2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)最新文献_第2页

Access Control for Distributed Processing Systems: Use Cases and General Considerations 分布式处理系统的访问控制:用例和一般考虑

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00026

Ang Li, Qinghua Li, Vincent C. Hu

引用次数: 2

Towards Online Smart Disguise: Real-Time Diversification Evading Co-Residency Based Cloud Attacks 走向在线智能伪装:实时多样化规避基于共同驻留的云攻击

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00039

Mona S. Kashkoush, M. Azab, M. Eltoweissy, G. Attiya

{"title":"Towards Online Smart Disguise: Real-Time Diversification Evading Co-Residency Based Cloud Attacks","authors":"Mona S. Kashkoush, M. Azab, M. Eltoweissy, G. Attiya","doi":"10.1109/CIC.2017.00039","DOIUrl":"https://doi.org/10.1109/CIC.2017.00039","url":null,"abstract":"Security is a major challenge in Cloud Computing. Attacks exploiting resource virtualization vulnerabilities such as cross-VM side-channel, VM escape, and VM hopping constitute significant threats. Hosted VMs may act as a potential attack-source against neighboring VMs or cloud infrastructure. Inspired by the sea-chameleons camouflaging process to evade predators, in this paper we propose an Online Smart Disguise Framework (OSDF). Our OSDF employs dynamic, proactive, real-time moving target defense against cloud attacks. We realize behavior obscuring by frequently and efficiently migrating live VMs between heterogeneously configured compute nodes to avoid host-based attacks. To evaluate the efficiency of OSDF and the effectiveness of OSDF-managed frequent live migrations in limiting attack dispersion and avoiding host-based attacks, we devised the VEAR model based on the SEIR epidemic model. The SEIR model is an epidemiological model commonly used to investigate disease dispersion on cooperative communities. The implementation of OSDF is tested on OpenStack private cloud. Simulation results show the impact of the frequent VM live migration on decreasing the number of attacked VMs even for fast-spreading worms.","PeriodicalId":156843,"journal":{"name":"2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128376198","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

Service Based FOG Computing Model for IoT 基于服务的物联网 FOG 计算模型

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00031

T. Ashrafi, M. A. Hossain, Sayed Erfan Arefin, K. Das, Amitabha Chakrabarty

{"title":"Service Based FOG Computing Model for IoT","authors":"T. Ashrafi, M. A. Hossain, Sayed Erfan Arefin, K. Das, Amitabha Chakrabarty","doi":"10.1109/CIC.2017.00031","DOIUrl":"https://doi.org/10.1109/CIC.2017.00031","url":null,"abstract":"The more we are heading towards the future with ever-growing number of IoT devices which is expected to take place in a giant number almost near trillions by 2020, the data access and computing are proceeding towards more complications and impediments requiring more efficient and logical data computation infrastructures. Cloud computing is a centralized Internet based computing model which acts like a storage as well as a network connection bridge between end devices and servers. Cloud computing has been ruling as a data computation model for quite a while but if we try to concentrate on the upcoming IoT generation, the vision will become a little bit blurry as it is not possible for the present cloud computing models to deal with such huge amount of data and to rescue from this foggy situation, Fog computing model comes forward. Instead of being a replacement of the cloud computing model, Fog computing model is an extension of Cloud which works as a distributed decentralized computing infrastructure in which data compute, storage and applications are distributed in the most logical, efficient place between the data source and the cloud. In this paper, we proposed an infrastructure with collaboration of Fog computing combined with Machine-to-Machine(M2M) intelligent communication protocol followed by integration of the Service Oriented Architecture(SOA) and this model will be able to transfer data by analyzing reliably and systematically with low latency, less bandwidth, heterogeneity in less amount of time maintaining the Quality of Service(QoS) befittingly.","PeriodicalId":156843,"journal":{"name":"2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128017104","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: 11

Extracting Linked Data from HTML Tables 从HTML表中提取关联数据

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00018

Ahmed Ktob, Zhoujun Li, D. Bouchiha

引用次数: 1

Proposing and Testing New Security Cue Designs for OAuth-WebView-Embedded Mobile Applications 为嵌入oauth - webview的移动应用程序提出和测试新的安全提示设计

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00063

Fadi Mohsen, Mohamed Shehab

{"title":"Proposing and Testing New Security Cue Designs for OAuth-WebView-Embedded Mobile Applications","authors":"Fadi Mohsen, Mohamed Shehab","doi":"10.1109/CIC.2017.00063","DOIUrl":"https://doi.org/10.1109/CIC.2017.00063","url":null,"abstract":"Today, many online service providers use the WebView-OAuth implementation in their Software Development Kits (SDKs) to seamlessly integrate their services into mobile applications. This approach was proven to be a target to JavaScript injection attacks that could lead into users losing their credentials or tricked into authorizing suspicious apps on their accounts. A number of solutions came out to countermeasure these attacks. However, the majority of these solutions do not involve the users in making the prevention decision and/or do not communicate the taken decision to them. That is because of two reasons: first, the focus of these works were mainly on detecting and preventing the attacks. Second, because of the lack of effective security cue designs for the WebView-based applications context. In this paper, we aim at investigating different security cue designs to aid with keeping the users informed of whatever these solutions are practicing. Finding an effective security cue design in the mobile browsers is challenging and more so for the WebView browsers. Thus, in this work, we are proposing and testing a number of security cue designs based on their understandability, noticeability, and effectiveness by conducting an online user study of 465 users. Our study found that some of the proposed security cue designs were truly noticeably, understandable and effective in alerting users of any suspicious activity. We highly recommend these security designs to be used by numerous security tools that detect and/or prevent WebView-based attacks.","PeriodicalId":156843,"journal":{"name":"2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129286819","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

