FPGA Implementation of Various Security Based Tollgate system Using ANPR Technique

Shashidhar, Srisailam; Krishna, Sri

doi:10.14445/22315381/ijett-v15p235

Cited by 2 publications

(2 citation statements)

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“…License Plate Recognition (LPR) atau sering disebut juga dengan Automatic Number Plate Recognition [6] merupakan salah satu teknologi atau sistem yang menangani pengenalan nomor polisi yang ada pada plat nomor kendaraan bermotor. Pengenalan nomor polisi yang ada pada plat nomor kendaraan tersebut dapat dilakukan secara otomatis dengan menggunakan teknologi seperti Optical Character Recognition.…”

Section: Automatic Number Plate Recognitionunclassified

Pengenalan Plat Kendaraan Berbasis Android menggunakan Viola Jones dan Kohonen Neural Network

Michael

2016

Ilk. J. Ilm.

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Penelitian ini bertujuan untuk membangun sistem pengenalan plat kendaraan roda dua berbasis android. Penelitian ini dilaksanakan di Kota Makassar Indonesia. Metode yang digunakan pada penelitian ini adalah pengenalan pola plat kendaraan dengan metode viola jones, kemudian segmentasi karakter plat menggunakan metode morfologi, dan pengenalan karakter plat dengan kohonen neural network. Hasil penelitian yang diperoleh menunjukkan bahwa pengenalan plat kendaraan menggunakan kohonen neural network berdasarkan pengujian yang dilakukan menunjukkan persentase keberhasilan pengenalan karakter pada plat kendaraan bermotor pada kondisi yang baik sebesar 78,57% edangkan pada plat yang kurang baik sebesar 57,14%

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Section: Automatic Number Plate Recognitionunclassified

Pengenalan Plat Kendaraan Berbasis Android menggunakan Viola Jones dan Kohonen Neural Network

Michael

2016

Ilk. J. Ilm.

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“…Instead, the proposed system implicitly considers distributed attack perpetrated by many coordinated nodes/bots. The approach followed by [33], [34] is instead based on dynamically changing the port number of the server through a random port hopping approach. We believe that such approach should be considered invasive for the server, while we prefer adopting a technique which can be deployed even on a network node such as a firewall.…”

Section: Related Workmentioning

confidence: 99%

A Network Traffic Representation Model for Detecting Application Layer Attacks

Cambiaso¹

2016

IJCDS

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Intrusion Detection Systems (IDS) play an important role in network security, protecting systems and infrastructures from malicious attacks. With the emerging of novel threats and offensive mechanisms, IDS require updates in order to efficiently detect new menaces. In this paper we propose an anomaly-based detection model designed for particular application protocols, exploited by emerging menaces known as Slow Denial of Service (DoS) Attacks. We define parameters characterizing network traffic and we describe in detail how to extrapolate them from a network traffic capture. We motivate the need of packet inspection in certain contexts in order to retrieve correct data. We analyze and describe how the proposed model behaves on two real scenarios involving legitimate and malicious activities, respectively. Thanks to our model, a detection framework for attacks working at the application layer of the communication protocol stack is provided, allowing and facilitating the execution of detection algorithms. Indeed, though the adoption of such framework, the design of efficient detection systems is simplified and designers work is reduced, allowing them a faster deploy of efficient detection algorithms. The aim of this paper is to provide an effective framework for application DoS attacks detection.

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FPGA Implementation of Various Security Based Tollgate system Using ANPR Technique

Cited by 2 publications

References 0 publications

Pengenalan Plat Kendaraan Berbasis Android menggunakan Viola Jones dan Kohonen Neural Network

Pengenalan Plat Kendaraan Berbasis Android menggunakan Viola Jones dan Kohonen Neural Network

A Network Traffic Representation Model for Detecting Application Layer Attacks

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