Lightweight Declarative Server-Side Web Programming

The purpose of this paper is to create an expert system to detect oil palm plant diseases in order to help farmers / companies in providing accurate information about the diseases of oil palm plants and how to overcome them and to help reduce the risk of decreasing palm oil production. This system is designed to mimic the expertise of an expert who is able to detect diseases that attack oil palm plants. The method used is forward chaining that is starting from a set of data and proving a fact by describing the level of confidence and uncertainty found in a hypothesis. The results of this study are to diagnose diseases of oil palm plants and their computerization using web programming languages.

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SISTEM INFORMASI PARIWISATA SEBAGAI MEDIA PROMOSI PADA DINAS KEBUDAYAAN DAN PARIWISATA KOTA TIDORE KEPULAUAN

10.31219/osf.io/bxrzn ◽

2019 ◽

Author(s):

IJIS - Indonesian Journal On Information System

Keyword(s):

Web Programming

Untuk mengetahui potensi wisata diperlukan system computer untuk membangun dan merancang sebuah system informasi pariwisata yang terintergrasi kedalam sebuah database berbasis web programming. Penelitian dilakukan pada Dinas Kebudayaan dan Pariwisata Kota Tidore Kepulauan, Metode yang digunakan dalam penelititan ini adalah menggunakan metode waterfall yang merupakan bagian dari SDLC (siklus hidup system) yang memiliki beberapa tahapan dalam pembangunan system, Teknik dalam pengumpulan data yaitu dengan cara studi pustaka dan literature, metode studi pustaka digunakan untuk pencarian dan pengumpulan data, software recruitment yang digunakan seperti, macromedia dreamwaver, PHP MySQL, Local Server serta hardware yang kompatibel dalam menunjang pembuatan sistem informasi promosi pariwisata. Hasil yang diharapkan adalah dengan adanya system informasi pariwisata ini dapat membantu promosi dan pengenalan tentang pariwisata di Kota Tidore Kepulauan, referensi belajar untuk pelajar dan mahasiswa serta pusat data bagi instansi yang terkait dengan pariwisata.Kesimpulannya adalah dengan adanya sistem informasi pariwisata berbasis web ini dapat membuka akses dan jaringan didaerah agar lebih dikenal secara nasional maupun internasional.

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DYNAMIC REST SERVICES ORCHESTRATION USING THE KNOWLEDGE BASE

Visnyk Universytetu “Ukraina” ◽

10.36994/2707-4110-2019-1-22-26 ◽

2019 ◽

Author(s):

Kostyantyn Kharchenko

Keyword(s):

Knowledge Base ◽

Service Oriented Architecture ◽

Main Idea ◽

The Real ◽

Server Side ◽

Service Oriented ◽

Services Orchestration ◽

Client Side ◽

Abstract Operation ◽

Microservice Architecture

The approach to organizing the automated calculations’ execution process using the web services (in particular, REST-services) is reviewed. The given solution will simplify the procedure of introduction of the new functionality in applied systems built according to the service-oriented architecture and microservice architecture principles. The main idea of the proposed solution is in maximum division of the server-side logic development and the client-side logic, when clients are used to set the abstract computation goals without any dependencies to existing applied services. It is proposed to rely on the centralized scheme to organize the computations (named as orchestration) and to put to the knowledge base the set of rules used to build (in multiple steps) the concrete computational scenario from the abstract goal. It is proposed to include the computing task’s execution subsystem to the software architecture of the applied system. This subsystem is composed of the service which is processing the incoming requests for execution, the service registry and the orchestration service. The clients send requests to the execution subsystem without any references to the real-world services to be called. The service registry searches the knowledge base for the corresponding input request template, then the abstract operation description search for the request template is performed. Each abstract operation may already have its implementation in the form of workflow composed of invocations of the real applied services’ operations. In case of absence of the corresponding workflow in the database, this workflow implementation could be synthesized dynamically according to the input and output data and the functionality description of the abstract operation and registered applied services. The workflows are executed by the orchestrator service. Thus, adding some new functions to the client side can be possible without any changes at the server side. And vice versa, adding new services can impact the execution of the calculations without updating the clients.

