• Title/Summary/Keyword: Intrusion Prevention

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Research on SecureOS Module Based on File System for Data Protection (데이터 보호를 위한 파일시스템 기반의 SecureOS Module에 관한 연구)

  • Yonggu JANG;Inchul KIM;Jisong RYU
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.4
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    • pp.67-79
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    • 2023
  • Service environments through laptops, smart devices, and various IoT devices are developing very rapidly. Recent security measures in these Internet environments mainly consist of network application level solutions such as firewall(Intrusion Prevention Systems) and IDS (intrusion detection system). In addition, various security data have recently been used on-site, and issues regarding the management and destruction of such security data have been raised. Products such as DRM(Digital Rights Management) and DLP(Data Loss Prevention) are being used to manage these security data. However despite these security measures, data security measures taken out to be used in the field are operated to the extent that the data is encrypted, delivered, and stored in many environments, and measures for encryption key management or data destruction are insufficient. Based on these issues we aim to propose a SecureOS Module, an OS-based security module. With this module users can manage and operate security data through a consistent interface, addressing the problems mentioned above.

Real-time Intrusion-Detection Parallel System for the Prevention of Anomalous Computer Behaviours (비정상적인 컴퓨터 행위 방지를 위한 실시간 침입 탐지 병렬 시스템에 관한 연구)

  • 유은진;전문석
    • Review of KIISC
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    • v.5 no.2
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    • pp.32-48
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    • 1995
  • Our paper describes an Intrusion Detection Parallel System(IDPS) which detects an anomaly activity corresponding to the actions that interaction between near detection events. IDES uses parallel inductive approaches regarding the problem of real-time anomaly behavior detection on rule-based system. This approach uses sequential rule that describes user's behavior and characteristics dependent on time. and that audits user's activities by using rule base as data base to store user's behavior pattern. When user's activity deviates significantly from expected behavior described in rule base. anomaly behaviors are recorded. Observed behavior is flagged as a potential intrusion if it deviates significantly from the expected behavior or if it triggers a rule in the parallel inductive system.

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A Hybrid PSO-BPSO Based Kernel Extreme Learning Machine Model for Intrusion Detection

  • Shen, Yanping;Zheng, Kangfeng;Wu, Chunhua
    • Journal of Information Processing Systems
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    • v.18 no.1
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    • pp.146-158
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    • 2022
  • With the success of the digital economy and the rapid development of its technology, network security has received increasing attention. Intrusion detection technology has always been a focus and hotspot of research. A hybrid model that combines particle swarm optimization (PSO) and kernel extreme learning machine (KELM) is presented in this work. Continuous-valued PSO and binary PSO (BPSO) are adopted together to determine the parameter combination and the feature subset. A fitness function based on the detection rate and the number of selected features is proposed. The results show that the method can simultaneously determine the parameter values and select features. Furthermore, competitive or better accuracy can be obtained using approximately one quarter of the raw input features. Experiments proved that our method is slightly better than the genetic algorithm-based KELM model.

An Improved Signature Hashing Algorithm for High Performance Network Intrusion Prevention System (고성능 네트워크 침입방지시스템을 위한 개선된 시그니처 해싱 알고리즘)

  • Ko, Joong-Sik;Kwak, Hu-Keun;Wang, Jeong-Seok;Kwon, Hui-Ung;Chung, Kyu-Sik
    • The KIPS Transactions:PartC
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    • v.16C no.4
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    • pp.449-460
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    • 2009
  • The signature hashing algorithm[9] provides the fast pattern matching speed for network IPS(Intrusion Prevention System) using the hash table. It selects 2 bytes from all signature rules and links to the hash table by the hash value. It has an advantage of performance improvement because it reduces the number of inspecting rules in the pattern matching. However it has a disadvantage of performance drop if the number of rules with the same hash value increases when the number of rules are large and the corelation among rules is strong. In this paper, we propose a method to make all rules distributed evenly to the hash table independent of the number of rules and corelation among rules for overcoming the disadvantage of the signature hashing algorithm. In the proposed method, it checks whether or not there is an already assigned rule linked to the same hash value before a new rule is linked to a hash value in the hash table. If there is no assigned rule, the new rule is linked to the hash value. Otherwise, the proposed method recalculate a hash value to put it in other position. We implemented the proposed method in a PC with a Linux module and performed experiments using Iperf as a network performance measurement tool. The signature hashing method shows performance drop if the number of rules with the same hash value increases when the number of rules are large and the corelation among rules is strong, but the proposed method shows no performance drop independent of the number of rules and corelation among rules.

