Content Security Research Articles

A New Encryption Algorithm Utilizing DNA Subsequence Operations for Color Images

The computer network has fundamentally transformed modern interactions, enabling the effortless transmission of multimedia data. However, the openness of these networks necessitates heightened attention to the security and confidentiality of multimedia content. Digital images, being a crucial component of multimedia communications, require robust protection measures, as their security has become a global concern. Traditional color image encryption/decryption algorithms, such as DES, IDEA, and AES, are unsuitable for image encryption due to the diverse storage formats of images, highlighting the urgent need for innovative encryption techniques. Chaos-based cryptosystems have emerged as a prominent research focus due to their properties of randomness, high sensitivity to initial conditions, and unpredictability. These algorithms typically operate in two phases: shuffling and replacement. During the shuffling phase, the positions of the pixels are altered using chaotic sequences or matrix transformations, which are simple to implement and enhance encryption. However, since only the pixel positions are modified and not the pixel values, the encrypted image’s histogram remains identical to the original, making it vulnerable to statistical attacks. In the replacement phase, chaotic sequences alter the pixel values. This research introduces a novel encryption technique for color images (RGB type) based on DNA subsequence operations to secure these images, which often contain critical information, from potential cyber-attacks. The suggested method includes two main components: a high-speed permutation process and adaptive diffusion. When implemented in the MATLAB software environment, the approach yielded promising results, such as NPCR values exceeding 98.9% and UACI values at around 32.9%, demonstrating its effectiveness in key cryptographic parameters. Security analyses, including histograms and Chi-square tests, were initially conducted, with passing Chi-square test outcomes for all channels; the correlation coefficient between adjacent pixels was also calculated. Additionally, entropy values were computed, achieving a minimum entropy of 7.0, indicating a high level of randomness. The method was tested on specific images, such as all-black and all-white images, and evaluated for resistance to noise and occlusion attacks. Finally, a comparison of the proposed algorithm’s NPCR and UAC values with those of existing methods demonstrated its superior performance and suitability.

Perbandingan Evaluasi Kerentanan Menggunakan Tenable Nessus Scanner dan Owasp Zed Attack Proxy untuk Meningkatkan Keamanan Sistem Informasi Kepegawaian di Universitas Merdeka Malang

This study aims to compare the vulnerability analysis between Tenable Nessus Scanner and OWASP Zed Attack Proxy (ZAP) for improving the security of the Human Resource Information System (HRIS) website at Universitas Merdeka Malang. The research methodology includes the use of both Nessus and OWASP ZAP tools to scan the HRIS website for potential vulnerabilities. The findings of this research indicate that OWASP ZAP identified several critical web application vulnerabilities such as the absence of Anti-CSRF tokens, lack of Content Security Policy (CSP) headers, and missing Anti-Clickjacking headers, which are essential for maintaining the security and integrity of user data. On the other hand, Nessus Scanner focused more on network and server infrastructure vulnerabilities. The results suggest that OWASP ZAP is more effective for web application security in this context. Recommendations are provided to address the identified vulnerabilities and enhance the overall security of the HRIS website.

Enhancing Data Warehouse Security: An Encrypted Cued-Click-Points Authentication Approach

Text passwords and other traditional security measures have been the mainstay of current data warehouse content security techniques. Due to the growing computational capability of information systems, security requirements, especially for the selection of secure text passwords, have changed throughout time. Because database administrators are either unaware of these changes or are overburdened by the magnitude of the adjustments necessary to remedy them, these vulnerabilities are typically invisible to them. As a result, research on usable authentication schemes have picked up steam, with the goal of developing a secure authentication method using cued click points and encryption techniques for accessing a hybrid data warehouse. This scheme aims to enhance the security of data access by combining the unique characteristics of cued click points with encryption to create a robust authentication system. The project will involve designing and implementing the authentication scheme, testing its effectiveness in a hybrid data warehouse environment, and evaluating its performance in terms of security and usability. Overall, the project aims to provide a secure and user-friendly authentication solution for accessing sensitive data in a hybrid data warehouse setting. This scheme utilizes a combination of encryption techniques and user-specific click points to verify user identity and access to the data warehouse. It also discusses the potential benefits of this authentication scheme in terms of data security and user experience.