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Optimized watershed delineation library for server-side and client-side web applications

Open Geospatial Data Software and Standards ◽

10.1186/s40965-019-0068-9 ◽

2019 ◽

Vol 4 (1) ◽

Cited By ~ 3

Author(s):

Muhammed Sit ◽

Yusuf Sermet ◽

Ibrahim Demir

Keyword(s):

Web Applications ◽

Server Side ◽

Watershed Delineation ◽

Client Side

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A Password Meter without Password Exposure

Sensors ◽

10.3390/s21020345 ◽

2021 ◽

Vol 21 (2) ◽

pp. 345

Author(s):

Pyung Kim ◽

Younho Lee ◽

Youn-Sik Hong ◽

Taekyoung Kwon

Keyword(s):

Performance Enhancement ◽

Homomorphic Encryption ◽

Optimization Techniques ◽

Third Party ◽

Fully Homomorphic Encryption ◽

Performance Achievement ◽

Server Side ◽

On Line ◽

Internal Mechanism ◽

High Chance

To meet password selection criteria of a server, a user occasionally needs to provide multiple choices of password candidates to an on-line password meter, but such user-chosen candidates tend to be derived from the user’s previous passwords—the meter may have a high chance to acquire information about a user’s passwords employed for various purposes. A third party password metering service may worsen this threat. In this paper, we first explore a new on-line password meter concept that does not necessitate the exposure of user’s passwords for evaluating user-chosen password candidates in the server side. Our basic idea is straightforward; to adapt fully homomorphic encryption (FHE) schemes to build such a system but its performance achievement is greatly challenging. Optimization techniques are necessary for performance achievement in practice. We employ various performance enhancement techniques and implement the NIST (National Institute of Standards and Technology) metering method as seminal work in this field. Our experiment results demonstrate that the running time of the proposed meter is around 60 s in a conventional desktop server, expecting better performance in high-end hardware, with an FHE scheme in HElib library where parameters support at least 80-bit security. We believe the proposed method can be further explored and used for a password metering in case that password secrecy is very important—the user’s password candidates should not be exposed to the meter and also an internal mechanism of password metering should not be disclosed to users and any other third parties.

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Deep PUF: A Highly Reliable DRAM PUF-Based Authentication for IoT Networks Using Deep Convolutional Neural Networks

Sensors ◽

10.3390/s21062009 ◽

2021 ◽

Vol 21 (6) ◽

pp. 2009

Author(s):

Fatemeh Najafi ◽

Masoud Kaveh ◽

Diego Martín ◽

Mohammad Reza Mosavi

Keyword(s):

Error Correction ◽

Random Access ◽

Error Correction Codes ◽

Access Memory ◽

Deep Convolutional Neural Networks ◽

Device Identification ◽

Physical Unclonable Functions ◽

Server Side ◽

Correction Technique ◽

Reduction Methods

Traditional authentication techniques, such as cryptographic solutions, are vulnerable to various attacks occurring on session keys and data. Physical unclonable functions (PUFs) such as dynamic random access memory (DRAM)-based PUFs are introduced as promising security blocks to enable cryptography and authentication services. However, PUFs are often sensitive to internal and external noises, which cause reliability issues. The requirement of additional robustness and reliability leads to the involvement of error-reduction methods such as error correction codes (ECCs) and pre-selection schemes that cause considerable extra overheads. In this paper, we propose deep PUF: a deep convolutional neural network (CNN)-based scheme using the latency-based DRAM PUFs without the need for any additional error correction technique. The proposed framework provides a higher number of challenge-response pairs (CRPs) by eliminating the pre-selection and filtering mechanisms. The entire complexity of device identification is moved to the server side that enables the authentication of resource-constrained nodes. The experimental results from a 1Gb DDR3 show that the responses under varying conditions can be classified with at least a 94.9% accuracy rate by using CNN. After applying the proposed authentication steps to the classification results, we show that the probability of identification error can be drastically reduced, which leads to a highly reliable authentication.

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