiently conduct the two tasks. We build a system model with the consideration of passive and active attacks and solve some security risks. One of performance metric, key generation rate is significantly improved in our method. We implement and verify the proposed methods on two test beds. The experimental result demonstrates the effectiveness and efficiency of our proposal.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114335964","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}

{"title":"Verification Code Recognition Based on Active and Deep Learning","authors":"Dongliang Xu, Bailing Wang, Xiaojiang Du, Xiao-Yuan Zhu, Zhitao Guan, Xiaoyan Yu, Jingyu Liu","doi":"10.1109/ICCNC.2019.8685560","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685560","url":null,"abstract":"A verification code is an automated test method used to distinguish between humans and computers. Humans can easily identify verification codes, whereas machines cannot. With the development of convolutional neural networks, automatically recognizing a verification code is now possible for machines. However, the advantages of convolutional neural networks depend on the data used by the training classifier, particularly the size of the training set. Therefore, identifying a verification code using a convolutional neural network is difficult when training data are insufficient. This study proposes an active and deep learning strategy to obtain new training data on a special verification code set without manual intervention. A feature learning model for a scene with less training data is presented in this work, and the verification code is identified by the designed convolutional neural network. Experiments show that the method can considerably improve the recognition accuracy of a neural network when the amount of initial training data is small.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131911121","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}

{"title":"Dynamic Bayesian Game Based Power Allocation in Mobile Edge Computing with Users’ Behaviors","authors":"Sachula Meng, Ying Wang, Wensheng Sun, Shan Guo, Kai Sun","doi":"10.1109/ICCNC.2019.8685547","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685547","url":null,"abstract":"In this paper, we investigate the power allocation problem based on users’ behaviors in mobile edge computing (MEC) networks. Due to the information limitation about the behavior types of mobile users, the power allocation is quite challenging. To deal with this problem, we propose a dynamic Bayesian game based power allocation algorithm to maximize the utility function of MEC network. In Bayesian game model, the MEC server imposes a price per unit power on mobile users. And the MEC server modified the price based on the Bayesian probability information about the behaviors of the users. The mobile users dynamically adapt the behavior types and the required power according to their own performance and cost. We investigate the existence of Bayesian Nash equilibrium and simulation studies are carried out to demonstrate the effectiveness of the proposed algorithm.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132044214","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}

{"title":"Joint Base Station Selection and Adaptive Slicing in Virtualized Wireless Networks: A Stochastic Optimization Framework","authors":"Kory Teague, Mohammad J. Abdel-Rahman, A. B. Mackenzie","doi":"10.1109/ICCNC.2019.8685518","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685518","url":null,"abstract":"Wireless network virtualization is a promising avenue of research for next-generation 5G cellular networks. Virtualization focuses on the concept of active resource sharing and the building of a network designed for specific demands, decreasing operational expenditures, and improving demand satisfaction of cellular networks. This work investigates the problem of selecting base stations (BSs) to construct a virtual network that meets the the specific demands of a service provider, and adaptive slicing of the resources between the service provider’s demand points. A two-stage stochastic optimization framework is introduced to model the problem of joint BS selection and adaptive slicing. Two methods are presented for determining an approximation for the two-stage stochastic optimization model. The first method uses a sampling approach applied to the deterministic equivalent program of the stochastic model. The second method uses a genetic algorithm for BS selection and adaptive slicing via a single-stage linear optimization problem. For testing, a number of scenarios were generated using a log-normal model designed to emulate demand from real world cellular networks. Simulations indicate that the first approach can provide a reasonably good solution, but is constrained as the time expense grows exponentially with the number of parameters. The second approach provides a vast improvement in run time with the introduction of some error.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133873048","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}

{"title":"Cloud-assisted Two-Factor Protection Mechanism for Public Data in Smart Campus","authors":"Jian Shen, Xinzhao Jiang, Dengzhi Liu, Tianqi Zhou","doi":"10.1109/ICCNC.2019.8685561","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685561","url":null,"abstract":"Two-factor data security protection in cloud environments has become a research hotspot in recent years. With the rapid development of cloud computing, how to achieve the two-factor protection of public data resources in the cloud is a serious problem to be tackled. Furthermore, how to achieve both security and revocability is a challenge for two-factor too. In this paper, we propose a cloud-assisted two-factor protection mechanism with factor revocability for public data in smart campus. The proposed mechanism allows a data owner to send an encrypted message to user through a cloud. The data owner is required to formulate access policies and perform attribute-based encryption on messages. In order to decrypt, the user needs to possess two factors. The first factor is user’s secret key. The second factor security equipment is a campus card in this paper. The ciphertext can be decrypted if and only if the user gathers the key and the security equipment at the same time. Analysis and experimental results demonstrate that the proposed mechanism is secure, efficient and practical.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134179161","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}

{"title":"Automatic Spam Detection on Gulf Dialectical Arabic Tweets","authors":"Dema Alorini, D. Rawat","doi":"10.1109/ICCNC.2019.8685659","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685659","url":null,"abstract":"The usage of social media is increasing rapidly in the Arab region. One of the popular social networking sites for sharing news and spreading propaganda is Twitter. Spammers use these sites to disseminate adult content and false political news in Arabic tweets. Within the Arab region, distributing adult materials is illegal and some governments attempted to block malicious URLs. In this paper, we study both user and content attributes to differentiate between legitimate and illegitimate users. Then, we use those attributes with machine learning algorithms to detect spam on Twitter. We use Naive Bayes (NB) and Support Vector Machine (SVM) classification methods to find malicious contents in the tweets. Our results show that NB produces more accurate outcomes for detecting spam in Gulf Dialectical Arabic tweets.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"262 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125806200","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}

