Performance Analysis of Advanced Iot Encryption on Serialization Concept: Application Optimization Approach
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(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 11, No. 12, 2020 Performance Analysis of Advanced IoT Encryption on Serialization Concept: Application Optimization Approach Johan Setiawan1, Muhammad Taufiq Nuruzzaman2* Department of Informatics Universitas Islam Negeri Sunan Kalijaga Yogyakarta Yogyakarta, Indonesia Abstract—This study investigates the effect of serialization running[8][12][14]. In tackling these threats, data encryption concepts with cipher algorithms and block mode on structured is required [15]. Encryption is a method used to convert data on execution time in low-level computing IoT devices. The original data into artificial data to become rugged and not research was conducted based on IoT devices, which are accessible for humans to read. The encryption process's currently widely used in online transactions. The result of drawback tends to impose more processing on the overheating on the CPU is fatal if the encryption load is not microprocessor embedded in an IoT device. It can result from reduced. One of the consequences is an increase in the small and limited microprocessor capabilities [16][17] and maintenance obligations. So that from this influence, the user large amounts of data in the encryption process [18]–[20]. As experience level will have bad influence. This study uses a result of an encryption algorithm's complexity, the experimental methods by exploring serialization, ciphers, and microprocessor on the IoT device is more burdened. block mode using benchmarks to get better data combination algorithms. The four test data groups used in benchmarking will The direct effect of microprocessor devices that get high produce an experimental benchmark dataset on the selected loads or pressures to overheat is the length of the computation AES, Serpent, Rijndael, BlowFish, and block mode ciphers. This process of a device so that it affects UX (User Experience) study indicates that YAML minify provides an optimal because it can reduce the level of efficiency [21][22] Users encryption time of 21% and decryption of 27% than JSON will feel bored in waiting for computation so that it has an Pretty if an average of the whole test is taken. On the other hand, impact on ongoing business processes [21][22][23][24]. On the AES cipher has a significant effect on the encryption and the other hand, the impact of overheating microprocessor decryption process, which is 51% more optimal for the YAML pressure is that the device is not durable. It harms device minify serialization providers that have to carry out more routine maintenance. In Keywords—Internet of Things; benchmark; cipher; block [3] research discussed one method of encrypting data with a mode; serialization Catalan object base and two structural combinations on IoT devices; however, that study did not discuss the concept of I. INTRODUCTION serialization in structured data to the encryption process. Computers and IoT are useful in assisting the activities of Therefore, The research related to the analysis and evaluation certain individuals or business groups. These business of several algorithms that are often used in data encryption domains include Trade, Transportation, Health [1]–[4], and which includes; AES, Rijndael, Serpent and Blowfish. The other specific matters discussed in research [5]–[7]. With the encryption process uses several different data serialization expansion of computers, all devices equipped with a concepts to improve application performance on IoT systems microprocessor have been embedded to sustain mobility and thus that it can provide less computation, time and memory the device's toughness. Devices controlled automatically or and provide a better impact on user UX (User Experience) remotely are a family of IoT (Internet of Things) supporting while sustaining a level of security information. At the same devices. IoT uses the M2M (machine-to-machine) concept time, the advantages for companies that will be gained from communication[8] without any human relationship [2][9]. this article are used as an option for IoT device providers in dealing with the problem of overheating on the low-level Communication between IoT devices uses information computational microprocessor utilized. data and instructions that have been designed or regulated by the manufacturer. The information sent and received by The rest of this article is organized as follows. Section II devices usually does not want to be known or understood by discusses previous research that has been carried out as a parties or devices [10][4][11][12] with no interest in literature study for the author. Section III discusses the destroying or converting the information. Therefore, research methods used. The experiment is a method used by manufacturers should consider durability and safety at a low the author to obtain benchmark data on a combination of cost [13]. The information security risks can be in the form of serialization, cipher and block mode. Section