A High-speed Packet Filtering System Architecture in Signature-based Network Intrusion Prevention (시그내쳐 기반의 네트워크 침입 방지에서 고속의 패킷 필터링을 위한 시스템 구조)

  • Kim, Dae-Young;Kim, Sun-Il;Lee, Jun-Yong
    • Journal of KIISE:Computer Systems and Theory
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    • v.34 no.2
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    • pp.73-83
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    • 2007
  • In network intrusion prevention, attack packets are detected and filtered out based on their attack signatures. Pattern matching is extensively used to find attack signatures and the most time-consuming execution part of Network Intrusion Prevention Systems(NIPS). Pattern matching is usually accelerated by hardware and should be performed at wire speed in NIPS. However, that alone is not good enough. First, pattern matching hardware should be able to generate sufficient pattern match information including the pattern index number and the location of the match found at wire speed. Second, it should support pattern grouping to reduce unnecessary pattern matches. Third, it should always have a constant worst-case performance even if the number of patterns is increased. Finally it should be able to update patterns in a few minutes or seconds without stopping its operations, We propose a system architecture to meet the above requirement. The system architecture can process multiple pattern characters in parallel and employs a pipeline architecture to achieve high speed. Using Xilinx FPGA simulation, we show that the new system stales well to achieve a high speed oner 10Gbps and satisfies all of the above requirements.

A Study on Data Acquisition of IoT Devices Intrusion (사물인터넷 기기 침해사고 데이터 수집 방안 연구)

  • Jong-bum Lee;Ieck-Chae Euom
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.3
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    • pp.537-547
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    • 2023
  • As Internet of Things (IoT) technology evolves, IoT devices are being utilized in a variety of fields. However, it has become a new surface of cyber attacks and is affecting industries that did not previously consider cyber breaches. After a intrusion occurs, post-processing and damage spread prevention are important, but it is difficult to respond due to the lackof standards and guidelines. Therefore, in order to respond to such incidents, this paper establishes an incident data collection procedure and presents the data that can be collected to improve the intrusion data acquisition method for general IoT devices. In addition, we proved the efficiency and feasibility of the data collection procedure through experiments.

Design of Intrusion Prevention System(IPS) in Linux Environment (Linux 환경에서의 침입방지시스템(IPS) 설계)

  • 이상훈;김우년;이도훈;박응기
    • Proceedings of the Korea Information Assurance Society Conference
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    • 2004.05a
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    • pp.21-26
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    • 2004
  • The growth of incidents on the Internet has reflected growth of the internet itself and growth of the computing power. while in previous years, external attacks tended to originate from those interested trend in exploring the Internet for its own sake and testing their skills, there is an increasing trend towards intrusions motivated by financial, political, and military objectives. so, attacks on the nation's computer infrastructures are becoming an increasingly serious problem. Even though the problem is ubiquitious, government agencies are particularly appealing targets and they tend to be more willing to reveal such events than commercial organizations. The threat of damage made necessity of security's recognition, as a result, many researches have been carried out into security of system actively. Intrusion Detection technology is detection of intrusion using audit data differently from using traditional simple filtering and informs manager of it. It has security manager of system deal with the intrusion more quickly. but, cause current environment of Internet manager can't doing response Intrusion alert immediately. That's why IPS needed. IPS can response automatically the intrusion alert. so, manager is more comfortable and can response quickly.