Improved protection for colour images via invertible colour‐to‐grey, image distortion, and visible‐imperceptible watermarking

AbstractInvertible colour‐to‐grey algorithms protect the colour of an image against illegal usage and distribution. These schemes hide the colour information into a grayscale version of the image, making colour recovery without proper authorization challenging. A previous study proposed the incorporation of content security by distorting the protected image to hinder illegal structure restoration. This work addresses the limitations of this method, significantly improving both processing time and the quality of the recovered colour image. Specifically, processing times are reduced from 45 h to 9 s, and the mean PSNR value is increased by up to 2.23 dB. Furthermore, this proposal achieves competitive results compared to existing approaches that do not implement content security, obtaining mean peak signal‐to‐noise ratio (PSNR) and structural similarity index measure (SSIM) values above 42.32 dB and 0.992, respectively. Finally, quantitative results are supported by visual comparisons.

EXPERT-ANALYTICAL PRODUCT: APPROACHES TO FORMATION AND IMPLEMENTATION IN THE COMMUNICATION ENVIRONMENT OF POLITICAL SECURITY

The article is devoted to the unification of approaches to the analysis of the public information environment, as well as the coordination of efforts to counter information aggression on a decentralized basis. The purpose of the study is to establish the main features and principles of the formation of an expert-analytical product within the framework of strengthening the security capacity of Ukrainian society. The value of a quick asymmetric information response in the form of discrediting the source, disavowing the information provided and/or using errors or mistakes in the information provided to one’s advantage is characterized. It was emphasized that the targeting of political and security content should also take into account the socio-demographic and behavioral characteristics (data) of the community to which the information is directed. The creativity of the expert-analytical security product is analyzed, which means a creative approach to counter hostile informational provocations and invasions. The importance of the principle of responsiveness, which means the compliance of the appearance of content with time dimensions and the requirements of the political and security situation, is revealed. It was found that the appearance of expert political and security materials should precede the events, be carried out according to the plan of media events, as well as within the framework of crisis situations. It was revealed that the empirical nature of the expert-analytical product involves the use of various models for assessing threats to political security. It is proven that the development of various scenarios of expert public content contributes to the development of the political situation in the future in the desired direction. It has been established that the expert-analytical product of public direction (reports, assessments, analytical summaries, etc.) should not only be broadcast in an accessible (understandable) language. It is assumed that the complexity and completeness of information means its completeness in terms of known and unknown facts. It has been established that the value neutrality of communication messages means avoiding the promotion of ideological messages and motivational components, except when such materials are not included in special promotions and operations. It was found that open discussion leaves the possibility of the information consumer to interactively interact with the text of the message and data. It was concluded that a promising direction of information security activity is asymmetric action in relation to operational massive support of political actions of hostile power institutions on the international arena.

Blockchain-Based Caching Architecture for DApp Data Security and Delivery.

Decentralized applications (DApps) built on blockchain technology offer a promising solution to issues caused by centralization. However, traditional DApps leveraging off-chain storage face performance challenges due to factors such as storage location, network speed, and hardware conditions. For example, decentralized storage solutions such as IPFS suffer from diminished download performance due to I/O constraints influenced by data access patterns. Aiming to enhance the Quality of Service (QoS) in DApps built on blockchain technology, this paper proposes a blockchain node-based distributed caching architecture that guarantees real-time responsiveness for users. The proposed architecture ensures data integrity and user data ownership through blockchain while maintaining cache data consistency through local blockchain data. By implementing local cache clusters on blockchain nodes, our system achieves rapid response times. Additionally, attribute-based encryption is applied to stored content, enabling secure content sharing and access control, which prevents data leakage and unauthorized access in unreliable off-chain storage environments. Comparative analysis shows that our proposed system achieves a reduction in request processing latency of over 89% compared to existing off-chain solutions, maintaining cache data consistency and achieving response times within 65 ms. This demonstrates the model's effectiveness in providing secure and high-performance DApp solutions.

A privacy-preserving image retrieval scheme with access control based on searchable encryption in media cloud

With the popularity of the media cloud computing industry, individuals and organizations outsource image computation and storage to the media cloud server to reduce the storage burden. Media images usually contain a large amount of private information. To prevent disclosure of privacy of the image owners, media images are encrypted before uploading to the server. However, this operation will greatly limit the utilization of the image for the user, such as content-based image retrieval. We propose an efficient similarity query algorithm with access control based on Bkd-tree in this paper, in which a searchable encryption scheme is designed for similarity image retrieval, and the encrypted image is used to extract image features by a pre-trained CNN model. The Bkd-tree is utilized to generate an index tree for the image features to speed up retrieval and make it faster than linear indexing. Finally, the security performances of the proposed scheme is analyzed and the performance of this scheme is evaluated by experiments. The results show that the security of the image content and image features can be ensured, and it has a shorter retrieval time and higher retrieval efficiency.

