Level Of Security Research Articles

The better bandit: decentralised infrastructure, crypto-States, and the rematerialisation of virtual worlds

ABSTRACT This paper examines the role of hardware security as the basis for order in the decentralised metaverse. It does this by considering the infrastructural tools and governance practices at the heart of KONG Land, an example of a blockchain-based decentralised autonomous organisation (DAO) and decentralised physical infrastructure network (DePIN) project. KONG Land manufactures open-source microchips to create verifiable hardware that anyone can use or integrate into their own application. KONG Land’s focus on the materiality of infrastructure led them to pursue a governance model as a digital-physical, politically decentralised polity. By foregrounding the physicality and affordances of decentralised efforts to manufacture microchips, this paper shows how rematerialising digital domains leads back to questions of statehood and its purpose and provides an explanation for emerging sovereignties. Building on Olson’s (1993. Dictatorship, democracy, and development. American Political Science Review, 87(3), 567–576) theory of the stationary bandit, the paper positions projects like KONG Land as an attempt to create a ‘better bandit’ – one that sets out to provide its citizens with a superior level of security than that offered by either nation states or the corporate metaverse, with the intention of creating the conditions for Web3 production and expansion.

A chaos-based word-wise stream cipher using keyed strong S-Box

Stream ciphers are crucial in the realm of information security. However, many existing stream ciphers suffer from several vulnerabilities, including insufficient security levels and the use of S-boxes with low non-linearity, fixed points, reverse fixed points and short cycles. To address these issues, a robust word-wise stream cipher was proposed that incorporates a keyed strong S-box and a two-dimensional (2D) chaotic map, significantly enhancing overall security. A 2D non-degenerate quadratic map (2D-NDQM) was constructed and evaluated using bifurcation and phase diagrams, Lyapunov exponent, Kolmogorov entropy, sample entropy, correlation dimension, and TestU01. The 2D-NDQM is then utilized to design a keyed strong S-box construction algorithm. Based on this, a word-wise stream cipher leveraging both the 2D-NDQM and the keyed strong S-box was developed. A series of tests were conducted to evaluate the proposed stream cipher's performance. The results were promising, showing a key space of 2179, an average number of bits change rate of 50.0229 %, a unified average changing intensity of 33.4402 %, and a number of pixels change rate of 99.6671 %. Additional metrics such as Hamming distance, linear complexity, and Shannon entropy also closely aligned with ideal values, confirming the security and feasibility of the proposed algorithm.

Enhanced lion swarm optimization and elliptic curve cryptography scheme for secure cluster head selection and malware detection in IoT-WSN

Wireless Sensor Networks present a significant issue for data routing because of the potential use of obtaining data from far locations with greater energy efficiency. Networks have become essential to modern concepts of the Internet of Things. The primary foundation for supporting diverse service-centric applications has continued to be the sensor node activity of both sensing phenomena in their local environs and relaying their results to centralized Base Stations. Malware detection and inadequate Cluster Heads node selection are issues with the current technology, resulting in a drastic decrease in the total Internet of Things-based performance of sensor networks. The paper proposes an Enhanced Lion Swarm Optimization (ELSO) and Elliptic Curve Cryptography (ECC) scheme for secure cluster head selection and malware detection in IoT-based Wireless Sensor Networks (WSNs). The paper includes network models, choice of Cluster Head (CH) and attack detection procedures. The proposed method chooses the Cluster Head with the best fitness function values, increasing data transmission speeds and energy efficiencies. Minimum Hop Detection has been implemented to provide the best routing paths against attack nodes. Security level for quick data transmissions via the Internet of Things using Wireless Sensor Networks strengthen sinkhole attacks and black hole nodes, which are successfully removed using this method. The proposed method integrates the use of Lion Swarm Optimization and Elliptic Curve Cryptography (ECC) enhances network security by ensuring secure data transmission and preventing unauthorized access, which is particularly important in IoT-WSN environments. The proposed method achieves less End delay, increased throughput of 93%, lower energy utilization of 4%, increased network lifetime of up to 96%, Packet Delivery Ratio of up to 98% and 97% of malicious node detection efficiently compared to existing methods.

