By Topic

Applications and the Internet (SAINT), 2012 IEEE/IPSJ 12th International Symposium on

Date 16-20 July 2012

Filter Results

Displaying Results 1 - 25 of 90
  • [Back cover]

    Page(s): C4
    Save to Project icon | Request Permissions | PDF file iconPDF (437 KB)  
    Freely Available from IEEE
  • [Title page i]

    Page(s): i
    Save to Project icon | Request Permissions | PDF file iconPDF (62 KB)  
    Freely Available from IEEE
  • [Title page iii]

    Page(s): iii
    Save to Project icon | Request Permissions | PDF file iconPDF (110 KB)  
    Freely Available from IEEE
  • [Copyright notice]

    Page(s): iv
    Save to Project icon | Request Permissions | PDF file iconPDF (118 KB)  
    Freely Available from IEEE
  • Table of contents

    Page(s): v - xii
    Save to Project icon | Request Permissions | PDF file iconPDF (149 KB)  
    Freely Available from IEEE
  • Message from General Chairs

    Page(s): xiii
    Save to Project icon | Request Permissions | PDF file iconPDF (149 KB)  
    Freely Available from IEEE
  • Message from Program Chairs

    Page(s): xiv
    Save to Project icon | Request Permissions | PDF file iconPDF (121 KB)  
    Freely Available from IEEE
  • Message from Workshop Co-chairs

    Page(s): xv
    Save to Project icon | Request Permissions | PDF file iconPDF (137 KB)  
    Freely Available from IEEE
  • Message from Doctoral Symposium Co-chairs

    Page(s): xvi
    Save to Project icon | Request Permissions | PDF file iconPDF (135 KB)  
    Freely Available from IEEE
  • Organizing Committee

    Page(s): xvii - xviii
    Save to Project icon | Request Permissions | PDF file iconPDF (95 KB)  
    Freely Available from IEEE
  • Program Committee

    Page(s): xix - xxii
    Save to Project icon | Request Permissions | PDF file iconPDF (109 KB)  
    Freely Available from IEEE
  • Reviewers

    Page(s): xxiii - xxvi
    Save to Project icon | Request Permissions | PDF file iconPDF (111 KB)  
    Freely Available from IEEE
  • Message from HSNCE 2012 Workshop Organizers

    Page(s): xxvii
    Save to Project icon | Request Permissions | PDF file iconPDF (142 KB)  
    Freely Available from IEEE
  • Message from WS-ITeS 2012 Workshop Organizers

    Page(s): xxviii
    Save to Project icon | Request Permissions | PDF file iconPDF (132 KB)  
    Freely Available from IEEE
  • Message from NETSAP 2012 Workshop Organizers

    Page(s): xxix
    Save to Project icon | Request Permissions | PDF file iconPDF (121 KB)  
    Freely Available from IEEE
  • Message from HEUNET 2012 Workshop Organizers

    Page(s): xxx
    Save to Project icon | Request Permissions | PDF file iconPDF (139 KB)  
    Freely Available from IEEE
  • Message from C3NET 2012 Workshop Organizers

    Page(s): xxxi
    Save to Project icon | Request Permissions | PDF file iconPDF (122 KB)  
    Freely Available from IEEE
  • Message from EUCASS 2012 Workshop Organizers

    Page(s): xxxii
    Save to Project icon | Request Permissions | PDF file iconPDF (121 KB)  
    Freely Available from IEEE
  • HEUNET 2012 Plenary Speakers

    Page(s): xxxiii
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (135 KB)  

    These plenary speeches discuss the following: Heuristics and Metaheuristics for Practical Optimisation in Wireless Networks and The Cloudy Sky of Programmable Infrastructures. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Location l-Diversity against Multifarious Inference Attacks

    Page(s): 1 - 10
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1080 KB) |  | HTML iconHTML  

    The increasing use of location-based services leads these users to publish their locations unintentionally. Adversarial attackers can identify the user and find sensitive locations where the user often visits. Although l-diversity can be applied to location data and protect the user's privacy by preserving variations of locations, it does not consider the difference of the adversary's knowledge and does not properly address each sensitive location. The sensitive locations vary depending on the adversary's knowledge which reflects the relationship between the adversary and the user. In this paper, we introduce multi-dimensional l-diversity (MDlD), an enhancement of location l-diversity, to control the privacy risk from published locations by considering the specific knowledge that an adversary has on the user. We also propose an anonymization algorithm that adopts both generalization and suppression of locations to satisfy the MDlD. To reduce information loss and to preserve the number of locations for each user as much as possible, our algorithm applies generalization preferentially to suppression. We also show the practicality of our algorithm based on experimental results which used two real world datasets. The results show the fact that MDlD enables the publication of precise enough location information while still preserving user's privacy. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Proposal of Movie CAPTCHA Method Using Amodal Completion

    Page(s): 11 - 18
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (376 KB) |  | HTML iconHTML  

    Web services accounts have recently been automatically acquired in large quantities by bot-programs, which are malicious. Furthermore, the acquired accounts have been used for spamming, which is a problem for service operators or Internet users. Completely Automated Public Turing Tests To Tell Computers and Humans Apart (CAPTCHAs) have generally been adopted for Web Services as a method of preventing Web services accounts from being acquired. These are Turing tests for users of Web services to distinguish between humans and bot-programs. There are several types of methods in CAPTCHAs, but the most typical in this field are text-based. However, these methods can be decoded with a high degree of probability, because of the OCR technology that has evolved. Much research on resolving this problem has been proposed. For example, one method in this research adds distortion to characters to make it difficult to analyze them with OCR. Despite this research, OCR has a higher success rate than humans. Thus, we propose a practical method for CAPTCHA in this paper in which only humans can provide correct answers by applying a modal completion. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Design and Implementation of a Secure Public Wireless Internet Service Model Using Host Identity Protocol