Analysis Vulnerability Website Baleomolcreative dengan Metode Penetration Testing Execution Standard & Vulnerability Assessment Pada Http Response Header Field

This research will analyze web security and how to find out whether there is a vulnerability or what could be called a vulnerability to enter gaps in the Baleomolcreative web, making the web unsafe. In analyzing whether there are vulnerabilities, the Penetration Testing Execution Standard and Vulnerability Assessment methods are used to determine whether there are gaps or vulnerabilities in the Baleomolcreative website that can be exploited by external parties. This method uses tools such as Owasp ZAP, Nikto, and Nmap which can be used to perform vulnerability scanning on a website. In this research, we succeeded in identifying 3 levels of vulnerability on the Baleomolcreative website, namely medium, low, and informational, with a total of 18 alerts generated from notifications on Owasp Zap. The scanning process includes vulnerability testing such as Content Security Policy, Anti-clickjacking Header, Dangerous JS Functions, Permissions Policy, and others.

On-chip silicon photonic micro-ring processor lights up optical image encryption.

Optical image encryption has long been an important concept in the fields of photonic network processing and communication. Here, we propose a convolution-like operation-based optical image encryption algorithm exploiting a silicon photonic multiplexing architecture to achieve content security. Particularly, the encryption process is completed in a 3 × 3 cross-shaped photonic micro-ring resonator (MRR) array on chip. For the first time, to the best of our knowledge, this algorithm encodes information in an integrated intensity modulation, effectively reducing the encoding difficulty. Moreover, the high reliability and scalability of optical encryption are ensured using both linear and nonlinear operations on photonic chips according to characteristics of MRRs. As the encryption and decryption experiments show, the image restoration accuracy of our optical encryption algorithm exceeds 99% under real system noise at the pixel level, indicating its noise-robust property. Meanwhile, the peak signal-to-noise ratios of the restored and encrypted images are >60 and <15 dB, respectively, revealing both the high accuracy of the restored image and the small correlation between the encrypted and original images. This work adds to the rapidly expanding field of optical image encryption on photonic chips.

Securing Decentralized Storage in Blockchain: A Hybrid Cryptographic Framework

Abstract The evolution of decentralized storage, propelled by blockchain advancements, has revolutionized data management. This paper focuses on content security in the InterPlanetary File System (IPFS), a leading decentralized storage network lacking inherent content encryption. To address this vulnerability, we propose a novel hybrid cryptographic algorithm, merging AES 128-bit encryption with Elliptic Curve Cryptography (ECC) key generation. The algorithm includes ECC key pairs, random IV generation, and content/AES key encryption using ECC public keys. Benchmarking against standard AES 256-bit methods shows a significant 20% acceleration in encryption speed and a 16% increase in decryption efficiency, affirming practicality for enhancing IPFS content security. This research contributes to securing decentralized storage and provides a performance-driven solution. The promising results highlight the viability of the proposed approach, advancing understanding and mitigating security concerns in IPFS and similar systems.

Multi-Image Steganography

Steganography is the practice of concealing information within various types of data, encompassing the embedding of confidential content like messages, images, audio, or video within a cover image. The primary objective involves hiding the secret message or image within the selected image through the utilization of the Least Significant Bit (LSB) technique. To ensure the safeguarding and security of the concealed content, the Advanced Encryption Standard (AES) Algorithm is implemented. The comparison of different image formats, each varying in text length or image size, is conducted. The algorithm's efficacy is evaluated through metrics such as Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE), with a higher PSNR value indicating a superior image quality. Steganography assumes a vital role in numerous applications, including but not limited to medical, military, One Time Password (OTP), and copyright protection. Key Words: Image steganography, LSB, Advanced Encryption Standard, PSNR Ratio, MSE

An Efficient Hybrid Algorithm to Enhance Cloud Data Security with Digital Watermarking Technique