Comparative Assessment of Hash Functions in Securing Encrypted Images

Different encryption methods have been developed to securely transmit confidential images over the Internet and combat the increasing cybercrime. Many of these methods use hash functions to enhance encryption strength. Due to the lack of a comprehensive evaluation of how different hash functions affect image encryption, this study presents a comparative analysis of the performance of various hash functions as encryption keys and analyzes their security, speed, and efficiency. The source image is first processed as a series of bytes. The bytes are divided into byte vectors, each with a length that matches the length of the hash value of a specified hash function. An XOR operation is performed between the hash value bytes and the associated byte vector. The bytes are reordered in each vector according to the ascending order of the associated hash value. Several metrics, such as Normalized Mean Absolute Error (NMAE), Peak Signal to Noise Ratio (PSNR), entropy, key size, and hash time, were used to evaluate the performance of different hash functions in image encryption. The results showed a clear variation in using various hash functions in terms of security, speed, and efficiency. With NMAE>72%, PSNR<6.62 dB, and Entropy>7.999 bpp, the use of the SHA family and MD5 is recommended in applications that need to achieve a high level of distortion in encrypted images. To resist brute-force attacks on the key, Blake2b, SHA512, and Whirlpool are the best choices with a key size of 512 bits. The Tiger is the fastest hash function, requiring the least average time of 0.372 seconds to complete the encryption process, making it the best choice for real-time applications. These findings help to choose the appropriate hash function in developing cryptographic techniques for a particular area.

A bibliometric survey on impact of Blockchain in Robotics: Trends and Applications

Integrating blockchain technology within robotic systems holds great potential for substantial breakthroughs, not only in industrial environments but in several avenues such as agriculture, healthcare, supply chain, and so on, which require increased levels of autonomy and security. This bibliometric survey comprehensively examines the evolution and interplay between blockchain technology and robotics. Addressing the inception of this domain, the study analyses research trends, publication shifts, influential academic articles, authors, countries, and so on. The influence of emerging themes, such as Industry 4.0, Artificial intelligence, and the Internet of Things, are also explored, elucidating their impact on the research trajectory. Utilizing bibliometric techniques, the review offers insights into the current state of blockchain applications in robotic systems and suggests potential future directions warranting in-depth exploration. For a holistic overview covering both literature and technological advancements, we also present patent landscaping on blockchain in robotics, bridging the gap between theoretical results and real-world applications. To the best of our knowledge, this is the first work to present the bibliometric approach of reviewing the literature and patents for blockchain in robotics, precisely via bibliometric techniques such as keyword co-occurrence network, co-citation network, thematic evolution, and Sankey graph.

Mastering information security through standard implementation

This paper aims to enhance information security within an organization, considering the perennial concern for security in organizations utilizing ICT applications. Educational institutions also exhibit deficiencies in the domain of data security. The adoption of international organization for standardization (ISO) 27001-2013 served to pinpoint potential vulnerabilities and non-compliance with safety standards, aiming to minimize associated risks. Through this framework, an assessment of data security within public educational institutions in our country was conducted, focusing on a public university as a case study. Given the sensitive nature of this field, guidance is provided on identifying security-related issues based on ISO 27001 standards and on-ground situations. Surveys were employed, aligning with the required standards, to scan the prevailing situation. Data from surveys at public academic institution were collected and analyzed using the SPSS application. The findings underscore instances where security protocols can prevent or mitigate abuses, consequently enhancing the overall level of data security. Emphasizing education as a pivotal recommendation, this study advocates for educating personnel who handle sensitive data, derived from the application of these standards. This paper accounts for potential risks that could expose organizational weaknesses and thoroughly elucidates the steps and procedures undertaken in this approach, substantiated by illustrated examples.

