2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)最新文献_第3页

Proactive Phishing Sites Detection 主动网络钓鱼网站检测

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3352565

Akihito Nakamura, Fuma Dobashi

{"title":"Proactive Phishing Sites Detection","authors":"Akihito Nakamura, Fuma Dobashi","doi":"10.1145/3350546.3352565","DOIUrl":"https://doi.org/10.1145/3350546.3352565","url":null,"abstract":"Phishing is one of the social engineering techniques to steal users’ sensitive information by disguising a fake Web site as a trustworthy one. Previous research proposed phishing mitigation techniques, such as blacklist, heuristics, visual similarity, and machine learning. However, these kinds of methods have limitation on the detection of a zero-hour phishing site, a phishing site that no one has noticed yet. This paper presents a new approach to the detection of zero-hour phishing sites: proactive detection. If those malicious sites are detected as early as possible, shutdown by the specialized agencies and mitigation of user damages are expected. We also present a method and system of efficient phishing site detection based on the proactive approach. The method is composed of two major parts: suspicious domain names generation and judgment. The former predicts likely phishing Web sites from the given legitimate brand domain name. The latter scores and judges suspects by calculating various indexes. That is, zero-hour phishing sites can be detected by hypothesis and test cycles. As a result of the preliminary experiment, we detected several zero-hour phishing sites disguising as major brands, including eBay, Google, and Amazon. CCS CONCEPTS • Security and privacy $rightarrow$ Phishing; Social network security and privacy.","PeriodicalId":171168,"journal":{"name":"2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115363103","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

A News Recommender System for Media Monitoring 面向媒体监控的新闻推荐系统

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3352510

F. Barile, F. Ricci, M. Tkalcic, B. Magnini, Roberto Zanoli, A. Lavelli, Manuela Speranza

引用次数: 6

Sentinel Nodes Identification for Infectious Disease Surveillance on Temporal Social Networks 基于时间社会网络的传染病监测前哨节点识别

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3360739

Jiachen Geng, Yuanxi Li, Z. Zhang, Li Tao

{"title":"Sentinel Nodes Identification for Infectious Disease Surveillance on Temporal Social Networks","authors":"Jiachen Geng, Yuanxi Li, Z. Zhang, Li Tao","doi":"10.1145/3350546.3360739","DOIUrl":"https://doi.org/10.1145/3350546.3360739","url":null,"abstract":"Active surveillance, which aims at detecting and controlling infectious diseases at an early stage, is essential to prevent the spread of infections, protect people’s health, and promote social good. One difficult problem in active surveillance is how to intelligently sample a small group of nodes as sentinels from a large number of individuals for detecting the outbreaks of infectious diseases as early as possible. To sample sentinels, the existing methods depending on the global information about a social network are infeasible for mapping out social connections is time-consuming and inaccurate. Instead, some existing studies utilize local information about individuals’ connected neighbors to heuristically select sentinels. However, few of them take into account the temporal structure of social connections, which is believed to have a direct effect on the spread of infectious diseases. In this paper, we propose two temporal-network surveillance strategies for selecting sentinels based on the friendship paradox theory, a sociological theory describing a phenomenon in social networks that most people have fewer friends than their friends have. By simulating our strategies with three existing strategies based on the susceptible-infected (SI) model, the results show that our proposed 1st AN and 2nd RN strategies can detect the outbreak of infectious diseases earlier than the other strategies on the synthetic temporal network and two real-world temporal social networks, respectively. CCS CONCEPTS • Social and professional topics → Surveillance; • Networks;","PeriodicalId":171168,"journal":{"name":"2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117063388","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

Preference Networks and Non-Linear Preferences in Group Recommendations 群体推荐中的偏好网络和非线性偏好

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3352556

Amra Delic, F. Ricci, J. Neidhardt

引用次数: 10

Joint Heterogeneous Pair-wise Loss For Top-N Recommendation Top-N推荐的联合异构成对损失

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3352517

Jin Yi, Jiajin Huang, Jin Qin, Yuan Luo

引用次数: 0

Implementing an Urban Dynamic Traffic Model 实现城市动态交通模型

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3352537

Chiara Bachechi, Laura Po

{"title":"Implementing an Urban Dynamic Traffic Model","authors":"Chiara Bachechi, Laura Po","doi":"10.1145/3350546.3352537","DOIUrl":"https://doi.org/10.1145/3350546.3352537","url":null,"abstract":"The world of mobility is constantly evolving and proposing new technologies, such as autonomous driving, electromobility, shared-mobility or even new air transport systems. We do not know how people and things will be moving within cities in 30 years, but for sure we know that road network planning and traffic management will remain critical issues. The goal of our research is the implementation of a data-driven micro-simulation traffic model for computing everyday simulations of road traffic in a medium-sized city. A dynamic traffic model is needed in every urban area, we introduce an easy-to-set-up solution for cities that already have traffic sensors installed. Daily traffic flows are created from real data measured by induction loop detectors along the urban roads in Modena. The result of the simulation provides a set of \"snapshots\" of the traffic flow within the Modena road network every minute. The main contribution of the implemented model is the ability, starting from traffic punctual information on 400 locations, to provide an overview of traffic intensity on more than 800 km of roads. CCS CONCEPTS • Computing methodologies → Model development and analysis; Modeling methodologies; • Human-centered computing → Visualization.","PeriodicalId":171168,"journal":{"name":"2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132181547","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: 10

