Malicious People Research Articles

Blockchain-enabled transparent traffic enforcement for sustainable road safety in cities

With the progress of the times, cars have become an important means of transportation in our lives. However, with new cars of all kinds, road safety issues still cannot be effectively improved. While countries have responded by enforcing traffic laws and using electronic technology to enhance enforcement, challenges still need to be addressed, including blurred images and misjudgments by police agencies, and even exploiting loopholes in traffic enforcement frameworks to evade consequences through bribery or connections. exacerbating an accident and leaving victims and families in the lurch of the aftermath. To solve this problem, we proposed a data traceability law enforcement system based on blockchain and InterPlanetary File System (IPFS). The system ensures rapid traceability and protects law enforcement data from external attacks. The goal of leveraging blockchain’s decentralized nature and smart contracts is to instill accountability and fairness in road safety measures, mitigate the effects of corruption, and pave the way for a safer and more just transportation environment. Our experimental results show that under our stress test of 50 transactions per second, the throughput can be as high as 300 and the maximum delay can reach 2.01s, which is enough to experimentally prove that our system is feasible. Our approach is designed to solve the data corruption problem caused by the centralized server being paralyzed. It applies to all technology enforcement, with high flexibility and scalability for all participants to join or set privileges. we also provide an automated traffic law enforcement system in a smart city. To make the data storage more secure and fair, and not easily damaged by malicious people or tampered with by intentional attackers. This brings a breakthrough to the country’s program security.

A Novel Model Based on Ensemble Learning for Phishing Attack

With the increase in the speed of the internet environment and the development of the infrastructures used, people have started to perform most of their work online. As much as this makes life easier, it also increases the possibility of being attacked by malicious people. Attackers can activate a phishing attack that aims to steal information from victims by creating copied, fake websites. While this attack is very old and somewhat simple, it can still be effective due to low IT literacy. People can enter their information on these fake websites out of spontaneity or ignorance or good intentions and be exposed to Phishing attacks. The compromise of a user's account information also puts at risk the security of the organization or institution to which it is connected. In this study, we propose a new machine learning-based ensemble model with feature selection methods to detect phishing attacks. Also, an ablation study is presented to measure the effect of different feature selection methods. The proposed model which we named as NaiveStackingSymmetric (NSS) is analyzed using the widely used accuracy (ACC), the area under curve (AUC), and F-score metrics as well as the polygon area metric (PAM), and it is shown that it outperforms other studies in the literature using the same dataset.

Machine learning-based identification of cybersecurity threats affecting autonomous vehicle systems

With the advancement of humanity, transportation and trade activities have increased, leading to the development process of basic land vehicles as more than physical power became necessary. Hand tools were developed with the invention of the wheel, followed by animal-powered vehicles, and then steam engine technology. After the advancement of electromechanical technologies, today's modern vehicles have been developed. Those who used these vehicles thought of transferring control from the human to autonomous driving systems to solve their safety and comfort problems. Today, instead of fully autonomous systems targeted for the future, autonomous driving support systems have been developed. Although these systems aim to increase the safety and comfort of passengers, they can become an easy target for malicious people due to network technologies and remote connection features. The most effective method of protection from these attackers is to conduct vulnerability analysis against newly emerging threats for the systems we use and to rectify identified vulnerabilities. In this research paper, the weaknesses of wireless communication towards remote connection usage of the mini electric autonomous vehicle were investigated, which we developed and produced its mechanics, electronics, and software. In this context, a test environment was created, and the problems and threats in autonomous driving technology were revealed through attacks (Deauth Attack, DoS, DDoS and MitM) made on the test environment. Following the exposed vulnerabilities, studies were conducted for the detection of these attacks using Artificial Intelligence. In the study, different algorithms were used to detect the attacks, and random forest algorithm successfully detected 96.1% of attacks. The main contribution to the field of cybersecurity in autonomous vehicles by providing effective solutions for threat identification and defense.

Unveiling the Veil: hacking using debugger GNU

In this present research, the tools such as debuggers and their use for ethical debugging and unethical, malicious use are analyzed. Debugger tool, in general, is used to analyze a program and make code debugging to detect vulnerabilities. But in reality, malicious people like cyber attackers are using such tools to misuse the system, find weak areas, and infect the system for malicious interests. Application-based interferences, containing based transformation of variables, malicious code penetration, security mechanism bypass, and the exploitation of weakness are the main functions of misusing a debugger tool. GNU or GDB debugger is used as a demo in this report to show how it is used. The paper also finds out ways to give security to the application by detecting the problem, avoiding any unauthorized intrusion, making preventive measures, and using roust coding policies. Developer awareness must also be enhanced to detect and predict such misuse of their program and take security measures to lower threats.

