2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)最新文献_第10页

Is he Becoming an Excellent Customer for us? A Customer Level Prediction Method for a Customer Relationship Management System 他会成为我们的优秀客户吗?客户关系管理系统中的客户等级预测方法

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-16 DOI: 10.1109/AINA.2018.00056

Chiaki Doi, M. Katagiri, T. Araki, Daizo Ikeda, H. Shigeno

引用次数: 1

Using Externals IdPs on OpenStack: A Security Analysis of OpenID Connect, Facebook Connect, and OpenStack Authentication 在OpenStack上使用外部idp: OpenID Connect、Facebook Connect和OpenStack认证的安全性分析

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-01 DOI: 10.1109/AINA.2018.00135

G. C. Batista, C. Miers, G. Koslovski, M. A. Pillon, N. Gonzalez, M. Simplício

{"title":"Using Externals IdPs on OpenStack: A Security Analysis of OpenID Connect, Facebook Connect, and OpenStack Authentication","authors":"G. C. Batista, C. Miers, G. Koslovski, M. A. Pillon, N. Gonzalez, M. Simplício","doi":"10.1109/AINA.2018.00135","DOIUrl":"https://doi.org/10.1109/AINA.2018.00135","url":null,"abstract":"The installation and configuration of cloud environments has increasingly become automated and therefore simple. For instance, solutions such as RedHat RDO and Mirantis Fuel facilitate the deployment of popular computational clouds like OpenStack. Despite the advances in usability, effort is still required to create and manage multiple users. This is of particular relevance when dealing with sensitive information, a somewhat common case for private clouds. To alleviate this burden, many clouds have adopted federated Single Sign-On (SSO) mechanisms for authenticating their users in a more transparent manner. In this work we analyze the practical security of an OpenStack IaaS cloud when combined with either OpenID Connect (using Google as IdP) or Facebook Connect (using Facebook as IdP). The criteria used in the analysis comprise the ability to provide data encryption, the risks involved in the use of an external IdP, and improper access control. We identify potential issues regarding these solutions and we propose approaches to fix them.","PeriodicalId":239730,"journal":{"name":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127100005","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

Towards Secure Smart Home IoT: Manufacturer and User Network Access Control Framework 迈向安全的智能家居物联网:制造商和用户网络访问控制框架

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-01 DOI: 10.1109/AINA.2018.00131

M. Al-Shaboti, I. Welch, Aaron Chen, M. Mahmood

{"title":"Towards Secure Smart Home IoT: Manufacturer and User Network Access Control Framework","authors":"M. Al-Shaboti, I. Welch, Aaron Chen, M. Mahmood","doi":"10.1109/AINA.2018.00131","DOIUrl":"https://doi.org/10.1109/AINA.2018.00131","url":null,"abstract":"Insecure smart home IoT network is growing in number and size, and enforcing standard security solutions in IoT is a challenge due to its limited resources. The vulnerable smart home IoT poses huge security threats. It puts smart home network security at risk as it can be used as an entry point into the network, also it exposes users' privacy due to the amount of personal data it collects. Meanwhile, as IoT increases in popularity, it has a significant impact on the security of the rest of the Internet community (e.g. forming botnets). Previous research delegates IoT security to a third party (e.g. ISP) and ignores social and contextual factor. In this paper, we propose an SDN-based framework for enforcing network static and dynamic access control, where manufacturers, security providers, and users can cooperate to enhance the smart home IoT security. Proposed approach has three features: a) it allows the manufacturers to enforce the least privileged policy for IoT, and hence reduce the risk associated with exposing IoT to the Internet; b) it enables to enforce access policy as a feedback from security services; c) it enables users to customize IoT access based on social and contextual needs (e.g. only permits LAN access to the IoT through his/her mobile), which reduce the attack surface within the network. We also proposed IPv4 ARP server as an NFV security service to mitigate ARP spoofing attack by replying to ARP requests in the network. We implement a prototype to demonstrate the functionality of the framework against common attack scenarios (i.e. network scanning, ARP spoofing).","PeriodicalId":239730,"journal":{"name":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125303559","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: 27

In-network Self-Learning Algorithms for BEMS Through a Collaborative Fog Platform 基于协同雾平台的BEMS网络自学习算法

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-01 DOI: 10.1109/AINA.2018.00166