    Page(s): 19 - 28
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4675 KB) |  | HTML iconHTML  

    In an ideal ubiquitous network, everyone can access the Internet when some connectivity exists there. A network administrator is supposed to provide a connection to public visitors securely. In this paper, we propose a secure public wireless Internet service model using Host identity Protocol (HIP). Services based on the model allow everyone to provide a connection. We give some consideration to its risks. Our goal is to implement and evaluate the model. The network administrator is responsible for tracing malicious users who attempt to access a global network. We call this traceability ensurance. In conventional Internet access services, a malicious user who has attacked someone can make excuses and may put the blame on the network administrator. The network administrator wants to prove that he himself has not committed malicious accesses, and to make sure that the malicious user cannot put the blame on others, that is, nonrepudiation should be ensured. To authenticate users, the network administrator needs to manage many accounts and take logs. If a malicious user attacks a correspondent, he or she may raise a complaint to the administrator. They are the burden for the network administrator. Our model ensures the traceability of users and the nonrepudiation. Our model also reduces the management work of network administrators. Installation cost of our model is low because we apply HIP without any modification, thus the network administrator can provide and the users can use the network securely without adopting a complex system. To protect from some attacks, we implement a gateway system. As a qualitative evaluation, we confirm that the system works in the real environment. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Detecting Malicious Websites by Learning IP Address Features

    Page(s): 29 - 39
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (399 KB) |  | HTML iconHTML  

    Web-based malware attacks have become one of the most serious threats that need to be addressed urgently. Several approaches that have attracted attention as promising ways of detecting such malware include employing various blacklists. However, these conventional approaches often fail to detect new attacks owing to the versatility of malicious websites. Thus, it is difficult to maintain up-to-date blacklists with information regarding new malicious websites. To tackle this problem, we propose a new method for detecting malicious websites using the characteristics of IP addresses. Our approach leverages the empirical observation that IP addresses are more stable than other metrics such as URL and DNS. While the strings that form URLs or domain names are highly variable, IP addresses are less variable, i.e., IPv4 address space is mapped onto 4-bytes strings. We develop a lightweight and scalable detection scheme based on the machine learning technique. The aim of this study is not to provide a single solution that effectively detects web-based malware but to develop a technique that compensates the drawbacks of existing approaches. We validate the effectiveness of our approach by using real IP address data from existing blacklists and real traffic data on a campus network. The results demonstrate that our method can expand the coverage/accuracy of existing blacklists and also detect unknown malicious websites that are not covered by conventional approaches. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Scalable and Performance-Efficient Client Honeypot on High Interaction System

    Page(s): 40 - 50
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (477 KB) |  | HTML iconHTML  

    We investigated client honeypots for detecting and circumstantially analyzing drive-by download attacks. A client honeypot requires both improved inspection performance and in-depth analysis for inspecting and discovering malicious websites. However, OS overhead in recent client honeypot operation cannot be ignored for improving honeypot multiplication performance. We propose a client honeypot client system that uses our proposed multi-OS and multi-process honeypot multiplication approaches and implemented this system to evaluate its performance. Our process sandbox mechanism, a security measure for our multi-process approach, creates a virtually isolated environment for each web browser. In a field trial, we confirmed that the use of our multi-process approach was three or more times faster than that of a single process and [our multi-OS approach lineally improved system performance according to the number of honeypot instances. Thus, our proposed multiplication approaches improve performance efficiency and enables in-depth analysis on high interaction systems. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • SSH Dictionary Attack Detection Based on Flow Analysis

    Page(s): 51 - 59
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (210 KB) |  | HTML iconHTML  

    SSH services are run on many hosts with various scopes other than just operation, so dictionary attack against the service is a common security threat. SANS has reported the emergence of distributed SSH dictionary attacks, which are very stealthy in comparison with a simple one. Since even one success of such an attack causes serious problems, administrators should implement countermeasures. SSH dictionary attacks have been detected in two basic ways that rely on either log files or network traffic. Both approaches, however, have limitations. The first approach imposes upon administrators heavy maintenance costs, which grow linearly with the number of hosts in networks. The second approach cannot distinguish between successful and unsuccessful attacks. Of more immediate concern, neither approach is effective against stealthy attacks because the login attempts of these attacks have little impact on log files or network traffic. An ideal method would be able to detect individual attacks and distinguish between an attack's success or failure, using information derived from only network traffic. In this paper, we describe such a method, which was developed by combining two novel elements. First, on the basis of our assumptions, we use two criteria: "existence of a connection protocol" and "difference in the inter-arrival time of an auth-packet". These criteria are not available, though, owing to the confidentiality and flexibility of the SSH protocol. Second, we resolve this problem by identifying transition points of a sub-protocol through flow features and machine learning algorithms. We evaluate the effectiveness of the proposed method through experiments on real traffic traces collected at the edge in our campus networks. The experimental results are encouraging for this research direction, though they are derived from reduced datasets of SSH dictionary attacks and under simplifying assumptions. The significant contribution is the demonstration that an ideal metho- for detecting SSH dictionary attacks seems feasible. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.