BJWT-EHR: A novel JWT based Blockchain System for Electronic Health Records

Since most transactions in the world now take place digitally, it is crucial to maintain data integrity, share data securely, and provide quick access to it. Our reliance on computers in our daily lives is growing, and new data will inevitably be generated to meet this need. Providing for safe data exchange is becoming increasingly crucial every day. Maintaining and safeguarding the security of this data is crucial. Recently, the term "blockchain" has been used extensively for data security. A decentralized digital ledger called blockchain is in charge of preserving data integrity and facilitating safe data sharing. Blockchain transfers data by the principle of transparency, records data one way, and prevents reverse engineering. According to reports, blockchain is the general term for the technology that promotes common data sharing of these recorded data and reduces access times, essential for preserving data security. There are several risks to patients' privacy when information from medical records is stolen or altered. The damage caused by malicious people with this information causes serious harm to both the patient and the financing institution. Therefore, cloud-based EHR (electronic health records) is becoming a focal point in many areas. Storing patient data, ensuring data accuracy, protecting data confidentiality, and ensuring fast data transmission in the cloud system is a significant concerns in the healthcare industry. In this study, the layered architecture structure is also addressed in addition to the blockchain for sharing health data with the help of cloud service providers while providing data access control and auditing for EHR records. To enter this layered architectural system, new solutions are proposed by applying JWT (JSON web token) and hashing function of patient information. This proposed method manages and controls the patient's health records electronically. Therefore, these technologies used in the blockchain platform open new doors to more secure and sustainable solutions.

Water Quality Estimation and Anomaly Detection: A Review

Critical infrastructures that provide irreplaceable services are systems that contain industrial control systems (ICS) that can cause great economic losses, security vulnerabilities and disruption of public order when the information in it is corrupted. These ICSs, which were previously isolated, have now become systems that contain online sensors, wireless networks and artificial intelligence technologies. This situation has also increased the scope of attacks by malicious people who intend to carry out industrial espionage and sabotage these systems. In this study, water quality estimation systems and anomaly detection are comprehensively examined. In this direction, the statistics of the studies in the literature, the methods for water quality anomaly detection, the existing data sets, and the difficulties encountered in the water systems to achieve better water management are discussed. Principle findings of this research can be summarized as follows: (i) new methodologies and architectures have improved water quality assessment through anomaly detection, (ii) different datasets including multi-modal information have been presented, and (iii) remaining challenges and prospects have been investigated.

THE RELATIONSHIP BETWEEN FAITH AND POLITICS IN THE FIRST PERIOD IN SALIM IBN ZEKWAN’S WORK “AS-SIRA”

In the book “as-Sira”, Salim ibn Zekwan has presented the essential codes of the Kharijites/Ibadi thought and the relationship between faith and politics in the early period. In “as – Sira” he reflected the specific examples of the Kharijites/Ibadi thought in faith and action context by using explanation of events of the time of Hazrat Osman and Hazrat Ali. Also, Salim has become one of the important figures of this thought by evaluating political events in the context of faith. Religion is one of the most effective values in the life of an individual and society. It is a motivation that influences, directs and gives enthusiasm and spirit to the individual and society. Therefore, religion does not serve any political, legal, individual and social purpose. Also, it cannot be sacrificed to a false belief or thought and fanaticism. When religious texts are taken out of their context, they can be misunderstood. One of the problematic reasons for religious fanaticism is the commentaries that contradict the purpose when they assign a meaning to divine orders and apply them to daily life. It causes chaos and discomfort trying to force your own political and intellectual views as absolute truths and imposing them on others. As a result of that people are directed to the wrong direction and purpose, they are divided, grouped, separated and become enemies to one another. Thus, religion, which its real purpose is making people live in unity, equality and sense of brotherhood, appears as a problem and chaos by being got off its point. Especially, it turns into means of violence, oppression and chaos in the hands of some malicious people. The Holy Quran has established the faith as high and sacred value principles. It invites people to believe in these values independently and gives people the freedom to accept or reject the values of Islamic faith. It does not accept any pressure or direction on this subject. Allah has not given a right to anyone or organization to make pressure or coercion in worships. The Quran has ordered Prophet Muhammad to preach revelation and not to put pressure upon this issue.

