• Title/Summary/Keyword: Packet Detection

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Comparative Analysis of Intrusion Detection Attack Based on Machine Learning Classifiers

  • Surafel Mehari;Anuja Kumar Acharya
    • International Journal of Computer Science & Network Security
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    • v.24 no.10
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    • pp.115-124
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    • 2024
  • In current day information transmitted from one place to another by using network communication technology. Due to such transmission of information, networking system required a high security environment. The main strategy to secure this environment is to correctly identify the packet and detect if the packet contain a malicious and any illegal activity happened in network environments. To accomplish this we use intrusion detection system (IDS). Intrusion detection is a security technology that design detects and automatically alert or notify to a responsible person. However, creating an efficient Intrusion Detection System face a number of challenges. These challenges are false detection and the data contain high number of features. Currently many researchers use machine learning techniques to overcome the limitation of intrusion detection and increase the efficiency of intrusion detection for correctly identify the packet either the packet is normal or malicious. Many machine-learning techniques use in intrusion detection. However, the question is which machine learning classifiers has been potentially to address intrusion detection issue in network security environment. Choosing the appropriate machine learning techniques required to improve the accuracy of intrusion detection system. In this work, three machine learning classifier are analyzed. Support vector Machine, Naïve Bayes Classifier and K-Nearest Neighbor classifiers. These algorithms tested using NSL KDD dataset by using the combination of Chi square and Extra Tree feature selection method and Python used to implement, analyze and evaluate the classifiers. Experimental result show that K-Nearest Neighbor classifiers outperform the method in categorizing the packet either is normal or malicious.

Deep Packet Inspection for Intrusion Detection Systems: A Survey

  • AbuHmed, Tamer;Mohaisen, Abedelaziz;Nyang, Dae-Hun
    • Information and Communications Magazine
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    • v.24 no.11
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    • pp.25-36
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    • 2007
  • Deep packet inspection is widely recognized as a powerful way which is used for intrusion detection systems for inspecting, deterring and deflecting malicious attacks over the network. Fundamentally, almost intrusion detection systems have the ability to search through packets and identify contents that match with known attach. In this paper we survey the deep packet inspection implementations techniques, research challenges and algorithm. Finally, we provide a comparison between the different applied system.

A Study on Buffer Scheme enhancing Performance In Intrusion Detection System (침입탐지시스템의 성능 향상을 위한 버퍼구조에 관한 연구)

  • 최인수;장덕성
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.2
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    • pp.44-50
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    • 2003
  • Even though algorithm of intrusion detection is superior to other algorithm in intrusion detection system, it is supposed that captured packet happened hostly lead to lose packet in system architecture when a buffer is full. If packet lost concerned to be hacked, it might impact to system all over. In this paper, try to focus on performance improvement of detection system. Buffer with threshold value could classify normal packet and hacked packet. The buffer accept normal packet and supposed to be hacked packet until critical value. When buffer reached at threshold value, destroyed packet is only normal packet. Proposed method can complement weakness that bypass hacked packet.

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A Text Detection Method Using Wavelet Packet Analysis and Unsupervised Classifier

  • Lee, Geum-Boon;Odoyo Wilfred O.;Kim, Kuk-Se;Cho, Beom-Joon
    • Journal of information and communication convergence engineering
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    • v.4 no.4
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    • pp.174-179
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    • 2006
  • In this paper we present a text detection method inspired by wavelet packet analysis and improved fuzzy clustering algorithm(IAFC).This approach assumes that the text and non-text regions are considered as two different texture regions. The text detection is achieved by using wavelet packet analysis as a feature analysis. The wavelet packet analysis is a method of wavelet decomposition that offers a richer range of possibilities for document image. From these multi scale features, we adapt the improved fuzzy clustering algorithm based on the unsupervised learning rule. The results show that our text detection method is effective for document images scanned from newspapers and journals.

A Packet Detection Algorithm for IEEE802.11n System (IEEE802.11n 시스템에 적용 가능한 패킷 검출 알고리즘)

  • Jung, Hyeok-Koo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.4C
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    • pp.330-335
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    • 2008
  • This paper proposes a packet detection algorithm for IEEE802.11n system. IEEE802.11n is a multiple input multiple output (MIMO) system and we have to consider several combining techniques which are used in multiple receive antenna system. In this paper, we propose a hybrid packet detection algorithm which combines double sliding window algorithm or delay and correlation algorithm, that is used in single input single output (SISO) system, and multiple receive antenna combining algorithms, and simulated their performances in Iin system environments and shows the results.

