• Title/Summary/Keyword: Cross-service 공격

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The proposal of detection mechanism against Cross-service attack (Cross-service 공격 탐지를 위한 메커니즘 제안)

  • Oh, Seung-Hee;Han, Jong-Wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.647-650
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    • 2008
  • 네트워크 환경이 컨버젼스(convergence)되면서 하나의 단말에서 제공하는 서비스 역시 다양화되고 있다. 개인용 휴대 단말들도 기존에 개별 기능만을 주로 다루던 형태에서 다양한 융복합 서비스를 하나의 단말에서 제공하는 형태로 발전하고 있다. 따라서 본 논문에서는 컨버젼스 네트워크 환경에서 제공되는 여러 서비스를 동시에 지원하는 단말을 "복합단말(All-in-one Mobile Device)"이라 정의한다. 복합단말은 기능, 성능, 네트워크 인터페이스 측면에서 다양한 컨버젼스가 제공되고 있는데, 이 중에서 다양한 네트워크 인터페이스의 제공으로 인터페이스간 교차로 인해 기존에 존재하지 않았던 새로운 형태의 보안 위협인 Cross-service 공격이 등장하고 있다. 기존 모바일 디바이스와는 달리 복합단말에서의 Cross-service 공격은 사용자에게 과금이나 배터리 소모와 같은 치명적인 문제점을 발생시킨다. 본 논문에서는 Cross-service 공격으로부터 복합단말을 보호하기 위한 탐지 메커니즘 및 보안 요구사항을 제시한다.

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An IDS in MANET with Cross Layer Concept (크로스 층에서의 MANET을 이용한 IDS)

  • Kim, Sang-Eun;Han, Seung-Jo
    • Journal of Advanced Navigation Technology
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    • v.14 no.1
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    • pp.41-48
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    • 2010
  • Intrusion detection forms a vital component of internet security. To keep pace with the growing trends, there is a critical need to replace single layer detection technology with multi layer detection. Different types of Denial of Service (DoS) attacks thwart authorized users from gaining access to the networks and we tried to detect as well as alleviate some of those attacks. We have proposed a novel cross layer intrusion detection architecture to discover the malicious nodes. The information available across different layers of protocol stack are exploited in order to improve the accuracy of detection. We have used cooperative and distributive anomaly intrusion detection with data mining technique to enhance the proposed architecture. The simulation of the proposed architecture is done in OPNET simulator and the results are analyzed.

Implementation of the Personal Information Infringement Detection Module in the HTML5 Web Service Environment (HTML5 웹 서비스 환경에서의 개인정보 침해 탐지 모듈 구현)

  • Han, Mee Lan;Kwak, Byung Il;Kim, Hwan Kuk;Kim, Huy Kang
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.4
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    • pp.1025-1036
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    • 2016
  • The conversion of the international standard web utilization HTML5 technology is being developed for improvement of the internet environment based on nonstandard technology like ActiveX. Hyper Text Markup Language 5 (HTML5) of basic programming language for creating a web page is designed to consider the security more than HTML4. However, the range of attacks increased and a variety of security threats generated from HTML4 environment inherited by new HTML5 API. In this paper, we focus on the script-based attack such as CSRF (Cross-Site Request Forgery), Cookie Sniffing, and HTML5 API such as CORS (Cross-Origin Resource Sharing), Geolocation API related with the infringement of the personal information. We reproduced the infringement cases actually and embodied a detection module of a Plug-in type diagnosed based on client. The scanner allows it to detect and respond to the vulnerability of HTML5 previously, thereby self-diagnosing the reliability of HTML5-based web applications or web pages. In a case of a new vulnerability, it also easy to enlarge by adding another detection module.