A Hybrid Spam Detection Framework for Social Networks

The widespread use of social networks has caused these platforms to become the target of malicious people. Although social networks have their own spam detection systems, these systems sometimes may not prevent spams in their social networks. Spam contents and messages threaten the security and performance of users of these networks. A spam account detection framework based on three components is proposed in this study. Short link analysis, machine learning and text analysis are the components used together in the proposed framework. First, a dataset was created for this purpose and the attributes of spam accounts were determined. Later, the hyperlinks in the messages in this dataset were analyzed through link analysis component. The machine learning component was modelled through attributes. Moreover, the messages of the social network users were analyzed through text analysis method. A web-based application of the proposed model was put into practice. As a result of the experimental studies carried out thanks to the framework, it was determined that the proposed framework showed a performance of 95.69 %. The success of this article was calculated according to the F-measure and precision evaluation metrics under the influence of sensitive content rate. It is aimed to detect spam accounts on social network and the spam detection policy of these networks is intended to support.

An Overview of Parallel Symmetric Cipher of Messages

Background:
 Despite significant developments in communications and technology, data protection has established itself as one of the biggest concerns. The data must be encrypted in order to link securely, quickly through web-based technological data transmission. Transforming plain text into ciphered text that cannot be read or changed by malicious people is the process of encryption.
 Materials and Methods:
 In order to maintain the required degree of security, both the cryptanalysis and decryption operations took a significant amount of time. However, in order to cut down on the amount of time required for the encryption and decryption operations to be completed, several researchers implemented the cryptography method in a parallel fashion. The research that has been done on the problem has uncovered several potential answers. Researchers used parallelism to improve the throughput of their algorithms, which allowed them to achieve higher performance levels on the encryption algorithm.
 Results:
 Recent research on parallel encryption techniques has shown that graphics processing units (GPUs) perform better than other parallel platforms when comparing their levels of encryption performance.
 Conclusion:
 To carry out comparison research on the most significant parallel crypto algorithms in terms of data security efficacy, key length, cost, and speed, among other things. This paper reviews various significant parallel algorithms used for data encryption and decryption in all disciplines. However, other criteria must be considered in order to show the trustworthiness of any encryption. Randomness tests are very important to discover and are highlighted in this study.

Application of interval type-2 fuzzy logic and type-1 fuzzy logic-based approaches to social networks for spam detection with combined feature capabilities.

Social networks are large platforms that allow their users to interact with each other on the Internet. Today, the widespread use of social networks has made them vulnerable to malicious use through different methods such as fake accounts and spam. As a result, many social network users are exposed to the harmful effects of spam accounts created by malicious people. Although Twitter, one of the most popular social networking platforms, uses spam filters to protect its users from the harmful effects of spam, these filters are insufficient to detect spam accounts that exhibit new methods and behaviours. That's why on social networking platforms like Twitter, it has become a necessity to use robust and more dynamic methods to detect spam accounts. Fuzzy logic (FL) based approaches, as they are the models such that generate results by interpreting the data obtained based on heuristics viewpoint according to past experiences, they can provide robust and dynamic solutions in spam detection, as in many application areas. For this purpose, a data set was created by collecting data on the twitter platform for spam detection. In the study, fuzzy logic-based classification approaches are suggested for spam detection. In the first stage of the proposed method, a data set with extracted attributes was obtained by applying normalization and crowdsourcing approaches to the raw data obtained from Twitter. In the next stage, as a process of the data preprocessing step, six attributes in the binary form in the data set were subjected to a rating-based transformation and combined with the other real-valued attribute to create a database to be used in spam detection. Classification process inputs were obtained by applying the fisher-score method, one of the commonly used filter-based methods, to the data set obtained in the second stage. In the last stage, the data were classified based on FL based approaches according to the obtained inputs. As FL approaches, four different Mamdani and Sugeno fuzzy inference systems based on interval type-1 and Interval Type-2 were used. Finally, in the classification phase, four different machine learning (ML) approaches including support vector machine (SVM), Bayesian point machine (BPM), logistic regression (LR) and average perceptron (Avr Prc) methods were used to test the effectiveness of these approaches in detecting spam. Experimental results were obtained by applying different FL and ML based approaches on the data set created in the study. As a result of the experiments, the Interval Type-2 Mamdani fuzzy inference system (IT2M-FIS) provided the highest performance with an accuracy of 0.955, a recall of 0.967, an F-score 0.962 and an area under the curve (AUC) of 0.971. However, it has been observed that FL-based spam models have a higher performance than ML-based spam models in terms of metrics including accuracy, recall, F-score and AUC values.

