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Purpose: The rise of cryptocurrencies and other digital assets has triggered concerns about regulation and security. Governments and regulatory bodies are challenged to create frameworks that protect consumers, combat money laundering and address risks linked to digital assets. Conventional approaches to confiscation and anti-money laundering are deemed insufficient in this evolving landscape. The absence of a central authority and the use of encryption hinder the identification of asset owners and the tracking of illicit activities. Moreover, the international and cross-border nature of digital assets complicates matters, demanding global coordination. The purpose of this study is to highlight that the effective combat of money laundering, legislative action, innovative investigative techniques and public–private partnerships are crucial. Design/methodology/approach: The focal point of this paper is Australia's approach to law enforcement in the realm of digital assets. It underscores the pivotal role of robust confiscation mechanisms in disrupting criminal networks operating through digital means. The paper firmly asserts that staying ahead of the curve and maintaining an agile stance is paramount. Criminals are quick to embrace emerging technologies, necessitating proactive measures from policymakers and law enforcement agencies. Findings: It is argued that an agile and comprehensive approach is vital in countering money laundering, as criminals adapt to new technologies. Policymakers and law enforcement agencies must remain proactively ahead of these developments to efficiently identify, trace and seize digital assets involved in illicit activities, thereby safeguarding the integrity of the global financial system. Originality/value: This paper provides a distinctive perspective by examining Australia's legal anti-money laundering and counterterrorism financing framework, along with its law enforcement strategies within the realm of the digital asset landscape. While there is a plethora of literature on both asset confiscation and digital assets, there is a noticeable absence of exploration into their interplay, especially within the Australian context. [ABSTRACT FROM AUTHOR]

Summary: This article proposes a security strategy based on chaos encryption for the transmission of robot data on cloud platforms. Based on chaos encryption technology, the data information collected by the robot is encrypted before transmission. After receiving the request, the cloud platform server uses chaos decryption technology to analyze the ciphertext information and obtain the original relevant data information. The security strategy proposed in this article is simple and feasible, and can resist all kinds of security attacks. [ABSTRACT FROM AUTHOR]

Smart medical devices and the internet of things (IoT) have enhanced healthcare systems by allowing remote monitoring of patient's health. Because of the unexpected increase in the number of diabetes patients, it is critical to regularly evaluate patients' health conditions before any significant illness occurs. As a result of transmitting a large volume of sensitive medical data, dealing with IoT data security issues remains a difficult challenge. This paper presents a secure remote diabetes monitoring (SR-DM) model that uses hybrid encryption, combining the advanced encryption standard and elliptic curve cryptography (AES-ECC), to ensure the patients' sensitive data is protected in IoT platforms based on the cloud. The health statuses of patients are determined in this model by predicting critical situations using machine learning (ML) algorithms for analyzing medical data sensed by smart health IoT devices. The results reveal that the AES-ECC approach has a significant influence on cloud-based IoT systems and the random forest (RF) classification method outperforms with a high accuracy of 91.4%. As a consequence of the outcomes obtained, the proposed model effectively establishes a secure and efficient system for remote health monitoring. [ABSTRACT FROM AUTHOR]

Nowadays, users often opt to encrypt their sensitive data before outsourcing it to the cloud. While this encryption ensures data privacy, it compromises the search functionality. Public key encryption with keyword search (PEKS) has been posited as a potential solution to this challenge. However, many PEKS schemes are either inefficient or vulnerable to various types of attacks, such as inside keyword guessing attacks, outside keyword guessing attacks, etc. In response, we introduce a sustainable certificateless authenticated encryption system with a keyword search scheme. To the best of our knowledge, this proposed scheme is the first to consider multi-trapdoor indistinguishability within the certificateless primitive. Furthermore, our in-depth security analysis indicates that our scheme effectively protects against both online and offline keyword guessing attacksAdditionally, it ensures semantic security by offering both ciphertext indistinguishability and multi-trapdoor indistinguishability. Performance analysis results also suggest that our scheme is efficient and superior to existing alternatives. [ABSTRACT FROM AUTHOR]

Improving the photoswitching rate and robustness of photochromic molecules in bulk solids is paramount for practical applications but remains an on‐going challenge. Here, we introduce an octupolar design paradigm to develop a new family of visible light organic photoswitches, namely multi‐branched octupolar Stenhouse Adducts (MOPSAs) featuring a C3‐symmetrical A3‐(D‐core) architecture with a dipolar donor–acceptor (D–A) photochrome in each branch. Our design couples multi‐dimensional geometric and electronic effects of MOPSAs to enable robust ultrafast reversible photoswitching in bulk polymers. Specifically, the optimal MOPSA (4 wt %) in commercial polyurethane films accomplishes nearly 100 % discoloration in 6 s under visible light with ∼ 100 % thermal‐recovery in 17.4 s at 60 °C, while the acquired kinetics constants are 3∼7 times that of dipolar DASA counterpart and 1∼2 orders of magnitude higher than those of reported DASAs in polymers. Importantly, the MOPSA‐doped polymer films sustain 500 discoloration/recovery cycles with slow degradation, superior to the existing DASAs in polymers (≤30 cycles). We discover that multi‐dipolar coupling in MOPSA enables enhanced polarization and electron delocalization, promoting the rate‐determining thermal cyclization, while the branched and non‐planar geometry of MOPSA induces large free volume to facilitate the isomerization. This design can be extended to develop spiropyran or azobenzene‐based ultrafast photochromic films. The superior photoswitching performance of MOPSAs together with their high‐yield and scalable synthesis and facile film processing inspires us to explore their versatile uses as smart inks or labels for time‐temperature indicators, optical logic encryption and multi‐levelled data encryption. [ABSTRACT FROM AUTHOR]

