2014 Ninth Asia Joint Conference on Information Security最新文献_第3页

Acquisition of Evidence of Web Storage in HTML5 Web Browsers from Memory Image 从记忆图像中获取HTML5网络浏览器中网络存储的证据

2014 Ninth Asia Joint Conference on Information Security Pub Date : 2014-09-01 DOI: 10.1109/AsiaJCIS.2014.30

Shinichi Matsumoto, K. Sakurai

{"title":"Acquisition of Evidence of Web Storage in HTML5 Web Browsers from Memory Image","authors":"Shinichi Matsumoto, K. Sakurai","doi":"10.1109/AsiaJCIS.2014.30","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2014.30","url":null,"abstract":"Web browser is a growing platform for the execution of various applications. There are large fractions of smartphone platforms that support the execution of web technology based application, especially one such as HTML 5. However there are also some emerging smartphone platforms that only support web technology based applications. Taking into the considerations of these situations may lead to a higher importance of forensic investigations on artifacts within the web browser bringing about the usefulness of the HTML5 specific attributes as evidences in mobile forensics. Through this paper, we explore the results of experiments that acquire the main memory image within terminal and extract the webStorage data as an evidence of the browsing activity. The memory forensics of web browsing activity is highly concerned. The evidences gathered from the HTML5 webStorage contents acquired from the main memory image are examined and the results of the observations indicate the ability to retrieve webStorage from the memory image is certain. Therefore, we proclaimed formats of evidences that are retrievable from the main memory. The formats were different depending on the type of web browser accessed. Three most utilized web browsers are experimented in this paper namely, Google Chrome, Mozilla Firefox and Microsoft Internet Explorer. The results showed that the acquisition of webStorage content on the browsers were possible and elucidated its formats. Values of webStorage is contained in the residuals that left by all of three web browsers. Therefore, if the investigator has the knowledge of values, he will be able to find the location of the evidence to hint values. If the investigator does not have the knowledge about the value, then he can explore the evidence based on the knowledge of the origin or key. Because the format of the evidence depends on Web browser, investigator must use different search techniques according to the Web browser.","PeriodicalId":354543,"journal":{"name":"2014 Ninth Asia Joint Conference on Information Security","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122348402","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

Bit Security for Lucas-Based One-Way Function 基于lucas的单向函数的位安全性

2014 Ninth Asia Joint Conference on Information Security Pub Date : 2014-09-01 DOI: 10.1109/AsiaJCIS.2014.9

Si-Wei Ren, Ke Lu

引用次数: 1

Chosen-Ciphertext Secure Multi-use Unidirectional Attribute-Based Proxy Re-Encryptions 选择密文安全多用途单向基于属性的代理重加密

2014 Ninth Asia Joint Conference on Information Security Pub Date : 2014-09-01 DOI: 10.1109/AsiaJCIS.2014.15

Juanjuan Li, Zhenhua Liu, Longhui Zu

引用次数: 2

A Parameterless Learning Algorithm for Behavior-Based Detection 基于行为检测的无参数学习算法

2014 Ninth Asia Joint Conference on Information Security Pub Date : 2014-01-26 DOI: 10.1109/AsiaJCIS.2014.29

Canyong Wang, Yaokai Feng, Junpei Kawamoto, Y. Hori, K. Sakurai

{"title":"A Parameterless Learning Algorithm for Behavior-Based Detection","authors":"Canyong Wang, Yaokai Feng, Junpei Kawamoto, Y. Hori, K. Sakurai","doi":"10.1109/AsiaJCIS.2014.29","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2014.29","url":null,"abstract":"The frequency and the extent of damages caused by network attacks have been actually increasing greatly in recent years, although many approaches to avoiding and detecting attacks have been proposed in the community of network security. Thus, how to fast detect actual or potential attacks has become an urgent issue. Among the detection strategies, behavior-based ones, which use normal access patterns learned from reference data (e.g., History traffic) to detect new attacks, have attracted attention from many researchers. In each of all such strategies, a learning algorithm is necessary and plays a key role. Obviously, whether the learning algorithm can extract the normal behavior modes properly or not directly influence the detection result. However, some parameters have to determine in advance in the existing learning algorithms, which is not easy, even not feasible, in many actual applications. For example, even in the newest learning algorithm, which called FHST learning algorithm in this study, two parameters are used and they are difficult to be determined in advance. In this study, we propose a parameter less learning algorithm for the first time, in which no parameters are used. The efficiency of our proposal is verified by experiment. Although the proposed learning algorithm in this study is designed for detecting port scans, it is obviously able to be used to other behavior-based detections.","PeriodicalId":354543,"journal":{"name":"2014 Ninth Asia Joint Conference on Information Security","volume":"449 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115610617","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