SAR Image Ship Target Detection Adversarial Attack and Defence Generalization Research.

The synthetic aperture radar (SAR) image ship detection system needs to adapt to an increasingly complicated actual environment, and the requirements for the stability of the detection system continue to increase. Adversarial attacks deliberately add subtle interference to input samples and cause models to have high confidence in output errors. There are potential risks in a system, and input data that contain confrontation samples can be easily used by malicious people to attack the system. For a safe and stable model, attack algorithms need to be studied. The goal of traditional attack algorithms is to destroy models. When defending against attack samples, a system does not consider the generalization ability of the model. Therefore, this paper introduces an attack algorithm which can improve the generalization of models by based on the attributes of Gaussian noise, which is widespread in actual SAR systems. The attack data generated by this method have a strong effect on SAR ship detection models and can greatly reduce the accuracy of ship recognition models. While defending against attacks, filtering attack data can effectively improve the model defence capabilities. Defence training greatly improves the anti-attack capacity, and the generalization capacity of the model is improved accordingly.

Supervised Character Resemble Substitution Personality Adversarial Method

With the development of science and computer technology, social networks are changing our daily lives. However, this leads to new, often hidden dangers in areas such as cybersecurity. Of these, the most complex and harmful is the Advanced Persistent Threat attack (APT attack). The development of personality analysis and prediction technology provides the APT attack a good opportunity to infiltrate personality privacy. Malicious people can exploit existing personality classifiers to attack social texts and steal users’ personal information. Therefore, it is of high importance to hide personal privacy information in social texts. Based on the personality privacy protection technology of adversarial examples, we proposed a Supervised Character Resemble Substitution personality adversarial method (SCRS) in this paper, which hides personality information in social texts through adversarial examples to realize personality privacy protection. The adversarial examples should be capable of successfully disturbing the personality classifier while maintaining the original semantics without reducing human readability. Therefore, this paper proposes a measure index of “label contribution” to select the words that are important to the label. At the same time, in order to maintain higher readability, this paper uses character-level resemble substitution to generate adversarial examples. Experimental validation shows that our method is able to generate adversarial examples with good attack effect and high readability.

A Contribution to Ottoman Tafsir Culture: An Analysis of Mehmed Fawzî Efendi's Tafsir of Surah Tefrîj al-qalaq fî tafsîri sûrat al-Falaq from an ishari Perspective

Bu çalışmada Osmanlının ondokuzuncu asrında yaşamış önemli simalardan biri olan Mehmed Fevzî Efendi ve onun Tefrîcu’l-kalak fî tefsîri sûreti’l-felak adlı eseri ele alınmaktadır. Bu amaçla önce müellifin hayatı, yaşadığı dönem ve eserleri hakkında bilgiler verilmektedir. Ardından tefsir ve tasavvuf alanındaki yeri konusunda bilgiler serdedilmektedir. Müellifin Tefrîcu’l-kalak adlı tefsiri hakkına bilgi vermeden önce, Felak suresi tefsiri olması hasebiyle daha önce yazılmış bazı Felak suresi tefsirlerinden bahsedilmektedir. Bundan sonra Tefrîcu’l-kalak’ın işârî yönü üzerinde durulmaktadır. Felak suresinin tefsiri olan eserde ayetlerin ele alınış ve tefsir ediliş tarzı işlenmektedir. Eserde dirâyî ve rivâyî yöntemler yanında bilhassa işârî yöntemle yapılan yorumlara dikkat çekilmektedir. Müellif, bu yorumları daha ziyade hâl ehli diyebileceğimiz kimselerin hayatlarından örnekler vererek incelemektedir. Kerâmet türünden olan ve olağanüstü bir nitelik arz eden bu hikâyeler verildikten sonra okuyucunun bunlardan ibret ve ders alması yönünde uyarılar yapılmaktadır. Müellif, dönemin şartları gereği sosyo-ekonomik sıkıntı yaşayanlara, bireysel nedenlerden dolayı psikolojik sorunlar içinde bunalanlara bu eseriyle adeta bir kurtuluş reçetesi sunmaktadır. Bilhassa sabır, tevekkül, tefekkür, zikir, şükür, tasadduk, sıla-i rahim, şükür, dua gibi güzel hasletlere dikkat çekerek kişinin bunları dilinden, aklından, gönlünden eksik etmemesi gerektiğini anlatmaktadır. Müellif, aynı zamanda sihir ve yapılmış olan sihre karşı nasıl davranılacağı, büyüden hangi yöntemlerle kurtulabileceği hususlarında da geniş bilgiler vermektedir. Yine eserde kötü niyetli insanlardan, kötülüğü emreden nefisten, şeytan ve cin gibi varlıklardan gelebilecek zararlar ve bunlara karşı korunma yollarına dair bilgiler de aktarılmaktadır. Osmanlı’nın son dönemine ait mühim eserlerden biri olan Tefrîcu’l-kalak’ın yazıldığı dönemdeki anlayışı yansıtması bakımından önemine dikkat çekilmektedir. Ayrıca beyan ettiği hususlar ve yaşanan psiko-sosyal sorunlara karşı serdettiği çareler bakımından bugünün insanı için de ehemmiyet arz ettiğine işaret edilmektedir. Bu çalışmayla Osmanlı tefsir kültürüne bir nebze de olsa bir katkı sağlanmak hedeflenmektedir.

