Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies最新文献

An empirical study of financial incentivized question answering in social websites 社交网站财务激励问答的实证研究

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3132471

Huangxin Wang, Zhonghua Xi, Jean X. Zhang, Fei Li

引用次数: 0

Understanding the effectiveness of typosquatting techniques 了解排字技术的有效性

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3132467

Jeffrey Spaulding, Daehun Nyang, Aziz Mohaisen

{"title":"Understanding the effectiveness of typosquatting techniques","authors":"Jeffrey Spaulding, Daehun Nyang, Aziz Mohaisen","doi":"10.1145/3132465.3132467","DOIUrl":"https://doi.org/10.1145/3132465.3132467","url":null,"abstract":"The nefarious practice of Typosquatting involves deliberately registering Internet domain names containing typographical errors that primarily target popular domain names, in an effort to redirect users to unintended destinations or stealing traffic for monetary gain. Typosquatting has existed for well over two decades and continues to be a credible threat to this day. As recently shown in the online magazine Slate.com [19], cybercriminals have attempted to distribute malware through Netflix.om, a typosquatted variant of the popular streaming site Netflix.com that uses the country code top-level domain (ccTLD) for Oman (.om). While much of the prior work has examined various typosquatting techniques and how they change over time, none have considered how effective they are in deceiving users. In this paper, we attempt to fill in this gap by conducting a user study that exposes subjects to several uniform resource locators (URLs) in an attempt to determine the effectiveness of several typosquatting techniques that are prevalent in the wild. We also attempt to determine if the security education and awareness of cybercrimes such as typosquatting will affect the behavior of Internet users. Ultimately, we found that subjects tend to correctly identify typosquatting which adds characters to the domain names, while the most effective techniques to deceive users involves permutations and substitutions of characters. We also found that subjects generally performed better and faster at identifying typosquatted domain names after being thoroughly educated about them, and that certain attributes such as Age and Education affect their behavior when exposed to them.","PeriodicalId":411240,"journal":{"name":"Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131426153","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: 16

Graph-pubsub: an efficient pub/sub architecture with graph-based information relationship Graph-pubsub:一种高效的基于图的信息关系发布/订阅体系结构

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3132477

Jiachen Chen, Haoyuan Xu, Yanyong Zhang, D. Raychaudhuri

引用次数: 0

Extracting web information using representation patterns 使用表示模式提取web信息

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3133840

J. C. Roldán, Patricia Jiménez, R. Corchuelo

{"title":"Extracting web information using representation patterns","authors":"J. C. Roldán, Patricia Jiménez, R. Corchuelo","doi":"10.1145/3132465.3133840","DOIUrl":"https://doi.org/10.1145/3132465.3133840","url":null,"abstract":"Feeding decision support systems with Web information typically requires sifting through an unwieldy amount of information that is available in human-friendly formats only. Our focus is on a scalable proposal to extract information from semi-structured documents in a structured format, with an emphasis on it being scalable and open. By semi-structured we mean that it must focus on information that is rendered using regular formats, not free text; by scalable, we mean that the system must require a minimum amount of human intervention and it must not be targeted to extracting information from a particular domain or web site; by open, we mean that it must extract as much useful information as possible and not be subject to any pre-defined data model. In the literature, there is only one open but not scalable proposal, since it requires human supervision on a per-domain basis. In this paper, we present a new proposal that relies on a number of heuristics to identify patterns that are typically used to represent the information in a web document. Our experimental results confirm that our proposal is very competitive in terms of effectiveness and efficiency.","PeriodicalId":411240,"journal":{"name":"Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128882908","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