CryptoGAN: a new frontier in generative adversarial network-driven image encryption

<span lang="EN-IN">There is a growing need for an image encryption scheme, for huge amount of social media data or even the medical data to secure the privacy of the patients or the user. This study introduces a ground-breaking deep learning architecture named crypto generative adversarial networks (CryptoGAN), a novel architecture for generating cipher images. This architecture has the ability to generate both encrypted and decrypted images. The CryptoGAN system consists of an initial encryption network, a generative network that verifies the output against the desired domain, and a subsequent decryption phase. The generative adversarial networks (GAN) are utilised as the learning network to generate cipher images. This is achieved by training the neural network using images encrypted from a conventional image encryption scheme such as advanced encryption standards (AES), and learning from the resulting losses. This enhances security measures when dealing with a large dataset of photos. The assessment of the performance metrics of the encrypted image, including entropy, histogram, correlation plot, and vulnerability to assaults, demonstrates that the suggested generative network may get a higher level of security.</span>

Mitigating blackhole attacks in wireless body area network

<p>In this paper, we aimed to develop a trusted secured routing Ad-hoc on-demand distance vector (AODV) protocol to fight against blackhole attacks within the wireless body area network (WBAN). The trusted secure routing protocol incorporates a routing strategy based on trust value to detect malicious nodes based on their trust value, a routing technique based on node residual energy to select the node with the highest residual energy during the communication process, and a hybrid cryptography algorithm that merges the Affine cipher with the modified RSA cipher algorithm to secure communication against malevolent biomedical sensor attacks. Simulation outcomes demonstrate that the suggested protocol outperforms the traditional AODV routing protocol in all evaluation metrics, including data rate, energy consumption, and packet delivery ratio. Its main strength is that it considers several factors, like illegitimate medical sensor detection, efficient network energy use, and secure data transmission, unlike similar secured routing protocols. Furthermore, the hybrid cipher algorithm improves the effectiveness and increases the security level of sensitive data compared to traditional cipher algorithms such as the Affine cipher and the RSA cipher.</p>

DIGITAL INTERVENTIONS ROLE IN SELF-MANAGEMENT OF DIABETES MELLITUS (DM): A NARRATIVE REVIEW

Diabetes mellitus (DM) is a chronic illness that raises morbidity and death rates worldwide and substantially negatively influences patients quality of life. Health authorities now teach patients and their families good behavioral changes and self-management techniques to enhance clinical therapy and lower complications. Diabetes requires a complicated set of everyday habits to manage, such as regular blood glucose testing, eating a balanced diet, exercising, and keeping a healthy weight. Patients now have the tools they need to effectively manage their conditions thanks to the development of e-health and mobile health (mHealth). These technologies help optimize and monitor glucose levels and have been warmly received. A meta-analysis by Captieux M., et al. (2016) found that application users attitudes toward self-care had improved, and their HbA1c levels had significantly decreased. The efficacy of these technologies varies, though, and obstacles to their broad adoption include low levels of literacy, privacy and security concerns, economic constraints, and the requirement for standardization across various demographics and technical platforms. Notwithstanding these obstacles, digital approaches have demonstrated the potential to enhance diabetic self-management and clinical outcomes. These include telemedicine, mobile health applications, and e-health systems. Applications like BlueStar and OneTouch Reveal, as well as programs like My Diabetes Coach, have been shown to improve glucose management and health-related quality of life. However, more investigation and creation are required to improve the usability and accessibility of these digital health solutions. This narrative review examines the current state of digital health technologies for diabetes self-management and highlights their benefits and drawbacks. It emphasizes the importance of addressing current challenges to fully achieve the potential of digital interventions in controlling type 2 diabetes and type 1 diabetes.

Cybersecurity Behavior in the West Sumatra Universities

User cybersecurity behavior refers to the actions, habits, and decisions made by individuals when using technology and information that affect the level of security of the data and systems they access. Previous research has shown that user cybersecurity behavior is one of the leading causes of computer and information security issues in many organizations, particularly education. To address this issue, researchers must find solutions to improve user cybersecurity behavior within an organization. Therefore, this study aims to find the factors influencing user cybersecurity behavior in higher education institutions in West Sumatra in 2020. This study was conducted using a survey research method. A questionnaire was distributed to 155 respondents. The questionnaire consisted of 28 questions covering seven factors influencing user cybersecurity behavior. The survey data will be analyzed using the Structural Equation Model based on Partial Least Square. The research findings indicate that all variables, such as Misuse Prevention and Compliance, Body of Knowledge, Skill, Behavioral Intervention, Attitude, Security Compliance Behavior, and Technology, have significant relationships. The relationships between these factors will be shown in the framework to be developed. This indicates that the education sector in Indonesia is aware of cyber threats and the importance of security procedures in the workplace. For further research, a deeper exploration of specific security issues is needed to propose potential solutions or actions that can be implemented to improve user cybersecurity behavior in the education sector, particularly in Indonesia.