Today, in the era of cloud computing, various types of digital content are being created and uploaded online and used digitally. Providing security, privacy, and originality and ownership rights of this digital content has become a challenging task. It is a good and effective way to completely save the content digitally. Various types of algorithms have traditionally been created to complete the process of watermarking, but these algorithms have some shortcomings and limitations. Keeping these in mind, an algorithm has been created which uses hybrid access based technology and works to increase security, privacy and originality. Under the presented research paper, an algorithm has been proposed with the help of which watermarking technology has been made to perform better and effective

Deep fakes Detection Using Human Eye Blinking Pattern: Deep Vision

Abstract: Deepfake technology is developing rapidly and has the ability to create fake videos that pose a threat to people. Modern depth detection methods often rely on facial disparity, but as technology advances these methods become obsolete. In this study, we propose a new method for deepfake detection based on observation of human eye blink patterns. Human eye blinking is a natural and involuntary action that is difficult to accurately replicate in deepfake video. In our study, we used the unique characteristics of individual blink patterns, which are influenced by many factors such as genetics, muscle tone and unconscious reflexes. We use computer vision and machine learning techniques to extract and identify these patterns from video clips. Our preliminary tests show good results in detecting deepfakes with high accuracy. We are focused on continuing to support the fight against the spread of fraud by focusing on a part of human behaviour that is difficult to replicate. This approach has the potential to improve existing tools for in-depth discovery and increase the overall security and reliability of multimedia content in the digital age. This research opens new avenues for the development of more robust, reliable and flexible deep recognition technologies. This represents a significant step forward in the ongoing fight against malicious misuse of electronic devices.

Browser Security

Web browsers play a crucial role in accessing and interacting with information on the internet. However, they also present significant security challenges due to their complexity and the diverse range of threats they face. This paper provides an overview of web browser security, focusing on the key challenges, vulnerabilities, and defences. It discusses common attack vectors, such as cross-site scripting (XSS) and cross-site request forgery (CSRF), as well as browser security features like sandboxing, secure storage, and Content Security Policy (CSP). Additionally, the paper explores emerging threats and future directions in web browser security, highlighting the importance of ongoing research and collaboration among browser vendors, developers, and security experts to ensure a more secure browsing experience for users.

Development and Employment of Cyber Security of e201 File Web Application for Data Center College of the Philippines of Laoag City, Inc.

Web-based systems in today's interconnected world play a vital role and need of enhanced cybersecurity measures to protect sensitive information since cybercrimes are increasing rapidly. The focus of the study is on the development of an e201 file web application for the Data Center College of the Philippines which will be accessed through a web browser. The objective study is to evaluate the cybersecurity of the developed application, particularly in handling essential personnel records using confidential data OWASP ZAP security testing tool and its software quality based on ISO 25010 specifically in software functionality, usability, and security to determine if it is ready for live deployment. The study utilizes the Research and Development model as its research design to achieve its purpose. The conceptual framework of the study utilized the used of Input-Process-Output model and the Agile Iterative model in the development. The result of the security testing and suggestions of the OWASP ZAP, cyber security was employed in the web application including Content Security Policy Header, HTTOnly Cookie flags, SameSite attribute, X-Content-Type-Options Header, and Anti-CSRF Token. With an overall mean of 4.41 in the result of Users Acceptance Testing, it implies that the system is a great help for the institution. The positive feedback received from evaluators confirmed that the development of the e201 files web application were successful. This study implies that utilizing the OWASP Zap is a great help in strengthening cybersecurity and ISO 25010 in the software quality assurance of web applications of educational institutions.

Remote Sensing Images Secure Distribution Scheme Based on Deep Information Hiding

To ensure the security of highly sensitive remote sensing images (RSIs) during their distribution, it is essential to implement effective content security protection methods. Generally, secure distribution schemes for remote sensing images often employ cryptographic techniques. However, sending encrypted data exposes communication behavior, which poses significant security risks to the distribution of remote sensing images. Therefore, this paper introduces deep information hiding to achieve the secure distribution of remote sensing images, which can serve as an effective alternative in certain specific scenarios. Specifically, the Deep Information Hiding for RSI Distribution (hereinafter referred to as DIH4RSID) based on an encoder–decoder network architecture with Parallel Attention Mechanism (PAM) by adversarial training is proposed. Our model is constructed with four main components: a preprocessing network (PN), an embedding network (EN), a revealing network (RN), and a discriminating network (DN). The PN module is primarily based on Inception to capture more details of RSIs and targets of different scales. The PAM module obtains features in two spatial directions to realize feature enhancement and context information integration. The experimental results indicate that our proposed algorithm achieves relatively higher visual quality and secure level compared to related methods. Additionally, after extracting the concealed content from hidden images, the average classification accuracy is unaffected.