IV provides data modifications or interruptions, and these risks can affect the design, benchmark flow design, data collection process and continuity of the process or business flow that is analysis process from experiments. Section V concludes this article. *Corresponding Author 673 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 11, No. 12, 2020 II. RELATED WORKS Data is an essential thing in business that must be secured when transmitted over public networks. It relates to attacks that threaten data modification and interruption. Encryption and data authentication schemes that are implemented can shield data from these attacks to not be read by unauthorized people [4][10]. Nevertheless, on the other hand, encryption Fig. 1. Research Method. can burden the microprocessor [3], resulting in overheating. TABLE I. IOT HARDWARE SPECIFICATION Sudip Maitra et al. Have published research related to evaluating the performance of the encryption algorithm on IoT Type Specifications devices with the XTEA and AES algorithms to obtain an CPU Manufacture AllWinner / ARMv7 algorithm with more optimal memory, time, and energy. The research has been conducted using an experimental method CPU Core 4 Cores utilizing an oscilloscope device to help identify the energy CPU Speed 1.5 GHz consumed in the encryption process. From these results, it was RAM 512 MB found that the XTEA algorithm is better in terms of efficiency if the IoT device does not use the AES accelerator [18]. On Disk 32 GB the other hand, Geovandro C. et al. Has researched the OS Linux Ubuntu 18.04 LTS evaluation of cryptographic algorithms' performance on IoT and operating systems [17]. B. Data Collection Data will operate as serialized data in JSON and YAML Nur Rachmat et al. has implemented the analysis of the with the pretty and minify schemes in this process. From some performance of Rijndael, Serpent, Twofish on an android of these data serialization concepts, the next step is to smartphone. The conclusion of the research that Serpent has benchmark the data encryption process to adjust the system or good performance at execution time [25]. Furthermore, algorithm to get better processing on specific platforms [29]. Muzafer H. Saračević et al. have been carried out providing a The benchmarking process in this study uses the Golang proposal to use encryption on Catalan object-based IoT and programming language. The author uses that in benchmarking two structural combinations. In this research, the whole to get data benchmarks with low-level programming procedure is based on the Catalan number's characteristics and languages [30]. Thus the golang application will be compiled the representation numbers and combinatorial problems. Apart into binary so that it becomes faster [31]. from improving the quality of encryption, that study recommended lightweight computing like e-health and smart C. Data Grouping cities [3]. Moreover, several studies are almost similar in The grouping process will determine the percentage level [26]–[28]. of time efficiency or processing carried out in the encryption III. RESEARCH METHOD and decryption process. The process will group on the type of encryption or decryption used based on data serialization. Researchers use the research method to collect data that From the benchmark results obtained, researchers can followed up as material for investigation and analysis. The compare these results. A more efficient variety of data research method provides information from the research serialization, cipher, and block mode combination will be design to be composed of time, place, and data source. At this discovered for the IoT application encryption and decryption condition, the researcher applies experimental research process. methods. It will provide an overview of the effect of data serialization of pretty JSON, JSON minify, YAML, and IV. RESULT AND DISCUSSIONS YAML minify as machine-to-machine communication. It is against several encryption algorithms/ciphers at AES, A. Benchmark Design Blowfish, Rijndael, and Serpent on IoT devices to get better Several schemes of the data structure to be used in the device performance. The steps taken in this study were benchmark have different characteristics so that the data used coding, data collection, data grouping, benchmarking, and the will have various levels of influence. The data sample is analysis process. The procedure of the research method used traditional data commonly used in communication between in this study can be seen in Fig. 1. devices. The traditional JSON data structure is used as a variety of file sizes, including 1.5 KB, 2.1 KB, 3.0 KB and 3.5 A. Research Tools KB. The data will be converted with serialization concept. Tools are vastly crucial in research since it can affect the results of the analysis to be performed. This study uses an IoT At this step, some of the cipher and block mode algorithms device in the form of Orange Pi Zero. It is a tiny computing listed in Table II will be designed as a benchmark process device with a more complex system to assist the data stage executed after the data serialization process.