Secure and Efficient Cloud Storage System with Deduplication and Compression Using Blockchain Technology

Cloud storage is becoming increasingly essential as data volumes continue to grow exponentially. However, traditional cloud storage systems face issues related to data redundancy, inefficient storage utilization, and vulnerabilities in security. This paper presents a novel approach to cloud storage that incorporates deduplication, compression, and blockchain technology. Deduplication removes redundant data, while compression minimizes storage requirements. Blockchain, known for its decentralized and immutable ledger, ensures data integrity and security. The results of this research demonstrate that the system effectively reduces storage consumption and provides a high level of security, outperforming conventional systems in terms of efficiency and protection against data breaches.

Comparative Analysis of Elliptic Curve-Based Cryptographic Approaches for Internet of Things Security

The rapid expansion of the Internet of Things (IoT) introduces significant security challenges, given the resource-constrained nature of most IoT devices. To address these challenges, elliptic curve cryptography (ECC) has emerged as a promising solution due to its ability to deliver high levels of security with shorter key lengths, making it highly efficient for devices with limited computational power and memory. This paper focuses on a comparative analysis of three widely used ECC-based cryptographic algorithms: Elliptic Curve Digital Signature Algorithm (ECDSA), Elliptic Curve Integrated Encryption Scheme (ECIES), and Elliptic Curve Diffie-Hellman (ECDH). Through a detailed evaluation of performance metrics such as key generation speed, execution time, and overall efficiency, the study identifies the strengths and limitations of each algorithm in securing IoT environments. The results reveal that ECDH excels in public key generation speed, making it suitable for applications requiring frequent key exchanges. ECDSA demonstrates the fastest overall execution time, providing an efficient option for digital signatures and authentication. Conversely, ECIES, while slower, offers robust encryption capabilities ideal for scenarios demanding enhanced confidentiality. This comparative study highlights the importance of aligning algorithm selection with specific IoT application requirements, balancing factors like security, performance, resource constraints, and operational complexity. The findings underscore the suitability of ECC-based algorithms in addressing the unique challenges of IoT security.

Implementation of the Caesar Chiper Method in Cryptography for Message Data Security

Data security in the digital era is a very important aspect, especially in maintaining the confidentiality and integrity of information transmitted over the network. One of the classic cryptographic methods that is often used to secure messages is the Caesar Cipher. This method uses a simple substitution technique, where each letter in the message is shifted a certain number of steps in the alphabet. This research discusses the implementation of the Caesar Cipher method as a basic solution for message data security. Although this algorithm is relatively easy to implement and understand, the Caesar Cipher has weaknesses, mainly due to its fixed shifting pattern making it vulnerable to brute force attacks or frequency analysis. Through testing and implementation, this research shows how Caesar Cipher works in the encryption and decryption process, and evaluates its effectiveness in protecting messages from unauthorized access. The results show that this method, although less powerful than modern algorithms, can still be used for certain scenarios that do not require a high level of security. On the other hand, the weaknesses underscore the importance of developing and using more complex cryptographic methods to protect more sensitive information in today's digital era.

An image encryption approach combining cross-interaction region scrambling and plainimage-related diffusion using a dynamic external key

