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Network instrusion prevention system ( NIPS) based on network intrusion detection system (NIDS) and ID3 algorithm decision tree classifier by Syurahbil, A

“…Network security has gained significant attention in research and industrial communities.Due to the increasing threat of the network intrusion,firewalls have become important elements of the security policy.Firewall performance highly depends toward number of rules,because the large more rules the consequence makes downhill performance progressively.Firewall can be allow or deny access network packets incoming and outgoing into Local Area Network(LAN),but firewall can not detect intrusion.To distinguishing an intrusion network packet or normal is very difficult and takes a lot of time.An analyst must review all the network traffics previously.In this study,a new way to make the rules that can determine network packet is intrusion or normal automatically.These rules implemented into firewall as prevention,which if there is a network packet that match these rules then network packet will be dropped.This is called Network Intrusion Prevention System(NIPS).These rules are generated based on Network Intrusion Detection System(NIDS)and Iterative Dichotomiser 3 (ID3)Algorithm Decision Tree Classifier,which as data training is intrusion network packet and normal network packets from previous network traffics.The experiment is successful,which can generate the rules then implemented into a firewall and drop the intrusion network packet automatically.Moreover,this way can minimize number of rules in firewall.…”
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Wormhole attack detection mechanism in mobile ad hoc network using neighborhood information and path tracing algorithm by Enshaei, Mehdi

“…In this study, a new defence mechanism is proposed based on modification of the packet forwarding process, using Neighborhood Information (NI) and PT algorithm, and known as NIPT algorithm. …”
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Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

“…FPF of SVM have merged the analyzed results of flexible packet filtering with support vector machine algorithm to get better classification of the captured network traffics and to detect anomalies. …”
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CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets by Alaidaros, Hashem Mohammed

“…This study proposed a Conditional Hybrid Intrusion Detection (CHID) by combining the flow-based with packet-based detection. …”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

“…Detection methods based on statistical and data mining techniques are widely deployed as anomaly-based detection system (ADS). …”
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Smart and energy aware routing for the internet of mobile things by Beh, Zi Xuan

“…This can also be concluded that the SEA routing algorithm is smart and energy aware based on the results obtained.…”
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Void avoidance opportunistic routing density rank based for underwater sensor networks by Ismail, Nasarudin

“…Secondly, the algorithm Opportunistic Routing Density Rank Based (ORDRB) was developed to deal with redundant packet forwarding by introducing a new method to reduce the redundant packet forwarding while in dense or sparse conditions to improve the energy consumption effectively. …”
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Location-Based Approach for Route Maintenance in Dynamic Source Routing Protocol by Sjaugi, Muhammad Farhan

“…The objectives of this research are to propose new algorithm to detect route failure as early warning message to the protocol to take further action, and to propose new algorithm for DSR route maintenance to response the early warning message from route failure detection algorithm. …”
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Non-invasive pathological voice classifications using linear and non-linear classifiers by Hariharan, Muthusamy

“…In the case of detection of specific disorders, wavelet packet and entropy features perform well compared to time-domain energy variations based features and MFCCs and SVD based features. …”
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Embedded Ethernet System For Real-Time Communication by Thiagarajan, Durgesh

“…The Ethernet network model is used to analyze the performance of the backoff algorithm in a different number of nodes. The end delay of each packet, the number of packet collision and number of packet delivered are determined based on the analysis. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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Flow-based approach on bro intrusion detection by Alaidaros, Hashem, Mahmuddin, Massudi

“…Packet-based or Deep Packet Inspection (DPI) intrusion detection systems (IDSs) face challenges when coping with high volume of traffic. …”
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Secure address resolution protocol proxy in software defined network by Munther, Munther Numan

“…In addition, ARP based attack detection technique combines ARP storm and ARP spoofing detection algorithms. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders by Murugesa Pandian, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr., Muthusamy, Hariharan, Dr.

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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

“…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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DDoS Classification using Combined Techniques by Mohd Yusof, Mohd Azahari, Mohd Safar, Noor Zuraidin, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Jofri, Muhamad Hanif, Mohamed, Juliana, Omar, Abdul Halim, Bahrudin, Ida Aryanie, Mohamed Ali @ Md Hani, Mohd Hatta

“…The four techniques focused in this research are PTA-SVM, PTA-NB, PTA-LR and PTA-KNN. Based on the results of detection accuracy and false positive rate for all the techniques involved, it proves the PTA-KNN technique is a more effective technique in the context of detection of incoming packets whether DDoS attacks or normal packets…”
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DDoS Classification using Combined Techniques by Mohd Yusof, Mohd Azahari, Mohd Safar, Noor Zuraidin, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Jofri, Muhamad Hanif, Mohamed, Juliana, Omar, Abdul Halim, Bahrudin, Ida Aryanie, Mohamed Ali @ Md Hani, Mohd Hatta

“…The four techniques focused in this research are PTA-SVM, PTA-NB, PTA-LR and PTA-KNN. Based on the results of detection accuracy and false positive rate for all the techniques involved, it proves the PTA-KNN technique is a more effective technique in the context of detection of incoming packets whether DDoS attacks or normal packets.…”
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

“…Results indicate that the wavelet-based damage detection method precisely identified the location and severity of damages even without reference data. …”
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Anomaly detection in ICS datasets with machine learning algorithms by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Abdul Rahman, Farah Diyana, Tahir, Mohammad

“…The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.…”
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