{"title":"Dynamic EAP Based MAC Protocol for Wireless Body Area Networks","authors":"Ai Enkoji, Ming Li, James Daniel Brisky, Ryan Melvin","doi":"10.1109/ICCNC.2019.8685495","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685495","url":null,"abstract":"Wireless body area networks are a network of sensors on, in the vicinity of, or implanted within the body for a variety of applications including medical monitoring. Due to the nature of these sensors, data transmission reliability and quality are essential. Furthermore, we must recognize that each type of body sensor holds a unique importance to each user and his or her specific health needs, an importance that can also change at any time. A user may have a multitude of different sensor combinations being measured with varying significance, and in order to ensure meaningful analysis, it is imperative that we have the highest possible data reliability. However, the current IEEE 802.15.6 [1] is static in general and cannot easily adapt to changing scenarios throughout the day. This paper presents a dynamic EAP based MAC protocol for WBANs that seeks to better suit the unique needs of users by dynamically adjusting the allocated slots of the Exclusive Access Phase (EAP) and Random Access Phase (RAP) of the IEEE 802.15.6 beacon period (superframe) structure to fit the transmission needs of the sensors, as well as utilizing packet prioritization to minimize resource competition during the RAP phase. The length of the EAP is determined by calculating the necessary transmission time of all the packets the EAP node has scheduled to send during the beacon period. The length of the RAP is calculated by weighting the remaining time by the lengths of the respective preceding EAP phase. Furthermore, each type of sensor is assigned to one of three ranks, Always Important, Sometimes Important, and Never Important, depending on their importance to the user. The purpose of these ranks is to categorize sensors based on the user’s unique needs and to ensure that sensor data with the highest importance are successfully collected while also ensuring that sensor data of lower ranked sensors have useful and acceptable throughput as well. Simulation results have shown that this protocol improves throughput for the most important data – data from Always Important sensors and Sometimes Important sensors with important data – with little to no decline in the overall throughput.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127524451","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}

{"title":"Fast and Accurate Machine Learning-based Malware Detection via RC4 Ciphertext Analysis*","authors":"Junggab Son, Euiseong Ko, Uday Bhaskar Boyanapalli, Donghyun Kim, Youngsoon Kim, Mingon Kang","doi":"10.1109/ICCNC.2019.8685644","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685644","url":null,"abstract":"Recent malware increases its viability by employing ciphers which help to hide malicious intention and/or behavior against detection schemes. So far, many efforts have been made to detect malware and to prevent it from damaging clients by monitoring network packets. However, these conventional detection schemes tend to treat an encrypted packet as legitimate due to the hardness of extracting information from ciphertexts. Cryptoanalysis of each packet flowing over a network might be one feasible solution to the problem. However, this approach is computationally expensive and lacks accuracy, and thus it is consequently not a practical solution. To address the problem, we firstly introduce a discovery that a fixed encryption key generates unique statistical patterns on RC4 ciphertexts. To the best of our knowledge, this unique signature has never been discussed in the literature. Then, we propose a machine learning-based detection scheme that can identify malware packets efficiently and accurately by leveraging the discovery. The proposed scheme directly analyze network packets without decrypting ciphertexts. Moreover, our analysis demonstrates the proposed scheme requires only a tiny subset of the network packet.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129285425","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}

{"title":"BRACELET: Edge-Cloud Microservice Infrastructure for Aging Scientific Instruments","authors":"Phuong Nguyen, Tarek Elgamal, Steven Konstanty, Todd Nicholson, Stuart Turner, Patrick Su, K. Nahrstedt, T. Spila, R. Campbell, J. Dallesasse, Michael Chan, Kenton McHenry","doi":"10.1109/ICCNC.2019.8685528","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685528","url":null,"abstract":"Recent advances in cyber-infrastructure have enabled digital data sharing and ubiquitous network connectivity between scientific instruments and cloud-based storage infrastructure for uploading, storing, curating, and correlating of large amounts of materials and semiconductor fabrication data and metadata. However, there is still a significant number of scientific instruments running on old operating systems that are taken offline and cannot connect to the cloud infrastructure, due to security and network performance concerns. In this paper, we propose BRACELET - an edge-cloud infrastructure that augments the existing cloud-based infrastructure with edge devices and helps to tackle the unique performance & security challenges that scientific instruments face when they are connected to the cloud through public network. With BRACELET, we put a networked edge device, called cloudlet, in between the scientific instruments and the cloud as the middle tier of a three-tier hierarchy. The cloudlet will shape and protect the data traffic from scientific instruments to the cloud, and will play a foundational role in keeping the instruments connected throughout its lifetime, and continuously providing the otherwise missing performance and security features for the instrument as its operating system ages.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130510118","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}

{"title":"Investigating the Delay Impact of the DiffServ Code Point (DSCP)","authors":"M. Welzl, Safiqul Islam, Runa Barik, S. Gjessing, A. Elmokashfi","doi":"10.1109/ICCNC.2019.8685538","DOIUrl":"https://doi.org/10.1109/ICCNC.2019.8685538","url":null,"abstract":"The DiffServ Code Point (DSCP) field in the IP header allows to specify a desired per-hop behavior as packets traverse routers. Setting the DSCP field opportunistically, without prior contractual agreement, has recently become accepted practice for Internet end hosts. Measurement studies find that there is reason to hope for a DSCP setting to have an effect on traffic, and at least configuring this value is not heavily detrimental: systematic drops of packets due to non-zero DSCP values are rare, and the value is often left intact along an end-to-end path. What these studies do not discuss is whether per-hop behaviors truly are honored: what happens to packets in terms of the delay they experience? In this paper, we make an attempt to find a first answer to this by mining a dataset of our own recent large-scale measurement study. Using a deep neural network, we obtain the importance of the factors which help us understand the delay impact of the DSCP.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129222113","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}