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Author

Apri Siswanto

Bio: Apri Siswanto is an academic researcher from Riau University. The author has contributed to research in topics: Encryption & Fingerprint (computing). The author has an hindex of 4, co-authored 15 publications receiving 51 citations.

Papers
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Proceedings ArticleDOI
12 Apr 2019
TL;DR: This study aims to obtain data about the results of traffic in a graphical form so that it can find out the number of users who access the internet and use bandwidth in Telkom Vocational School Pekanbaru.
Abstract: Traffic analysis using the internet is an activity to record data from user activities in using the Internet. This study aims to obtain data about the results of traffic in a graphical form so that it can find out the number of users who access the internet and use bandwidth. In this study, researchers also noted when the peak internet usage time in Telkom Vocational School Pekanbaru. The method used to get the results of the study is the packet sniffing method. Researchers can filter data packets from the http protocol application. Since, user activity is more dominant in finding and downloading sites on the Internet. The tool used is wireshark, this application is greatly helpful with features that are truly supportive and easy to analyze networks.

19 citations

Proceedings ArticleDOI
12 Apr 2019
TL;DR: Results shows sensor node be able to detect polluted water parameter and water level as well flow rate and will be testing at actual site which is one of the river in Riau Province in Indonesia.
Abstract: Development of economic has impact by many industries operating along the river then create the pollution by industry waste as well as effected to river water. This research aims to develop a system to monitor river water quality in many parameters that safe for human as well as for ecosystem live in the river. Wireless Sensor Networks (WSNs) used in this design because of advantages WSNs system, a sensor node attached to many sensors such as water temperature, pH, dissolved oxygen (DO) and electricity conductivity. The river water monitoring system designed be able to monitor water level and flow rate for environmental and flooding alert. A sensor node customizes designed to fulfill water quality standard as well added others sensor for flooding alert, data collected by sensor node forward to WSNs sink node which embedded with a microcontroller unit and memory as local database before sending to backend system. Monitoring at backend system shows by some displays in order to easy monitoring by representative institution or local authority as well action will be taken if some case happen or abnormality reported by monitoring system. Prototype of WSNs node have been designed and tested, the results shows sensor node be able to detect polluted water parameter and water level as well flow rate. Furthermore, sensor node will be testing at actual site which is one of the river in Riau Province in Indonesia.

12 citations

Proceedings ArticleDOI
25 May 2016
TL;DR: The simulation produced a display that IEEE 802.11n WLAN can support up more than 100 client users e learning with web browsing activity, and estimated the number of web user clients and other network applications that could be supported by the Wireless LAN 802.
Abstract: This study is the evaluation of the performance of the Wireless Local Area Network (WLAN) 802.11n, implemented in the Faculty of Engineering, Islamic University of Riau. The study in the wake server E Learning and will be accessed using the Wireless LAN 802.11n. This simulation uses Riverbed Software Modeler and study a simulation to estimate the number of web user clients and other network applications that could be supported by the Wireless LAN 802.11n to provide certain network load. The simulation produced a display that IEEE 802.11n WLAN can support up more than 100 client users e learning with web browsing activity.

10 citations

31 Oct 2016
TL;DR: A simple home security system that is implemented using fingerprint biometrics technology that makes the system easier to implement with cheaper costs is described.
Abstract: Home security system is an emerging technology that gained much attention recently by homeowners. The conventional hardwired system is easy to install in newly developed homes; however, the existing homes require complex configuration of such systems which involves substantial cost. Hence, a wireless home security system has been an alternative to the hardwired.This paper describes a simple home security system that is implemented using fingerprint biometrics technology.The system is known as BIOmetrics FIngerprint for Home Security (BIOFIHS). BIOFIHS is demonstrated using a prototype that consists of hardware and software components.The hardware includes fingerprint sensors, a microcontroller, a wireless network router, an application server, and a smartphone. For the software, a program is developed to record the fingerprint data and to verify the data on the remote server. All of the components are connected to the home network wirelessly that makes the system easier to implement with cheaper costs.