Detecting Malicious Scripts in Web Contents through Remote Code Verification (원격코드검증을 통한 웹컨텐츠의 악성스크립트 탐지)

  • Choi, Jae-Yeong;Kim, Sung-Ki;Lee, Hyuk-Jun;Min, Byoung-Joon
    • The KIPS Transactions:PartC
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    • v.19C no.1
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    • pp.47-54
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    • 2012
  • Sharing cross-site resources has been adopted by many recent websites in the forms of service-mashup and social network services. In this change, exploitation of the new vulnerabilities increases, which includes inserting malicious codes into the interaction points between clients and services instead of attacking the websites directly. In this paper, we present a system model to identify malicious script codes in the web contents by means of a remote verification while the web contents downloaded from multiple trusted origins are executed in a client's browser space. Our system classifies verification items according to the origin of request based on the information on the service code implementation and stores the verification results into three databases composed of white, gray, and black lists. Through the experimental evaluations, we have confirmed that our system provides clients with increased security by effectively detecting malicious scripts in the mashup web environment.

Vulnerability Analysis of the Creativity and Personality Education based on Digital Convergence Curation System (창의·인성 교육기반의 디지털 융합 큐레이션 시스템에 관한 취약점 분석)

  • Shin, Seung-Soo;Kim, Jung-In;Youn, Jeong-Jin
    • Journal of the Korea Convergence Society
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    • v.6 no.4
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    • pp.225-234
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    • 2015
  • With the growing number of people that use web services, the perception of the importance of securing web applications is also increasing. There are many different types of attacks that target web applications. In the rapidly-changing knowledge and information society, which came into being with the advancements made in information and communication technology, there is currently an urgent need for building web sites for the purposes of developing one's creativity and character. In this paper, attack schemes that use SQL injections and XSS and target educational digital curation systems which provide educational contents with the aim of developing of one's creativity and character are analyze, in terms of how the attacks are carried out and their vulnerabilities. Furthermore, it suggests ways of dealing appropriately with these web-based attacks that use SQL injections and XSS.

A Study of Development of Diagnostic System for Web Application Vulnerabilities focused on Injection Flaws (Injection Flaws를 중심으로 한 웹 애플리케이션 취약점 진단시스템 개발)

  • Kim, Jeom-Goo;Noh, Si-Choon;Lee, Do-Hyeon
    • Convergence Security Journal
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    • v.12 no.3
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    • pp.99-106
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    • 2012
  • Today, the typical web hacking attacks are cross-site scripting(XSS) attacks, injection vulnerabilities, malicious file execution and insecure direct object reference included. Web hacking security systems, access control solutions, access only to the web service and flow inside but do not control the packet. So you have been illegally modified to pass the packet even if the packet is considered as a unnormal packet. The defense system is to fail to appropriate controls. Therefore, in order to ensure a successful web services diagnostic system development is necessary. Web application diagnostic system is real and urgent need and alternative. The diagnostic system development process mu st be carried out step of established diagnostic systems, diagnostic scoping web system vulnerabilities, web application, analysis, security vulnerability assessment and selecting items. And diagnostic system as required by the web system environment using tools, programming languages, interfaces, parameters must be set.

Bias & Hate Speech Detection Using Deep Learning: Multi-channel CNN Modeling with Attention (딥러닝 기술을 활용한 차별 및 혐오 표현 탐지 : 어텐션 기반 다중 채널 CNN 모델링)

  • Lee, Wonseok;Lee, Hyunsang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.12
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    • pp.1595-1603
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    • 2020
  • Online defamation incidents such as Internet news comments on portal sites, SNS, and community sites are increasing in recent years. Bias and hate expressions threaten online service users in various forms, such as invasion of privacy and personal attacks, and defamation issues. In the past few years, academia and industry have been approaching in various ways to solve this problem The purpose of this study is to build a dataset and experiment with deep learning classification modeling for detecting various bias expressions as well as hate expressions. The dataset was annotated 7 labels that 10 personnel cross-checked. In this study, each of the 7 classes in a dataset of about 137,111 Korean internet news comments is binary classified and analyzed through deep learning techniques. The Proposed technique used in this study is multi-channel CNN model with attention. As a result of the experiment, the weighted average f1 score was 70.32% of performance.