An Assessment of Blockchain Identity Solutions: Minimizing Risk and Liability of Authentication 区块链身份解决方案评估:最小化认证风险和责任

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3352497

Rima Rana, Razieh Nokhbeh Zaeem, K. S. Barber

{"title":"An Assessment of Blockchain Identity Solutions: Minimizing Risk and Liability of Authentication","authors":"Rima Rana, Razieh Nokhbeh Zaeem, K. S. Barber","doi":"10.1145/3350546.3352497","DOIUrl":"https://doi.org/10.1145/3350546.3352497","url":null,"abstract":"Personally Identifiable Information (PII) is often used to perform authentication and acts as a gateway to personal and organizational information. One weak link in the architecture of identity management services is sufficient to cause exposure and risk identity. Recently, we have witnessed a shift in identity management solutions with the growth of blockchain. Blockchain—the decentralized ledger system—provides a unique answer addressing security and privacy with its embedded immutability. In a blockchain-based identity solution, the user is given the control of his/her identity by storing personal information on his/her device and having the choice of identity verification document used later to create blockchain attestations. Yet, the blockchain technology alone is not enough to produce a better identity solution. The user cannot make informed decisions as to which identity verification document to choose if he/she is not presented with tangible guidelines. In the absence of scientifically created practical guidelines, these solutions and the choices they offer may become overwhelming and even defeat the purpose of providing a more secure identity solution.We analyze different PII options given to users for authentication on current blockchain-based solutions. Based on our Identity Ecosystem model, we evaluate these options and their risk and liability of exposure. Powered by real world data of about 6,000 identity theft and fraud stories, our model recommends some authentication choices and discourages others. Our work paves the way for a truly effective identity solution based on blockchain by helping users make informed decisions and motivating blockchain identity solution providers to introduce better options to their users.CCS CONCEPTS• Security and privacy → Privacy protections; • Social and professional topics → Privacy policies; • Applied computing → Digital cash.","PeriodicalId":171168,"journal":{"name":"2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133888419","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: 25

REALM: An Altmetrics-based Framework to Map Science Impacts on Society. A Case Study on Zika Research REALM:一个基于替代度量的框架来描绘科学对社会的影响。寨卡病毒研究个案研究

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3352523

Luís Fernando Monsores Passos Maia, M. Lenzi, E. Rabello, Jonice Oliveira

引用次数: 4

An efficient co-Attention Neural Network for Social Recommendation 一种高效的社会推荐协同注意神经网络

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3352498

Munan Li, K. Tei, Y. Fukazawa

{"title":"An efficient co-Attention Neural Network for Social Recommendation","authors":"Munan Li, K. Tei, Y. Fukazawa","doi":"10.1145/3350546.3352498","DOIUrl":"https://doi.org/10.1145/3350546.3352498","url":null,"abstract":"The recent boom in social networking services has prompted the research of recommendation systems. The basic assumption behind these works was that \"users’ preference is similar to or influenced by their friends\". Although many studies have attempted to use social relations to enhance recommendation system, they neglected that the heterogeneous nature of online social networks and the variations in users' trust of friends according to different items. As a natural symmetry between the latent preference vector of the user and her friends, we propose a new social recommendation method called ScAN (short for “co-Attention Neural Network for Social Recommendation”). ScAN is based on a co-attention neural network, which learns the influence value between the user and her friends from the historical data of the interaction between the user/her friends and an item. When the user interacts with different items, different attention weights are assigned to the user and her friends respectively, and the user’s new latent preference feature is obtained through an aggregation strategy. To enhance the recommendation performance, a network embedding technique is utilized as a pre-training strategy to extract the users’ embedding and to incorporate the extracted factors into the neural network model. By conducting extensive experiments on three different real-world datasets, we demonstrate that our proposed method ScAN achieves a superior performance for all datasets compare with state-of-the-art baseline methods in social recommendation task.CCS CONCEPTS• Information systems → Recommender systems • Computing methodologies → Machine learning","PeriodicalId":171168,"journal":{"name":"2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115308180","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

SentiLangN: A Language-Neutral Graph-Based Approach for Sentiment Analysis in Microblogging Data sentilang:一种语言中立的基于图的微博数据情感分析方法

2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2019-10-01 DOI: 10.1145/3350546.3352568

M. Abulaish, M. Rahimi, Habeebullah Ebrahemi, Amit Kumar Sah

引用次数: 1