8 citations

Journal ArticleDOI
08 Feb 2017
TL;DR: Pada penelitian ini simulasi menghasilkan tampilan bahwa WLAN IEEE 802.11N bisa mendukung sampai lebih dari 100 klien pengguna e-learning dengan aktifitas web browsing.
Abstract: Penelitian ini merupakan evaluasi kinerja tentang wireless LAN (WLAN) 802.11N yang diimplementasikan dalam suatu lingkungan fakultas. Dalam penelitian ini di bangun server E Learning dan akan di akses menggunakan Wireless LAN 802.11N. Simulasi ini menggunakan Perangkat Lunak Riverbed Modeler. Penelitian ini merupakan sebuah simulasi untuk memperkirakan jumlah klien pengguna web dan aplikasi jaringan lainnya yang bisa didukung oleh Wireless LAN 802.11N dengan memberikan beban jaringan tertentu. Pada penelitian ini simulasi menghasilkan tampilan bahwa WLAN IEEE 802.11N bisa mendukung sampai lebih dari 100 klien pengguna e-learning dengan aktifitas web browsing.

6 citations


Cited by
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Journal ArticleDOI
19 Feb 2020-Sensors
TL;DR: A multi-parameter sensing node embedding a miniaturized slime monitor able to estimate the micrometric thickness and type of slime is presented, paving the way to water monitoring with unprecedented spatio-temporal resolution.
Abstract: A smart, safe, and efficient management of water is fundamental for both developed and developing countries. Several wireless sensor networks have been proposed for real-time monitoring of drinking water quantity and quality, both in the environment and in pipelines. However, surface fouling significantly affects the long-term reliability of pipes and sensors installed in-line. To address this relevant issue, we presented a multi-parameter sensing node embedding a miniaturized slime monitor able to estimate the micrometric thickness and type of slime. The measurement of thin deposits in pipes is descriptive of water biological and chemical stability and enables early warning functions, predictive maintenance, and more efficient management processes. After the description of the sensing node, the related electronics, and the data processing strategies, we presented the results of a two-month validation in the field of a three-node pilot network. Furthermore, self-powering by means of direct energy harvesting from the water flowing through the sensing node was also demonstrated. The robustness and low cost of this solution enable its upscaling to larger monitoring networks, paving the way to water monitoring with unprecedented spatio-temporal resolution.

41 citations

Proceedings ArticleDOI
01 Nov 2018
TL;DR: In this article, a smart monitoring system using Long Range Wide Area Network (LoRa WAN) with low power wireless data communication and Internet of Things (IoT) technology is proposed to detect land and forest fire.
Abstract: Land and forest fires especially in Riau Province, Indonesia, have affected the length and breadth of Indonesia. The fires are normally hampered by seasonal dry conditions such as El Nino effect. In addition, the haze has affected the neighboring countries such as Malaysia, Singapore and south of Thailand. The effects of haze on human health as reported in that particular year were about 20 million people have suffered from respiratory problems and serious deterioration in overall health. There were other effects on environment, economy, flora and fauna in Southeast Asia region due to this disaster. This research proposes to develop a smart monitoring system using Long Range Wide Area Network (LoRa WAN) with low power wireless data communication and Internet of Things (IoT) technology. With LoRa technology, data can be transmitted up to 30 miles which is worthwhile to cover some of Riau Province that have been badly impacted by this disaster. In this article propose to develop sensors system that capable of detecting land and forest fire. The sensors will be located at several locations that has badly impacted previously. LoRa IoT Technology will be deployed to provide a platform for connecting the sensors. An early indication of land or forest fires is vital for quick prevention before they become uncontrollable and overwhelming. The design and development of LoRa sensors give high feasibility to overcome current issues in Riau Province because of land and forest fire.