Several multimedia applications encounter difficulties due to concerns about the security of the underlying digital images. The peculiar properties of digital images, such as voluminous data, redundant data, and significant correlation between neighboring pixels, are typically strenuous to be handled by conventional encryption techniques. Further, several well-known image cryptosystems are flawed by different security issues, including fixed encryption parameters, inadequate plainimage sensitivity, independence of keystream generation from the plainimage, equivalent decryption keys, and a limited key space. Hence, this paper suggests an effective chaotic-based image cryptosystem to remedy these defects and accomplish the requirements of secured image exchange. The suggested scheme adopts the confusion-diffusion architecture which incorporates a new scrambling mapping and a novel substitution mapping. During the scrambling stage, the plainimage is first decomposed into four non-overlapping regions, and then the information of each region is mixed with the others by swapping operations through cross-interaction mapping. While in the diffusion stage, the shuffled pixels are masked by a strongly plainimage-related keystream, allowing each bit of the plainimage to influence the entire enciphered image. The suggested architecture employs several chaotic maps, including 1D logistic map, 2D logistic map and 4D hyper-chaos system, which boost the dynamic behavior of the cipher. Moreover, both stages are fully parameterized mappings that are wholly dependent on the plainimage data, including the pixel summation, histogram variance, and entropy features of the input image in addition to the previously substituted pixel. The inclusion of these features in computing all encryption parameters makes the corresponding keystreams for two images that differ by only one bit completely distinct. Specifically, the suggested cryptosystem does not directly employ the parameters or initial seeds of the chaos maps used as a secret key. Instead, an external secret key-based mechanism is suggested to produce these parameters, which employs several non-linear operations, resulting in a "butterfly effect" where a small input change affects subsequent keystream bits. As a result, it can achieve several advantages, such as key sensitivity support, security enhancement, dynamic encryption, resistance to attacks, efficiency, scalability, and flexibility, addressing chaotic system key distribution issues. While the suggested cryptosystem initially employs a static external key for all plainimages, both the generated scrambling sequence and the diffusion keystream are unique (representing a one-time key) to each image. Moreover, our architecture adjusts the external key used for each pixel based on the previously enciphered information. So, even a small change in the external key or input image results in completely different computed parameters. This creates a unique chaotic behavior that controls both the confusion and diffusion operations through different chaotic sequences. Consequently, the suggested cryptosystem can properly withstand different attacks involving the most potent known/chosen plainimage attack. Visually and computationally, the conducted experimental simulations attest that the suggested strategy delivers a superior security level and a noteworthy encryption quality compared to other techniques.

Food Acquisition Locations and Food Groups Acquired According to Levels of Food Insecurity in Brazil

Food insecurity (FI) is a persistent issue in Brazil, with significant disparities existing across the country’s macroregions. This study investigated the food acquisition locations and types of foods purchased at different levels of FI, utilizing data from 57,920 households in the 2017–2018 Brazilian Household Budget Survey. Food acquisition locations were grouped into supermarkets, small markets, street fairs/fruit and vegetable stores/public markets, and others. Foods were categorized into 12 groups: rice, beans, vegetables, fruits, red meats, fish, poultry, eggs, milk and dairy products, bread, cookies, and sugary drinks. Supermarkets are the primary source of food in Brazil. However, in the North and Northeast regions, small markets are more frequently used across all levels of FI. Nationally, most food groups are predominantly purchased at supermarkets. Nevertheless, households experiencing moderate or severe FI rely more on small markets for essential items such as rice, beans, and proteins, as well as ultraprocessed foods. These findings highlight the need for public policies that improve food access for vulnerable populations and address regional inequalities. Enhancing access and ensuring food security across different regions is essential to promoting equitable and healthy diets throughout the country.

The Impact of Cashless Payment Policies on Consumer Behavior at Kesiangan Coffee, Batam City

This research aims to analyze the effect of cashless payment policy on consumer behavior at Kesiangan Coffee, Batam City. With the increasing use of technology in various aspects of life, especially in the payment sector, it is important to understand how cashless policies affect consumer behavior. This study used a survey method with questionnaires distributed to 100 respondents. Data analysis was conducted using SPSS software, and it included validity, reliability, and linear regression analysis. The results showed that the R-value was 0.128 and the R Square was 0.165, indicating that only 16.5% of the variation in the cashless payment policy could be explained by consumer behavior. The validity and reliability test results show that all research instruments are valid and reliable, but the influence of consumer behavior on this policy is still relatively low. This finding suggests that other more dominant factors, such as technological infrastructure, level of security, and consumer demographics, influence the acceptance of cashless payments. Therefore, it is recommended that relevant parties, such as financial institutions and the government, focus on education and infrastructure development to increase the acceptance of this payment system among the public. Further research is needed to explore other factors that play a role in influencing cashless payment policies, so that more effective strategies can be implemented to encourage the use of this technology in various sectors.