Web Application Penetration Testing on Udayana University's OASE E-learning Platform Using Information System Security Assessment Framework (ISSAF) and Open Source Security Testing Methodology Manual (OSSTMM)

Education is a field that utilizes information technology to support academic and operational activities. One of the technologies widely used in the education sector is web-based applications. Web-based technologies are vulnerable to exploitation by attackers, which highlights the importance of ensuring strong security measures in web-based systems. As an educational organization, Udayana University utilizes a web-based application called OASE. OASE, being a web-based system, requires thorough security verification. Penetration testing is conducted to assess the security of OASE. This testing can be performed using the ISSAF and OSSTMM frameworks. The penetration testing based on the ISSAF framework consists of 9 steps, while the OSSTMM framework consists of 7 steps for assessment. The results of the OASE penetration testing revealed several system vulnerabilities. Throughout the ISSAF phases, only 4 vulnerabilities and 3 information-level vulnerabilities were identified in the final testing results of OASE. Recommendations for addressing these vulnerabilities are provided as follows. Implement a Web Application Firewall (WAF) to reduce the risk of common web attacks in the OASE web application. input and output validation to prevent the injection of malicious scripts addressing the stored XSS vulnerability. Update the server software regularly and directory permission checks to eliminate unnecessary information files and prevent unauthorized access. Configure a content security policy on the web server to ensure mitigation and prevent potential exploitation by attackers.

DeepFake Image Detection

The growth of deepfakes in today’s digital environ- ment raises significant doubts regarding the genuineness and dependability of the content found. To overcome this new challenge, Developing an effective method in the context of detection of deep images. In this study, we conduct a comparative analysis of three varied convolutional neural networks (CNNs) for deepfake image detection. Our experimental results highlight the strengths and weaknesses of each CNN architecture. We deliberate on the consequences of our results in the context of deep image perception and show which models may be better for certain situations. We also address the challenges and limitations associated with deep learning, such as the arms race of deep learning technologies and tools. In conclusion, our work adds to the expanding body of knowledge regarding deep image detection by comparing three major CNN architectures. Our findings provide important guidance for researchers, prac- titioners, and policymakers working to improve the security and authenticity of content in an increasingly digital age. As deepfake technology continues to evolve, the information presented in this study sets the groundwork for development of more powerful and updated deepfake detection mechanisms. Keywords—Deepfake, image detection, convolutional neural networks (CNNs), ResNet, InceptionV3, DenseNet, face forgery detection, GAN, forensics, deep learning, artificial intelligence, convolutional layers, pooling layers, fully connected layers, augmented data, accuracy, precision, recall, F1 measure, Area Under Receiver Operating Characteristic Curve.

Unmasking DeepFakes Using Machine Learning

Our task objectives to deal with the trouble of Deepfake videos, which can be inflicting fear because of their capacity to unfold fake records and manage human beings. Deepfake veideos appearance so actual that it`s tough to inform them other than actual ones, making them a severe danger. This sensible look can result in sizable damage .We are using Machine Learning Algorithms discover Deepfake videos. This entails the usage of era to differentiate among actual and manipulated content. By growing this, we lessen the effect of incorrect information and manipulation, safeguarding human beings from cappotential damage as a result of deceptive content. Keywords: Deepfake Detection, Machine Learning, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Facial Analysis, Anomaly Detection, Synthetic Media, Image and Video Analysis, Temporal and Spatial Patterns, Training Datasets, Real-time Detection, Visual Content Security

Влияние возобновляемых источников энергии на энергетическую безопасность

The article examines the content of energy security, which is an important basis for the state in implementing its energy policy. Advances in technology, climate change and environmental issues are leading to fundamental transformations in global politics and energy. Consumption tradition energy sources (oil and gas, coal) is grad-ually being replaced by renewable energy sources (RES). Today, as the calls are growing in many countries for an accelerated transition for widespread use of new energy sources, data shows that energy demand has been growing in recent years. This means that traditional energy sources are expected to maintain their dominant role over the next two decades. The author notes that the new energy transition is accompanied by the desire of hydrocarbon importers to reduce energy dependence on supplier countries, the desire of leading states to find new sources of economic growth, as well as a revision of the content of energy security in the context of in-creasing strategic competition.