Risk management in digitalized educational environments: Teachers' information security awareness levels.

With the spread of Information and Communication Technologies (ICT) tools and the Internet, Twenty first century technologies have significantly affected human life, and it has been desired to be obtained continuously. It has become challenging to protect information due to the increase in the methods by which malicious people can get information. As a result, it is crucial to determine people’s awareness levels by revealing the risks and threats to information security. In this context, a study was conducted to show the awareness levels of teachers who come after the family in raising conscious individuals in society. For this purpose, a quantitative research method was adopted for the problem and sub-problems that form the basis of the research. The survey model, one of the research designs used within the framework of the quantitative research method, was used. Information Security Awareness Scale was applied to 394 teachers, and according to the results obtained, it was determined that the information security awareness level of the teachers was moderate. According to the attacks and threats sub-dimension, which includes technical issues, it has been determined that the awareness levels of the teachers are at a medium level. The study results show that female teachers’ information security awareness levels are lower than male teachers. In comparison, the awareness levels of those who received information security awareness training and information technology teachers are higher.

Bogac Han in Dede Korkut

Yaşadıkları coğrafya ve iklim koşullarıyla uyum içerisinde hayatını devam ettirmiş Türklerin tarihinde ve Türk halk edebiyatında destanlar önemli bir yere sahiptir. Dede Korkut Destanları Türk destanları içerisinde önemli bir yere sahiptir. Dede Korkut’ta birçok kişi adı geçmektedir. Bunlardan biri Boğaç Han’dır. Boğaç Han’ın adı Dede Korkut Kitabı’nda bir boyda geçmektedir. Dede Korkut’ta önemli bir yere sahip olan Boğaç Han tipinde en eskisi tarihin derinliklerine uzanan birçok tarihi-destani-efsanevi-mitolojik tabaka bulunmaktadır. Dirse Han Oğlu Boğaç Han Boyu’nun kökleri tarihi-mitolojiktir. Destanın eski devirlere uzanan bir en alt tabakası olabilir. Dirse Han Oğlu Boğaç Han Boyu aslında üzücü bir tarihi olayın, baba-oğul arasındaki bir taht ve hükümdarlık mücadelesinin destanileşmiş, masumaneleşmiş bir yansımasıdır. Konusu, Türk ve dünya tarihinde benzerleri görülen bir olaydır. Bu durum destanın tarihi yönüyle ilgilidir ve destanın tarihi bağlarını yansıtmaktadır. Dirse Han Oğlu Boğaç Han Boyu’nda, Kırk Mert, eski Türk hükümdar, bey ve teginlerinin yanlarında yer alan bürokratik yapının, görevlilerin destani bir yansımasıdır. Destanda Kırk Mert sonradan Kırk Namert’e dönüşmüştür. Destandaki Kırk Namert ise, hükümdarın yanındaki kötü niyetli ve çıkarcı kişilerin, beylerin ve onların yönetimindeki yozlaşmış bürokratik yapının bir yansımasıdır. Dirse Han Oğlu Boğaç Han Boyu birçok mesajlar vermektedir. Bu makalede, Dede Korkut’taki Boğaç Han; adı, ailesi, tarihteki, Dede Korkut’taki ve destanlardaki yeri incelenmiştir.