Enhancing IoT security through emotion recognition and blockchain-driven intrusion prevention

As the Internet of Things (IoT) expands, ensuring the security and privacy of interconnected devices poses significant challenges. Traditional intrusion detection and prevention systems (IDPS) for IoT rely primarily on network traffic, anomaly detection, and signature-based approaches. This paper addresses deficiencies in conventional infrastructure security, particularly within Closed-Circuit Television (CCTV) operations, to fortify IoT environments against emerging intrusions and ensure heightened levels of privacy and security. Traditional intrusion detection and prevention systems (IDPSs) for IoT primarily rely on network traffic analysis, anomaly detection, and signature-based approaches. However, there is a promising opportunity to enhance IDPS effectiveness by incorporating CCTV cameras and human-inspired techniques. We present a novel approach to IoT security employing CCTV cameras, Raspberry Pi, and emotion recognition intrusion detection and prevention. Initially, two CCTV cameras are installed and connected to a Raspberry Pi for video recording and preprocessing. Emotions are then detected using a convolutional neural network (CNN). Anomalies are classified according to predefined criteria based on detected emotions: individuals meeting conditions such as fear, multiple failed logins (greater than 2), and activity after 6 PM are classified as intruders, those meeting one or two criteria are labeled suspicious, while others are considered normal (non-intruders). In the event of suspicious activity, an alarm is automatically generated, while for intruders, an internet ban is also applied in addition to an alarm. Our proposed system aims to provide a proactive and context-aware defense mechanism against IoT intrusions by integrating machine learning algorithms and blockchain technology, ensuring the robustness and reliability of IoT security.

Association Between Food Insecurity, Body Composition, Anemia and Cognitive Performance Among Students of a Ghanaian University

Association Between Food Insecurity, Body Composition, Anemia and Cognitive Performance Among Students of a Ghanaian University

Unidirectional Communications in Secure IoT Systems—A Survey

The security of Internet of Things (IoT) systems has consistently been a challenge, particularly in the context of critical infrastructure. One particular approach not yet employed in this domain is the unidirectional communication paradigm. This survey presents an analysis of the most prevalent unidirectional communication solutions, namely, data diodes, network pumps, unidirectional gateways, and unidirectional protocols. The objective of the survey is to present an analysis of the unidirectional communication methods that meet the requirements of IoT security. These methods are classified according to their implementation and operational mode. The survey analyzes the unidirectional communication solutions based on their performance, the level of security offered, the cost-effectiveness, and their cost of implementation. Additionally, it includes an analysis of the existing off-the-shelf unidirectional communication implementations found in the industry. Furthermore, it identifies some of the most important current issues and development directions.

Development and Validation of the South African Diet Quality Index for Pregnancy.

Diet quality indexes (DQIs) consist of combinations of foods and/or nutrient components that represent adherence to dietary guidelines. A high-quality diet during pregnancy contributes to optimal birth outcomes. We developed and validated the first DQI for pregnancy for South African women. The South African Food Based Dietary Guidelines and pregnancy dietary guidelines were used as theoretical basis for the a priori development of the South African Diet Quality Index for Pregnancy (SA-DQI-P). To validate the SA-DQI-P, we applied it to data collected for the Nutritional status of Expectant Mothers and their newborn Infants (NuEMI) study (N = 682). We determined the associations between SA-DQI-P scores in tertiles with nutrient intakes, sociodemographic factors, household food security level, and biochemical values. A lower household density ratio, household access to a toilet, refrigerator, and microwave, a higher educational level, being employed and being food secure were significantly associated with a higher score. After correcting for energy intake, higher scores were significantly associated with higher intakes of protein, total fat, saturated fat, cholesterol, calcium, vitamin A, vitamin E, folic acid, vitamin B12, and vitamin C. Significantly more participants who were vitamin A deficient scored in the lowest tertile than those in higher tertiles. The SA-DQI-P is the first DQI developed for a South African population and has proven to be valid in ranking diet quality in pregnant women in our sample. Information regarding diet quality of this vulnerable group can assist with planning nutrition intervention programs to improve nutritional status.