Detecting Android Malwares by Mining Statically Registered Broadcast Receivers 通过挖掘静态注册广播接收器检测Android恶意软件

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00021

Fadi Mohsen, Halil Bisgin, Z. Scott, Kyle Strait

{"title":"Detecting Android Malwares by Mining Statically Registered Broadcast Receivers","authors":"Fadi Mohsen, Halil Bisgin, Z. Scott, Kyle Strait","doi":"10.1109/CIC.2017.00021","DOIUrl":"https://doi.org/10.1109/CIC.2017.00021","url":null,"abstract":"Android has a large share in the mobile apps market which makes it attractive for both malicious and good developers. Online apps markets, despite their vetting procedures, still admit malicious apps that could be downloaded mistakenly by mobile users. Detecting Android malwares has been studied by many researchers using different approaches and techniques. The vast majority of them though were focused on using the requested permissions that are declared in the AndroidManifest. xml files. A number of researchers have considered other components of the Android applications besides the permissions such as package info, activities, and process name. Some researchers pointed out Android Broadcast receivers' component but it was not discussed thoroughly like other components. In this paper, we are conducting an empirical study to investigate the usage patterns of the Broadcast receivers component by malicious and benign Android applications. In addition to processing the AndroidManifest. xml files, the source code of malware samples, in particular the onReceive() are manually analyzed. We also propose a data mining malware detection mechanism based on the statically registered Broadcast receivers. Our research shows that Android Broadcast receivers are intensively used by malware compared to benign applications. Our Java code analysis shows that malware samples fully utilize Broadcast receivers compared to benign apps. Finally, our experiments showed that using the Broadcast receivers with permissions improves the malwares prediction accuracy.","PeriodicalId":156843,"journal":{"name":"2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123508175","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

CaCM: Context-Aware Call Management for Mobile Phones ccm:移动电话上下文感知呼叫管理

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00057

Hsien-Ming Chou, Dongsong Zhang, Lina Zhou, Yin Kang

{"title":"CaCM: Context-Aware Call Management for Mobile Phones","authors":"Hsien-Ming Chou, Dongsong Zhang, Lina Zhou, Yin Kang","doi":"10.1109/CIC.2017.00057","DOIUrl":"https://doi.org/10.1109/CIC.2017.00057","url":null,"abstract":"When a user receives a phone call, his mobile phone will normally ring or vibrate immediately regardless of whether the user is available to answer the call or not, which could be disruptive to his ongoing tasks or social situation. Mobile call management systems are a type of mobile applications for coping with the problem of mobile interruption. They aim to reduce mobile interruption through effective management of incoming phone calls and improve user satisfaction. Many existing systems often utilize only one or two types of user context (e.g., location) to determine the availability of the callee and make real-time decisions on how to handle the incoming call. In reality, however, mobile call management needs to take diverse contextual information of individual users into consideration, such as time, location, event, and social relations. The objective of this research is to propose a conceptual framework called CaCM (Context-aware Call Management) for mobile call management and implement a prototype system based on CaCM that incorporates rich context factors, including time, location, event, social relations, environment, body position, and body movement, and leverages machine learning algorithms to build call management models for individual mobile phone users. An empirical evaluation via a field study shows promising results that demonstrate the effectiveness of the proposed approach.","PeriodicalId":156843,"journal":{"name":"2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121108443","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

Detection of Phishing Webpages Using Heterogeneous Transfer Learning 基于异构迁移学习的网络钓鱼网页检测

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00034

Karl R. Weiss, T. Khoshgoftaar

{"title":"Detection of Phishing Webpages Using Heterogeneous Transfer Learning","authors":"Karl R. Weiss, T. Khoshgoftaar","doi":"10.1109/CIC.2017.00034","DOIUrl":"https://doi.org/10.1109/CIC.2017.00034","url":null,"abstract":"The detection of phishing websites using traditional machine learning methods has been demonstrated in previous studies. Traditional machine learning methods assume that the input feature space is the same between the training and testing data. There are scenarios in machine learning, where the available labeled training data has a different input feature space than the testing data. In cases where the input feature space between the testing and training data are different, traditional machine learning methods cannot be used. Heterogeneous transfer learning methods are used to transform the different input feature spaces between the testing and the training data into a unique and common set of input features. For our experiment, we construct numerous scenarios for the application of phishing website detection, where the features of the testing and training data are different. Our experiment starts with a baseline dataset for the detection of phishing websites. This baseline dataset is used to create separate training and testing datasets by splitting the features, such that the features in the training and testing data are mutually exclusive. Then, a heterogeneous transfer learning technique called Canonical Correlation Analysis is used to align the input feature space between the training and testing data. The feature aligned training and testing data is used with various traditional machine learning methods and homogeneous transfer learning methods to predict phishing websites. The performance results of the different scenarios and algorithms are reported and analyzed.","PeriodicalId":156843,"journal":{"name":"2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)","volume":"789 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134609346","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

A Comparative Study of E-Collaboration on Temporary vs. Ongoing Teams 临时团队与持续团队的电子协作比较研究

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00013

D. Kauffmann, Golan Carmi

引用次数: 3

A Comparative Study of Increasing Automation in the Integration of Multilingual Social Media Information 多语言社交媒体信息整合中日益自动化的比较研究

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC) Pub Date : 2017-10-01 DOI: 10.1109/CIC.2017.00049

Qixuan Hou, A. Musaev, Yang Yang, C. Pu

引用次数: 2