31 citations

Journal ArticleDOI
TL;DR: The performance are compared to the state-of-the-art methods for the superiority of the proposed feature extraction technique and individual performance analysis has been performed at all the security levels of the propose Cancelable FaceHashing Technique.
Abstract: A novel cancelable FaceHashing technique based on non-invertible transformation with encryption and decryption template has been proposed in this paper. The proposed system has four components: face preprocessing, feature extraction, cancelable feature extraction followed by the classification, and encryption/decryption of cancelable face feature templates. During face preprocessing, the facial region of interest has been extracted out to speed the process for evaluating discriminant features. In feature extraction, some optimization techniques such as Sparse Representation Coding, Coordinate descent, and Block coordinates descent have been employed on facial descriptors to obtain the best representative of those descriptors. The representative descriptors are further arranged in a spatial pyramid matching structure to extract more discriminant and distinctive feature vectors. To preserve them, the existing BioHashing technique has been modified and extended to some higher levels of security attacks and the modified BioHashing technique computes a cancelable feature vector by the combined effect of the facial feature vector and the assigned token correspond to each user. The elements of computed cancelable feature vector are in a numeric form that has been employed to perform both verifications as well as identification task in online while the original facial feature vectors are kept offline either in hard drive or disc. Then, to enhance more security levels and also to preserve the cancelable face features, an RSA based encryption-decryption algorithm has been introduced. The proposed system has been tested using four benchmark face databases: CASIA-FACE-v5, IITK, CVL, and FERET, and performance are obtained as correct recognition rate and equal error rate. The performance are compared to the state-of-the-art methods for the superiority of the proposed feature extraction technique and individual performance analysis has been performed at all the security levels of the proposed Cancelable FaceHashing Technique. These comparisons show the superiority of the proposed system.

21 citations

Journal ArticleDOI
TL;DR: A novel darknet traffic analysis and network management framework to real-time automating the malicious intent detection process, using a weight agnostic neural networks architecture, and an automated searching neural net architecture strategy that can perform various tasks such as identifying zero-day attacks.
Abstract: Attackers are perpetually modifying their tactics to avoid detection and frequently leverage legitimate credentials with trusted tools already deployed in a network environment, making it difficult for organizations to proactively identify critical security risks. Network traffic analysis products have emerged in response to attackers’ relentless innovation, offering organizations a realistic path forward for combatting creative attackers. Additionally, thanks to the widespread adoption of cloud computing, Device Operators (DevOps) processes, and the Internet of Things (IoT), maintaining effective network visibility has become a highly complex and overwhelming process. What makes network traffic analysis technology particularly meaningful is its ability to combine its core capabilities to deliver malicious intent detection. In this paper, we propose a novel darknet traffic analysis and network management framework to real-time automating the malicious intent detection process, using a weight agnostic neural networks architecture. It is an effective and accurate computational intelligent forensics tool for network traffic analysis, the demystification of malware traffic, and encrypted traffic identification in real time. Based on a weight agnostic neural networks (WANNs) methodology, we propose an automated searching neural net architecture strategy that can perform various tasks such as identifying zero-day attacks. By automating the malicious intent detection process from the darknet, the advanced proposed solution is reducing the skills and effort barrier that prevents many organizations from effectively protecting their most critical assets.

20 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a comprehensive tutorial on enabling technologies, design considerations, requirements, and prospects of broadband schemes, and propose potential solutions to address them for fixed wireless access (FWA).
Abstract: There has been a growing interconnection across the world owing to various multimedia applications and services. Fixed wireless access (FWA) is an attractive wireless solution for delivering multimedia services to different homes. With the fifth-generation (5G) and beyond mobile networks, the FWA performance can be enhanced significantly. However, their implementation will present different challenges on the transport network due to the incessant increase in the number of required cell-sites and the subsequent increase in the per-site requirements. This paper presents a comprehensive tutorial on the enabling technologies, design considerations, requirements, and prospects of broadband schemes. Furthermore, the related technical challenges of FWA are reviewed, and we proffer potential solutions to address them. Besides, we review various transport network options that can be employed for FWA deployment. In this regard, we offer an in-depth discussion on their related requirements for different use cases. Moreover, we give an insight into the 3GPP RAN functional split implementations and implications on the 5G FWA transport network solutions. The concepts of virtualized RANs for attending flexibly to the dynamic nature of different use cases are also presented.

12 citations