智能手机点击劫持攻击检测方法研究

点击劫持通过欺骗用户点击经过伪装的界面元素达到攻击目的。移动互联网环境下,智能手机的屏幕特征、手势识别、HTML5支持度高等特性成为点击劫持新的利用点。深入分析并实验验证智能手机脆弱特性,在此基础上提出点击劫持在智能手机上的潜在攻击方案。进而设计并实现一套有针对性的检测方案。该方案从静态页面和动态行为两个角度提取攻击特征,并进行基于规则的量化评估与组合判定。实验结果表明该方案可以有效地降低传统页面特征检测方案的漏报和误报情况。     

一种基于浏览代价优化的电视网页重构方法

随着智能家庭概念的发展与推广,出现了大量面向电视机用户的Web应用。由于用户与电视机之间通过遥控的方式进行交互,一方面使得网页浏览代价受页面元素排布的影响较大,而另一方面,电视机网页元素类型和数量少的特点,使得对其进行自动优化成为可能。考虑到包括按键式遥控器、手势、触屏等电视机交互方式,根据不同的交互方式的特点提出了页面浏览代价的计算方法;考虑到元素类型、位置、大小、内容关键字、网页结构等信息,提出了一种页面元素可替换性评估方法;在这两种方法的基础上,基于网页浏览代价全局最小化的原则,提出了根据页面的访问情况动态对网页进行自动重构的方法。在一个包含116个页面的电视机Web应用中采用该方法进行的实验验证了方法的正确性和有效性。     

Exploiting User Interests to Characterize Navigational Patterns in Web Browsing Assistance

In order to be capable of exploiting context for pro-active information recommendation, agents need to extract and understand user activities based on their knowledge of the user interests. In this paper, we propose a novel approach for context-aware recommendation in browsing assistants based on the integration of user profiles, navigational patterns and contextual elements. In this approach, user profiles built using an unsupervised Web page clustering algorithm are used to characterize user ongoing activities and behavior patterns. Experimental evidence show that using longer-term interests to explain active browsing goals user assistance is effectively enhanced.

Using VRML-based visualisations to facilitate information retrieval in the world wide web

With the explosive growth of information in the WWW, it is becoming increasingly difficult for the user to find information of interest. Visualisations may be helpful in assisting the users in their information retrieval task. Effective visualisation of the structure of a WWW site is extremely useful for browsing through the site. Visualisation can also be used to augment a WWW search engine when too many or too few results are retrieved. In this paper, we discuss several visualisations we have developed to facilitate information retrieval on the WWW. With VRML becoming the standard for graphics on the Web and efficient VRML browsers becoming available, VRML was used for developing these visualisations. Unique visualisations like focus + context views of WWW nodes and semantic visualisation are presented and examples are given on scenarios where the visualisations are useful.     

B-hist: Entity-centric search over personal web browsing history

Web Search is increasingly entity centric; as a large fraction of common queries target specific entities, search results get progressively augmented with semi-structured and multimedia information about those entities. However, search over personal web browsing history still revolves around keyword-search mostly. In this paper, we present a novel approach to answer queries over web browsing logs that takes into account entities appearing in the web pages, user activities, as well as temporal information. Our system, B-hist, aims at providing web users with an effective tool for searching and accessing information they previously looked up on the web by supporting multiple ways of filtering results using clustering and entity-centric search. In the following, we present our system and motivate our User Interface (UI) design choices by detailing the results of a survey on web browsing and history search. In addition, we present an empirical evaluation of our entity-based approach used to cluster web pages.     

Adaptively browsing image databases with PIBE

Browsing large image collections is a complex and often tedious task, due to the semantic gap existing between the user subjective notion of similarity and the one according to which a browsing system organizes the images. In this paper we propose PIBE, an adaptive image browsing system, which provides users with a hierarchical view of images (the Browsing Tree) that can be customized according to user preferences. A key feature of PIBE is that it maintains local similarity criteria for each portion of the Browsing Tree. This makes it possible both to avoid costly global reorganization upon execution of user actions and, combined with a persistent storage of the Browsing Tree, to efficiently support multiple browsing tasks. We present the basic principles of PIBE and report experimental results showing the effectiveness of its browsing and personalization functionalities.     

基于Web使用挖掘技术的个性化教育网站构筑

本文介绍了个性化网络教育的特点，对在Web服务器端和客户端进行学生浏览路径模式采集的各种方法进行了分析，探讨了如何将Web使用挖掘技术应用到个性化网络教育，最后介绍了由我们开发的个性化教育网站。     

新客户在商务站点中的个性化推荐

提出了一种针对新客户在商务站点购物的个性化推荐方法。首先利用已购物客户的浏览信息生成购物行为模型,得到新客户在站点中的浏览行为生成浏览行为模型,通过最近邻居的协同过滤技术生成与新客户行为最为相近的用户集,将最近邻居已购商品推荐给新客户。该方法能够给新客户提供及时准确的个性化商品信息。     

Visual guided navigation for image retrieval

In this work, we are interested in technologies that will allow users to actively browse and navigate large image databases and to retrieve images through interactive fast browsing and navigation. The development of a browsing/navigation-based image retrieval system has at least two challenges. The first is that the system's graphical user interface (GUI) should intuitively reflect the distribution of the images in the database in order to provide the users with a mental picture of the database content and a sense of orientation during the course of browsing/navigation. The second is that it has to be fast and responsive, and be able to respond to users actions at an interactive speed in order to engage the users. We have developed a method that attempts to address these challenges of a browsing/navigation based image retrieval systems. The unique feature of the method is that we take an integrated approach to the design of the browsing/navigation GUI and the indexing and organization of the images in the database. The GUI is tightly coupled with the algorithms that run in the background. The visual cues of the GUI are logically linked with various parts of the repository (image clusters of various particular visual themes) thus providing intuitive correspondences between the GUI and the database contents. In the backend, the images are organized into a binary tree data structure using a sequential maximal information coding algorithm and each image is indexed by an n-bit binary index thus making response to users’ action very fast. We present experimental results to demonstrate the usefulness of our method both as a pre-filtering tool and for developing browsing/navigation systems for fast image retrieval from large image databases.     

Interactive visualization for opportunistic exploration of large document collections

Finding relevant information in a large and comprehensive collection of cross-referenced documents like Wikipedia usually requires a quite accurate idea where to look for the pieces of data being sought. A user might not yet have enough domain-specific knowledge to form a precise search query to get the desired result on the first try. Another problem arises from the usually highly cross-referenced structure of such document collections. When researching a subject, users usually follow some references to get additional information not covered by a single document. With each document, more opportunities to navigate are added and the structure and relations of the visited documents gets harder to understand.