• Title/Summary/Keyword: Attacker model

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A Storage Method to Enhance Cookie File Security (쿠키파일의 보안성 향상을 위한 저장 방식)

  • Sim, Won-Tae;Choi, Yo-Han;Seo, Hee-Suk;Noh, Bong-Nam
    • Journal of the Korea Society for Simulation
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    • v.20 no.1
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    • pp.29-37
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    • 2011
  • Cookie file can be properly protected by designing security zone to enhance the safety of cookie file vulnerable to cyber attacks. In this paper, the model, in which cookie file is stored in the security area and the current visiting page is closely linked with cookie, is proposed to help users utilize in the same existing way, as well as enhance the security of user cookie files. Even if attacker tries to compromise web browser's cookie folder, the security of other cookies can be preserved. It is possible since the folder has the only cookie for the current web page where user is visiting.

A Security Model for Duplication Resistant eSeal (복제 공격 저항성을 갖는 전자봉인 보안 모델)

  • Kim, Joo-Hae;Choi, Eun-Young;Lee, Dong-Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.17 no.5
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    • pp.111-116
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    • 2007
  • An eSeal(Electrical Seal) is an active RFID device which installed on the door of a container. The main role of the tag is to make sure the seal is not breaking by unauthorized people. Because an eSeal uses RFID system, we need to prevent eavesdrop and impersonate. Moreover, an eSeal which uses a secure protocol must not be able to duplicate. If duplication resistant property is not provide to a eSeal, an attacker may replace a object in the sealed container and reseal the container with duplicated eseal to hide breaking of the eSeal. In this paper, we provide a protocol which resist duplicate an eSeal during prevent eavesdrop and impersonation.

A Simulation Modeling for the Effect of Resource Consumption Attack over Mobile Ad Hoc Network

  • Raed Alsaqour;Maha Abdelhaq;Njoud Alghamdi;Maram Alneami;Tahani Alrsheedi;Salma Aldghbasi;Rahaf Almalki;Sarah Alqahtani
    • International Journal of Computer Science & Network Security
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    • v.23 no.9
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    • pp.111-119
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    • 2023
  • Mobile Ad-hoc Network (MANET) is an infrastructure-less network that can configure itself without any centralized management. The topology of MANET changes dynamically which makes it open for new nodes to join it easily. The openness area of MANET makes it very vulnerable to different types of attacks. One of the most dangerous attacks is the Resource Consumption Attack (RCA). In this type of attack, the attacker consumes the normal node energy by flooding it with bogus packets. Routing in MANET is susceptible to RCA and this is a crucial issue that deserves to be studied and solved. Therefore, the main objective of this paper is to study the impact of RCA on two routing protocols namely, Ad hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR); as a try to find the most resistant routing protocol to such attack. The contribution of this paper is a new RCA model (RCAM) which applies RCA on the two chosen routing protocols using the NS-2 simulator.

Using Machine Learning Techniques for Accurate Attack Detection in Intrusion Detection Systems using Cyber Threat Intelligence Feeds

  • Ehtsham Irshad;Abdul Basit Siddiqui
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.179-191
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    • 2024
  • With the advancement of modern technology, cyber-attacks are always rising. Specialized defense systems are needed to protect organizations against these threats. Malicious behavior in the network is discovered using security tools like intrusion detection systems (IDS), firewall, antimalware systems, security information and event management (SIEM). It aids in defending businesses from attacks. Delivering advance threat feeds for precise attack detection in intrusion detection systems is the role of cyber-threat intelligence (CTI) in the study is being presented. In this proposed work CTI feeds are utilized in the detection of assaults accurately in intrusion detection system. The ultimate objective is to identify the attacker behind the attack. Several data sets had been analyzed for attack detection. With the proposed study the ability to identify network attacks has improved by using machine learning algorithms. The proposed model provides 98% accuracy, 97% precision, and 96% recall respectively.

A Study of Step-by-step Countermeasures Model through Analysis of SQL Injection Attacks Code (공격코드 사례분석을 기반으로 한 SQL Injection에 대한 단계적 대응모델 연구)

  • Kim, Jeom-Goo;Noh, Si-Choon
    • Convergence Security Journal
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    • v.12 no.1
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    • pp.17-25
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    • 2012
  • SQL Injection techniques disclosed web hacking years passed, but these are classified the most dangerous attac ks. Recent web programming data for efficient storage and retrieval using a DBMS is essential. Mainly PHP, JSP, A SP, and scripting language used to interact with the DBMS. In this web environments application does not validate the client's invalid entry may cause abnormal SQL query. These unusual queries to bypass user authentication or da ta that is stored in the database can be exposed. SQL Injection vulnerability environment, an attacker can pass the web-based authentication using username and password and data stored in the database. Measures against SQL Inj ection on has been announced as a number of methods. But if you rely on any one method of many security hole ca n occur. The proposal of four levels leverage is composed with the source code, operational phases, database, server management side and the user input validation. This is a way to apply the measures in terms of why the accident preventive steps for creating a phased step-by-step response nodel, through the process of management measures, if applied, there is the possibility of SQL Injection attacks can be.