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Anomaly Detection Model based on Network using the Session Patterns (세션 패턴을 이용한 네트워크기반의 비정상 탐지 모델)

  • Park Soo-Jin;Choi Yong-Rak
    • The KIPS Transactions:PartC
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    • v.11C no.6 s.95
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    • pp.719-724
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    • 2004
  • Recently, since the number of internet users is increasing rapidly and, by using the public hacking tools, general network users can intrude computer systems easily, the hacking problem is getting more serious. In order to prevent the intrusion, it is needed to detect the sign in advance of intrusion in a positive prevention by detecting the various foms of hackers' intrusion trials to know the vulnerability of systems. The existing network-based anomaly detection algorithms that cope with port- scanning and the network vulnerability scans have some weakness in intrusion detection. they can not detect slow scans and coordinated scans. therefore, the new concept of algorithm is needed to detect effectively the various forms of abnormal accesses for intrusion regardless of the intrusion methods. In this paper, SPAD(Session Pattern Anomaly Detector) is presented, which detects the abnormal service patterns by comparing them with the ordinary normal service patterns.

Ensemble Based Optimal Feature Selection Algorithm for Efficient Intrusion Detection in Wireless Sensor Network

  • Shyam Sundar S;R.S. Bhuvaneswaran;SaiRamesh L
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.8
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    • pp.2214-2229
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    • 2024
  • Wireless sensor network (WSN) consists of large number of sensor nodes that are deployed in geographical locations to collect sensed information, process data and communicate it to the control station for further processing. Due the unfriendly environment where the sensors are deployed, there exist many possibilities of malicious nodes which performs malicious activities in the network. Therefore, the security threats affect performance and life time of sensor networks, whereas various security aspects are there to address security issues in WSN namely Cryptography, Trust Management, Intrusion Detection System (IDS) and Intrusion Prevention Systems (IPS). However, IDS detect the malicious activities and produce an alarm. These malicious activities exploit vulnerabilities in the network layer and affect all layers in the network. Existing feature selection methods such as filter-based methods are not considering the redundancy of the selected features and wrapper method has high risk of overfitting the classification of intrusion. Due to overfitting, the classification algorithm fails to detect the intrusion in better manner. The main objective of this paper is to provide the efficient feature selection algorithm which was suitable for any type classification algorithm to detect the intrusion in an effective manner. This paper, the security of the network is addressed by proposing Feature Selection Algorithm using Chi Squared with Ensemble Method (FSChE). The proposed scheme employs the combination of decision tree along with the random forest classification algorithm to form ensemble classifier. The experimental results justify the feasibility of the proposed scheme in terms of attack detection, packet delivery ratio and time analysis by employing NSL KDD cup data Set. The obtained results shows that the proposed ensemble method increases the overall performance by 10% to 25% with respect to mentioned parameters.

Study on the categorization of modus operandi and tools used in domestic burglary (건축물 침입에 이용되는 침입수법 및 도구의 유형화 연구)

  • Park, Hyeon-Ho;Cho, Joon-Tag
    • Korean Security Journal
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    • no.40
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    • pp.57-86
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    • 2014
  • As the revision of Building Code including applying crime prevention design to buildings passed recently and target hardening ought to be evidence-based, we studied the Modus Operandi (MO) and intrusion tools of domestic burglary to earn basic data for improvement of crime prevention hardware in the future. To be specific, we reviewed related academic literature and police official statistics of domestic burglary critically and interviewed detectives in charge of burglary to specify and categorize MO and tools. We can derive some implications from research findings, including improvement of the statistical system for the MO of burglary, active sharing of the MO of burglary among the criminal justice agencies and related industries and experts. Also, crime prevention advice and education for the local residents focused on MO of burglary can be recommended. Based on this research, to enhance the level of community safety significantly, performance tests of crime prevention hardware such as security doors and windows etc. and the study on related certification system should be vitalized.

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