Real-Time QRS Detection Using Wavelet Packet Transform

  • Bholsithi, Wisarut;;Hinjit, Watcharapong;Dejhan, Kobchai
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1880-1884
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    • 2004
  • The wavelet packet transform has been applied for QRS detection with squaring, window integration, and impulse filter techniques to cut down the false detection of QRS complex. This real time QRS detection has been performed on Simulink and Matlab. The correct QRS detection rates have reached to 99.75% in the experiment with 15 sets of ECG data from European ST-T database which are kept in Physionet.

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Packet Detection and Frequency Offset Estimation/Correction Architecture Design and Analysis for OFDM-based WPAN Systems (OFDM-기반 WPAN 시스템을 위한 패킷 검출 및 반송파 주파수 옵셋 추정/보정 구조 설계 및 분석)

  • Back, Seung-Ho;Lee, Han-Ho
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.49 no.7
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    • pp.30-38
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    • 2012
  • This paper presents packet detection, frequency offset estimation architecture and performance analysis for OFDM-based wireless personal area network (WPAN) systems. Packet detection structure is used to find the start point of a packet exactly in WPAN system as the correlation value passes the constant threshold value. The applied autocorrelation structure of the algorithm can be implemented simply compared to conventional packet detection algorithms. The proposed frequency offset estimation architecture is designed for phase rotation process structure, internal bit reduction to reduce hardware size and the frequency offset adjustment block to reduce look-up table size unlike the conventional structure. If the received signal can be compensated by estimated frequency offset through the correction block, it can reduce the impact on the frequency offset. Through the performance result, the proposed structure has lower hardware complexity and gate count compared to the conventional structure. Thus, the proposed structure for OFDM-based WPAN systems can be applied to the initial synchronization process and high-speed low-power WPAN chips.

An Analysis of Detection of Malicious Packet Dropping and Detour Scheme in IoT based on IPv6 (IPv6 기반의 사물인터넷 환경에서 악성 노드의 패킷 유실 공격 탐지 및 우회 기법 분석)

  • Choi, Jaewoo;Kwon, Taekyoung
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.3
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    • pp.655-659
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    • 2016
  • In this paper, we propose new detection and detour methods against packet drop attacks for availability in the Internet of Things (IoT) based on the IEEE 802.15.4e and RPL protocol standards that employ IPv6. We consider the rank value of RPL and the consecutive packet drops to improve the detection metrics, and also take into account the use of both sibling and child nodes on a RPL routing path to construct the detour method. Our simulation results show that the proposed detection method is faster than the previous result, and the detour method improves the detour success rate.

A Single Channel Voice Activity Detection for Noisy Environments Using Wavelet Packet Decomposition and Teager Energy (웨이블렛 패킷 변환과 Teager 에너지를 이용한 잡음 환경에서의 단일 채널 음성 판별)

  • Koo, Boneung
    • The Journal of the Acoustical Society of Korea
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    • v.33 no.2
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    • pp.139-145
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    • 2014
  • In this paper, a feature parameter is obtained by applying the Teager energy to the WPD(Wavelet Packet Decomposition) coefficients. The threshold value is obtained based on means and standard deviations of nonspeech frames. Experimental results by using TIMIT speech and NOISEX-92 noise databases show that the proposed algorithm is superior to the typical VAD algorithm. The ROC(Receiver Operating Characteristics) curves are used to compare performance of VAD's for SNR values of ranging from 10 to -10 dB.

Policy of packet dropping for enhancing IDS performance (IDS의 성능 향상을 위한 패킷 폐기 방안)

  • Moon, Jong-Wook;Kim, Jong-Su;Jung, Gi-Hyun;Yim, Kang-Bin;Joo, Min-Kyu;ChoI, Kyung-Hee
    • The KIPS Transactions:PartC
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    • v.9C no.4
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    • pp.473-480
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    • 2002
  • Although many researches on IDS (Intrusion Detection System) have been performed, the most of them are limited to the algorithm of detection software. However, even an IDS with superior algorithm can not detect intrusion, if it loses packets which nay have a clue of intrusions. In this paper, we suggest an efficient wav to improve the performance of IDS by reducing packet losses occurred due to hardware limitation and abundant processing overhead introduced by massive detection software itself. The reduction in packet losses is achieved by dropping hacking-free packets. The result shows that this decrease of packet losses leads an IDS to improve the detection rate of real attack.