Inference attacks based on neural networks in social networks 社交网络中基于神经网络的推理攻击

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3132469

Bo Mei, Yinhao Xiao, Hong Li, Xiuzhen Cheng, Yunchuan Sun

{"title":"Inference attacks based on neural networks in social networks","authors":"Bo Mei, Yinhao Xiao, Hong Li, Xiuzhen Cheng, Yunchuan Sun","doi":"10.1145/3132465.3132469","DOIUrl":"https://doi.org/10.1145/3132465.3132469","url":null,"abstract":"In modern society, social networks play an important role for online users. However, one unignorable problem behind the booming of the services is privacy issues. At the same time, neural networks have been swiftly developed in recent years, and are proved to be very effective in inference attack. This paper conducts an extensive study to infer sensitive personal information from public insensitive attributes in social networks by deploying fully connected neural networks. Correlation matrices and the details of constructing neural networks for social networks are elaborated. To show the advantages of neural networks on inference attack, different traditional machine learning algorithms are also studied. The results show that neural networks can achieve about 4 times of the baseline accuracy to classify low-correlation, high-noise dataset to infer sensitive users' attributes. In addition, neural networks outperform all the selected traditional algorithms. Outcomes from the study are deliberately discussed, and the limitations of both neural networks and traditional machine learning algorithms are also illustrated.","PeriodicalId":411240,"journal":{"name":"Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132583368","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: 7

Rethinking information sharing for threat intelligence 重新思考威胁情报的信息共享

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3132468

Aziz Mohaisen, Omar Al-Ibrahim, C. Kamhoua, K. Kwiat, L. Njilla

引用次数: 17

Precog: action-based time-shifted prefetching for web applications on mobile devices Precog:移动设备上web应用程序的基于动作的时移预取

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3132473

Shruti Sanadhya, U. Moravapalle, Kyu-Han Kim, Raghupathy Sivakumar

引用次数: 5

Automated least privileges in cloud-based web services 基于云的web服务中的自动最小权限

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3132470

M. Sanders, Chuan Yue

引用次数: 6

A knowledge and reasoning toolkit for cognitive applications 认知应用的知识和推理工具包

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3132478

Mustafa Canim, Cristina Cornelio, Robert G. Farrell, Achille Fokoue, K. Y. Gao, J. Gunnels, A. Iyengar, Ryan Musa, M. Rodriguez-Muro, Rosario A. Uceda-Sosa

引用次数: 1

Edge computing enabled smart firefighting: opportunities and challenges 边缘计算实现智能消防:机遇与挑战

Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies Pub Date : 2017-10-14 DOI: 10.1145/3132465.3132475

Xiaopei Wu, R. Dunne, Qingyang Zhang, Weisong Shi

{"title":"Edge computing enabled smart firefighting: opportunities and challenges","authors":"Xiaopei Wu, R. Dunne, Qingyang Zhang, Weisong Shi","doi":"10.1145/3132465.3132475","DOIUrl":"https://doi.org/10.1145/3132465.3132475","url":null,"abstract":"By collectively leveraging advanced communications systems, sensing, drones, wearable technologies and large-scale data analysis, smart firefighting is envisioned as the next generation firefighting with the capacities of gathering massive real-time scene data, transferring them into useful information and insights for fire responders, and even providing them with more safe and accurate decisions. For smart firefighting, timeliness and accuracy are two foremost system requirements, yet they are unsatisfied in many applications. One reason for such dilemma is due to the underlying used computing architecture (i.e. cloud computing) that can produce extra latency in large-scale data transmission. To address this problem, we explore the firefighting field utilizing edge computing and discuss the overall system architecture, opportunities, challenges, as well as some early technical suggestions on building edge-enabled smart firefighting. To validate the feasibility of edge computing, we simulate the firefighting context and respectively deploy a video-based flame detection algorithm on a local Intel's edge computing platform and a remote Amazon EC2. The preliminary results show that edge computing can significantly increase system's reactive speed, with on average 50% reduction in system latency.","PeriodicalId":411240,"journal":{"name":"Proceedings of the fifth ACM/IEEE Workshop on Hot Topics in Web Systems and Technologies","volume":"364 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123193081","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: 26