Zhishu Shen, K. Yokota, Jiong Jin, A. Tagami, T. Higashino

{"title":"In-network Self-Learning Algorithms for BEMS Through a Collaborative Fog Platform","authors":"Zhishu Shen, K. Yokota, Jiong Jin, A. Tagami, T. Higashino","doi":"10.1109/AINA.2018.00166","DOIUrl":"https://doi.org/10.1109/AINA.2018.00166","url":null,"abstract":"Building Energy Management System (BEMS) is a vital approach in constructing a global energy-efficient environment. It can be operated by analyzing data collected from sensors located in designated indoor areas. The key is to improve the data processing results while reducing the total data processing/communication volume required in the whole Internet of Things (IoT) networks as much as possible. In this work, a novel in-network self-learning algorithm for BEMS through a collaborative Fog platform is proposed. In particular, we devise an emerging Fog computing enabled IoT network architecture, where most of data can be processed in the Sensor-to-Fog and Fog-to-Fog layers. Data processing on Cloud is only required if anomalous sensor data are detected, and thus, the energy consumption due to heavy data processing on Cloud will be significantly reduced. The proposed algorithm makes the best use of Fog node capability to realize distributed data collection and processing. Via Fog-to-Fog connections, it can examine the sensor data by collecting them from different search ranges, whose values are meanwhile optimized. Numerical experiments conducted in a real indoor environment demonstrate that our algorithm achieve a high prediction accuracy for anomaly detection even with relatively small sensor data for processing. The effectiveness of Fog node placement is also verified. The overall scheme is expected to be a feasible solution to construct a cost-effective IoT network to minimize energy consumption while maximizing the indoor user's comfort, from the perspective of achieving a high prediction accuracy in BEMS data monitoring.","PeriodicalId":239730,"journal":{"name":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115533849","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: 8

Cognitive Systems for Service Management in Cloud Computing 云计算服务管理的认知系统

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-01 DOI: 10.1109/AINA.2018.00141

U. Ogiela, M. Takizawa, L. Ogiela

引用次数: 0

Clustering Method for Characterizing Areas of Spatial Networks Based on Degree Mixing Patterns 基于程度混合模式的空间网络区域特征聚类方法

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-01 DOI: 10.1109/AINA.2018.00143

M. Arief

{"title":"Clustering Method for Characterizing Areas of Spatial Networks Based on Degree Mixing Patterns","authors":"M. Arief","doi":"10.1109/AINA.2018.00143","DOIUrl":"https://doi.org/10.1109/AINA.2018.00143","url":null,"abstract":"We address a problem of classifying and characterizing spatial networks in term of local connection patterns of node degrees, by especially focusing on property that the maximum node degree of these networks is restricted to relatively small numbers. We mainly consider spatial networks constructed from urban streets by mapping the intersections of streets into nodes and the streets between nodes into links. To this end, we propose a new clustering method for classifying and characterizing a road network automatically into some areas and characterizing them based on the tri-mixing patterns of node degrees and the K-medoids clustering algorithm. The proposed method first computes a feature vector for each node, consisting of the normalized frequency of the ego-centric tri-mixing patterns, then classifies these vector into some areas by the use of the greedy K-medoids clustering algorithm. In our experiments, using the three road networks of three cities in Shizuoka prefecture collected from OpenStreetMap(OSM), we evaluate the characteristic of our method in comparison to a variant method whose feature vectors are computed by the distance from a set of some facility positions. We show that our method can produce the clustering results comparable to those obtained by the variant method without using some extra information like facility positions.","PeriodicalId":239730,"journal":{"name":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","volume":"2533 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128693600","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

Training System Using a Force Feedback Device for Acupuncture Treatment 基于力反馈装置的针刺治疗训练系统

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-01 DOI: 10.1109/AINA.2018.00083

Meguru Yamashita, Zhiyi Gao, A. Doi, H. Ogawa

引用次数: 2

Challenges and Methodologies of Hardware Security 硬件安全的挑战和方法

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-01 DOI: 10.1109/AINA.2018.00136

K. F. Li, Narges Attarmoghaddam

引用次数: 6

Cognitive Cryptography in Advanced Data Security 高级数据安全中的认知密码学

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-01 DOI: 10.1109/AINA.2018.00111

M. Ogiela, L. Ogiela

引用次数: 2

An Eco Migration Algorithm of Virtual Machines in a Server Cluster 服务器集群中虚拟机的生态迁移算法

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) Pub Date : 2018-05-01 DOI: 10.1109/AINA.2018.00039

Dilawaer Duolikun, Ryoma Watanabe, T. Enokido, M. Takizawa

引用次数: 8