Models for Privacy-preserving Data Publishing : A Survey (프라이버시 보호 데이터 배포를 위한 모델 조사)

  • Kim, Jongseon;Jung, Kijung;Lee, Hyukki;Kim, Soohyung;Kim, Jong Wook;Chung, Yon Dohn
    • Journal of KIISE
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    • v.44 no.2
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    • pp.195-207
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    • 2017
  • In recent years, data are actively exploited in various fields. Hence, there is a strong demand for sharing and publishing data. However, sensitive information regarding people can breach the privacy of an individual. To publish data while protecting an individual's privacy with minimal information distortion, the privacy- preserving data publishing(PPDP) has been explored. PPDP assumes various attacker models and has been developed according to privacy models which are principles to protect against privacy breaching attacks. In this paper, we first present the concept of privacy breaching attacks. Subsequently, we classify the privacy models according to the privacy breaching attacks. We further clarify the differences and requirements of each privacy model.

Personal Information Protection for Biometric Verification based TeleHealth Services (바이오인식을 이용한 원격의료에서의 개인정보보호)

  • Shin, Yong-Nyuo;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.5
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    • pp.659-664
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    • 2010
  • This paper provides an integrated framework for biometric data and private information protection in TeleHealth. Biometric technology is indispensable in providing identification and convenience in the TeleHealth environment. Once biometric information is exposed to mallicious attacker, he will suffer great loss from the illegferuse of his biometric data by someone else because of difficulty of change not like ID and password. We have to buil by someone esystem data bon the integrated framework for biometric data and private information protection in TeleHealth. First, we consider the structure of the biometric system and the security requirements of y someone esystem data bon the biometrics. And then, we define the TeleHealth system model and provide the vulnerabilities and countermeasures of the biometric-data by someone eintegrated model.byhe TeleHealth sse bec requires two-phata authentication for countermeasure. Finally, we made some functionferrequirements for main componenets of biometric-data bintegrated TeleHealth system framework to protect biometric data.

Analysis of privacy issues and countermeasures in neural network learning (신경망 학습에서 프라이버시 이슈 및 대응방법 분석)

  • Hong, Eun-Ju;Lee, Su-Jin;Hong, Do-won;Seo, Chang-Ho
    • Journal of Digital Convergence
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    • v.17 no.7
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    • pp.285-292
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    • 2019
  • With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.

Improvement Mechanism of Security Monitoring and Control Model Using Multiple Search Engines (다중 검색엔진을 활용한 보안관제 모델 개선방안)

  • Lee, Je-Kook;Jo, In-June
    • The Journal of the Korea Contents Association
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    • v.21 no.1
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    • pp.284-291
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    • 2021
  • As the current security monitoring system is operated as a passive system only for response after an attacker's attack, it is common to respond to intrusion incidents after an attack occurs. In particular, when new assets are added and actual services are performed, there is a limit to vulnerability testing and pre-defense from the point of view of an actual hacker. In this paper, a new security monitoring model has been proposed that uses multiple hacking-related search engines to add proactive vulnerability response functions of protected assets. In other words, using multiple search engines with general purpose or special purpose, special vulnerabilities of the assets to be protected are checked in advance, and the vulnerabilities of the assets that have appeared as a result of the check are removed in advance. In addition, the function of pre-checking the objective attack vulnerabilities of the protected assets recognized from the point of view of the actual hacker, and the function of discovering and removing a wide range of system-related vulnerabilities located in the IP band in advance were additionally presented.

An Extended SAML Delegation Model Based on Multi-Agent for Secure Web Services (안전한 웹서비스를 위한 멀티 에이전트 기반의 확장된 SAML 위임 모델)

  • Kim, Kyu-Il;Won, Dong-Ho;Kim, Ung-Mo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.4
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    • pp.111-122
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    • 2008
  • Web service is defined to support interoperable machine to machine interaction over a network and defined as distributed technologies. Recently in web service environment, security has become one of the most critical issues. An attacker may expose user privacy and service information without authentication. Furthermore, the users of web services must temporarily delegate some or all of their behalf. This results in the exposure of user privacy information by agents. We propose a delegation model for providing safety of web service and user privacy in ubiquitous computing environments. In order to provide safety of web service and user privacy, XML-based encryption and a digital signature mechanism need to be efficiently integrated. In this paper, we propose web service management server based on XACML, in order to manage services and policies of web service providers. For this purpose, we extend SAML to declare delegation assertions transferred to web service providers by delegation among agents.