A survey on internet of vehicles: Applications, security issues & solutions

Recent advancements in wireless technology have created an exponential rise in the number of connected devices leading to the internet of things (IoT) revolution. Large amounts of data are captured, processed and transmitted through the network by these embedded devices. Security of the transmitted data is a major area of concern in IoT networks. Numerous encryption algorithms have been proposed in these years to ensure security of transmitted data through the IoT network. Tiny encryption algorithm (TEA) is the most attractive among all, with its lower memory utilization and ease of implementation on both hardware and software scales. But one of the major issues of TEA and its numerous developed versions is the usage of the same key through all rounds of encryption, which yields a reduced security evident from the avalanche effect of the algorithm. Also, the encryption and decryption time for text is high, leading to lower efficiency in IoT networks with embedded devices. This paper proposes a novel tiny symmetric encryption algorithm (NTSA) which provides enhanced security for the transfer of text files through the IoT network by introducing additional key confusions dynamically for each round of encryption. Experiments are carried out to analyze the avalanche effect, encryption and decryption time of NTSA in an IoT network including embedded devices. The results show that the proposed NTSA algorithm is much more secure and efficient compared to state-of-the-art existing encryption algorithms.

https://www.mdpi.com/2073-8994/11/2/293/pdf

A Secure and Efficient Lightweight Symmetric Encryption Scheme for Transfer of Text Files between Embedded IoT Devices

Political connections, the liability of foreignness, and legitimacy: A business historical analysis of multinationals’ strategies in Chile

The impact of entrepreneurship orientation on project performance: A machine learning approach

The bank is one of the financial institutions that provide a program called Home Ownership Loans or abbreviated KPR. In performing its services the bank ensures that prospective borrowers are really able to repay the approved mortgages. For that purpose, several criteria are set to the debtor wishing to apply for Home Ownership Credit. The application of MOORA method is used to calculate criteria as a requirement of the mortgage application. It is expected that the application of Multi-Objective Optimization On The Basis Of Ratio Analysis (Moora) method can assist the decision makers who remain for the debtor candidate.

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Sistem pendukung keputusan penentukan kredit pemilikan rumah menerapkan multi-objective optimization on the basis of ratio analysis (moora)

The selection of the best employees is one of the process of evaluating how well the performance of the employees is adjusted to the standards set by the company and usually done by top management such as General Manager or Director. In general, the selection of the best employees is still perform manually with many criteria and alternatives, and this usually make it difficult top managerial making decisions as well as the selection of the best employees periodically into a long and complicated process. Therefore, it is necessary to build a decision support system that can help facilitate the decision maker in determining the best choice based on standard criteria, faster, and more objective. In this research, the computational method of decision-making system used is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The criteria used in the selection of the best employees are: job responsibilities, work discipline, work quality, and behaviour. The final result of the global priority value of the best employee candidates is used as the best employee selection decision making tool by top management.

https://iopscience.iop.org/article/10.1088/1742-6596/1028/1/012052/pdf

TOPSIS Method Application for Decision Support System in Internal Control for Selecting Best Employees

Implementation of Decision Support System for various purposes now can facilitate policy makers to get the best alternative from a variety of predefined criteria, one of the methods used in the implementation of Decision Support System is VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje), VIKOR method in this research got the best results with an efficient and easily understood process computationally, it is expected that the results of this study facilitate various parties to develop a model any solutions.

https://iopscience.iop.org/article/10.1088/1742-6596/1019/1/012034/pdf

Multi-Attribute Decision Making with VIKOR Method for Any Purpose Decision

The development of data miningis inseparable from the recent developments in information technology that enables the accumulation of large amounts of data. For example, a shopping mall that records every sales transaction of goods using various POS (point of sales). Database data from these sales could reach a large storage capacity, even more being added each day, especially when the shopping center will develop into a nationwide network. The development of the internet at the moment also has a share large enough in the accumulation of data occurs. But the rapid growth of data accumulation it has created conditions that are often referred to as \"data rich but information poor\" because the data collected can not be used optimally for useful applications. Not infrequently the data set was left just seemed to be a \"grave data\". There are several techniques used in data mining which includes association, classification, and clustering. In this paper, the author will do a comparison between the performance of the technical classification methods naïve Bayes and C4.5 algorithms.

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Data Mining Classification Comparison (Naïve Bayes and C4.5 Algorithms)

The steganography process combines mathematics and computer science. Steganography consists of a set of methods and techniques to embed the data into another media so that the contents are unreadable to anyone who does not have the authority to read these data. The main objective of the use of base64 method is to convert any file in order to achieve privacy. This paper discusses a steganography and encoding method using base64, which is a set of encoding schemes that convert the same binary data to the form of a series of ASCII code. Also, the EoF technique is used to embed encoding text performed by Base64. As an example, for the mechanisms a file is used to represent the texts, and by using the two methods together will increase the security level for protecting the data, this research aims to secure many types of files in a particular media with a good security and not to damage the stored files and coverage media that used.

https://iopscience.iop.org/article/10.1088/1742-6596/1007/1/012003/pdf

Combination Base64 Algorithm and EOF Technique for Steganography

Rabin Karp algorithm is a search algorithm that searches for a substring pattern in a text using hashing. It is beneficial for matching words with many patterns. One of the practical applications of Rabin Karp's algorithm is in the detection of plagiarism. Michael O. Rabin and Richard M. Karp invented the algorithm. This algorithm performs string search by using a hash function. A hash function is the values that are compared between two documents to determine the level of similarity of the document. Rabin-Karp algorithm is not very good for single pattern text search. This algorithm is perfect for multiple pattern search. The Levenshtein algorithm can be used to replace the hash calculation on the Rabin-Karp algorithm. The hash calculation on Rabin-Karp only counts the number of hashes that have the same value in both documents. Using the Levenshtein algorithm, the calculation of the hash distance in both documents will result in better accuracy.  

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Andysah Putera Utama Siahaan

Papers

TOPSIS Method Application for Decision Support System in Internal Control for Selecting Best Employees

Multi-Attribute Decision Making with VIKOR Method for Any Purpose Decision

Data Mining Classification Comparison (Naïve Bayes and C4.5 Algorithms)

Combination Base64 Algorithm and EOF Technique for Steganography

Combination of levenshtein distance and rabin-karp to improve the accuracy of document equivalence level