A Product Production and Transfer Application with Blockchain

In traditional software systems, user information is kept in databases of the system. Much of this information is critical. Theft of data and getting into the hands of malicious people can cause big problems. The most efficient way to get rid of this is to keep the information encrypted, to decrypt the encrypted information with private keys that are not registered in the system, to never access the encrypted information without the private key, and to use it in platform-independent systems. Blockchain technology offers us this system. Blockchain technology, which can be applied very easily in economic fields or systems with transparent data policy of priority, is also the basic structure of cryptocurrencies. Its importance is increasing day by day in the world and it is increasing its weight in banking-finance, voting, asset management and company-specific software systems. In this study, encryption methods of Blockchain technology, data verification approaches, wallet creation, the roles of public and private keys in wallets in the system, their authorization, the formation of transfers within a certain rule and their verification by a third party after the transfer are discussed theoretically and practically. An application was developed on peer-to-peer transfers of white goods production and products, which were fictionalized as a scenario, and Blockchain technology was applied.

Evolution of IoT Security: The Era of Smart Attacks

Internet of Things devices have become the new privileged targets for cyberattackers in recent years. This is in part due to the amount of sensitive data they provide. In parallel, security systems are becoming more and more robust with the help of machine learning (ML) algorithms. However, this advance can also benefit malicious people. In recent years, ML-based smart attacks have emerged and are significantly changing the threat landscape. This article focuses on the point of view of the attacker. We have designed a new attack framework based on Markov chain theory. The goal of this latter is to maximize the success probability of attacks while minimizing energy consumption. We tested this framework on both passive and active jamming attacks, thus exhibiting the effectiveness of our approach when compared against basic eavesdropping and jamming attacks. We show that this new type of attack can cut by half the energy consumption of an eavesdropping attack, while maintaining 88 percent attack efficiency.

The Implementation of Information Security for the Inventory System in a Municipality of Lima-Perú

In recent years, digital transformation has played an important role in all companies investing in technology. This investment greatly contributes to the daily tasks that companies carry out and can mean notable business growth. Also, it brings vulnerabilities that can be exploited by malicious people who, for any reason, seek to damage or appropriate the company's resources, thus directly or indirectly affecting business operations, which is why it is necessary to prevent these acts of vulnerability with the realization of information security. That is why the materials used to implement information security are explained in this work. The purpose of the research work is to identify, analyze, and evaluate to deal with the risks, thus better controlling the risks. This allowed us to land it in the conclusions made based on the objective and methodology used. It allowed us to have a sequence divided into three stages: initiation, planning, and execution. This helps us identify the infrastructure, times, risks, controls, policies, and information assets, in addition to evaluating and treating each risk identified in the District Municipality of Jesás María. This study showed that the implementation of information security has a positive impact since it helps make decisions for the protection of information assets.

Иронические поучения

The paper deals with ironic edification – autosemantic utterances which contain critical evaluation of human shortcomings expressed in derisive assertion of absurd, or pretentious, or malicious behavior certain people manifest. They make a specific class of proverbs, aphorisms, and miniatures of modern network discourse. They are heterogeneous and vary from profound observations of human character up to banalities used to amuse a down-home partner, from witty phrases up to acid black humour. They are very common in everyday conversations and serve to help interlocutors express their understanding of hidden manipulations they are exposed to. Structurally they may be simple and composite, the former are integral sentences expressing a certain attitude to norms of behavior, the latter are judgments which consist of two parts, in the first part a certain positive norm of behavior is expressed, and in the second part it is denied. Their integral semantic content is a frame which expresses a concessive juxtaposition of values, pragmatically they promote important assumptions about realistic evaluation of human nature, and their most relevant syntactic feature is a ludic allusion to well-known texts or events.

Image Steganography-Based GUI Design to Hide Agricultural Data

Throughout the ages, safely preserving and transmitting data that have extraordinary importance for humanity has increased its importance with rapid advances in computer technology. Steganography stores hidden data within the files, which are unnoticed by third parties, so it provides secure transmission of data to the receiver. In this study, a steganography-based GUI design has been carried out, which ensures that the agricultural data is safely stored and communicated to the other party. We used LSB one-bit, two-bit, three-bit substitution and PVD algorithms with GUI for stages of agricultural data hiding and extracting at cover images. We also provided extra security using the embedded key and shifting operations on the hidden data before hiding data the cover image. In short, we confused the hidden data in the cover image so that malicious people can't understand. In experimental studies, performance analysis was evaluated by comparing various criteria as similarity ratio (Structural Similarity Index Measure, SSIM), stego image quality (Peak Signal-to-Noise Ratio, PSNR) and data hiding capacity (Payload).