With the rapid development of the information age, smart meters play an important role in the smart grid. However, there are more and more attacks on smart meters, which mainly focus on the identity authentication of smart meters and the security protection of electricity consumption data. In this paper, an efficient lightweight smart meter authentication scheme is proposed based on the Chinese Remainder Theorem (CRT), which can realize the revocation of a single smart meter user by publishing a secret random value bound to the smart meter identity. The proposed scheme not only protects the security of smart meter electricity consumption data by using encryption, but also resists identity attacks from both internal and external adversaries by using hash functions and timestamps. Experiment shows that the proposed scheme has lower computation overhead and communication overhead than other authentication schemes and is more suitable for smart meter authentication. [ABSTRACT FROM AUTHOR]

Data outsourcing has become more and more popular due to its low cost and flexibility. However, there is a problem that the cloud server used to store data is partially trusted. Searchable encryption is an efficient technology that is devoted to helping people conduct accurate searches without leaking information. Nonetheless, most existing schemes cannot support dynamic updates or meet the privacy requirements of all users. There have been some experiments to solve these issues by implementing a dynamically searchable asymmetric encryption scheme. This paper proposes an efficient searchable encryption scheme based on the Authenticator Bloom Filter (ABF). The solution can support dynamic updates and multiple users and meet forward and backward security. This paper uses an ABF to improve the efficiency of searches and updates while playing a significant role in dynamic updates. This paper designs a new token encryption scheme and file set encryption scheme, which not only helps users reduce time in searches and updates but also supports multi-user modes. Experiments show that the proposed scheme takes less time in searching and updating algorithms, especially when the keyword does not exist. The solution also takes into account the problem of history storage when updating, which reduces the unnecessary consumption of memory and avoids multiple storage states for the same file. [ABSTRACT FROM AUTHOR]

In recent years, the popularity of blockchain application in healthcare sector has increased manifold due to features such as decentralized architecture, security, immutability and authentication. However, there are some challenges associated with blockchain-based healthcare frameworks. Firstly, blockchain provides data verifiability meaning that anything stored there is accessible to all nodes in the network for verification. However, it is unacceptable for sensitive medical data to be made accessible to everyone. Secondly, healthcare sectors are group-oriented and frequently involve open networks for communication which lead to data breaches and other security risks. Lastly, due to limited size of a block in blockchain, many hospitals prefer storing patient's data locally in a centralized server or opt for cloud storage which have their own threat vectors. In this work, we propose a three-phase unified approach to solve the above problems. Our framework utilizes proxy re-encryption and advanced cryptographic techniques to provide stringent access control. Next, a blockchain-based group encryption is proposed to ensure secure group communication. A group session key will be agreed upon by the authorized group members and used to protect sensitive patient information. Lastly, IPFS-based blockchain data storage is proposed to maintain data securely offsite. We provide a comparative security analysis of the proposed framework with other existing peer models and show that our framework offers several new security features. We also examine the security of the proposed framework using BAN logic. Furthermore, the proposed framework is simulated using the OMNET++ software, and its storage and computation costs are examined to establish its effectiveness. [ABSTRACT FROM AUTHOR]

MOTIVATION: With the enhancement of people's awareness of the protection of personal privacy information, how to provide better services on the premise of protecting users' privacy has become an urgent problem to be solved. Therefore, it is a necessary motivation to build a network intelligent platform for privacy protection and integrated big data mining. OBJECTIVE: In view of the existing network platform of data privacy leakage, low efficiency of data mining and user satisfaction is not high, this paper will adopt advanced privacy technology, to ensure the confidentiality of users' personal information and security, to enhance the user trust and use experience, to better meet the needs of users. METHODS: In order to better protect the privacy of users, the network intelligent platform should adopt more advanced privacy protection technology. This paper uses the differential privacy algorithm to reduce the risk of data leakage and abuse, and ensure the accuracy and efficiency of data analysis and mining. In the design of the platform, the performance of the platform is fully taken into account to realize the secure storage and efficient processing of data, with good scalability and flexibility to meet the growing user needs and business needs. The performance of the network intelligent platform is also analyzed by experimental simulation. RESULT: The experimental results of this article indicated that in a network intelligent platform based on privacy protection and integrated big data mining, its data transmission encryption score was 9.5; the data storage encryption score was 9.8; the score of access control mechanism was 9.3; the privacy protection score was 9.6; the response time was 80 ms; the processing speed was 121GB/h; the user satisfaction rating was 6.6. CONCLUSION: This indicated that the network intelligent platform had good platform performance and user friendliness while ensuring data security and privacy protection. It could efficiently conduct data mining and ensure data security and privacy. [ABSTRACT FROM AUTHOR]

To secure sensitive medical records in the healthcare clouds, this paper proposes an End-to-End Encryption (E2EE) to enhance a patient-centric blockchain-based system for electronic health record (EHR) management. The suggested system with a focus on the patient enables individuals to oversee their medical records within various involved parties by authorizing or withdrawing permission for access to their records. Utilizing the inter-planetary file system (IPFS) for record storage is chosen due to its decentralized nature and its ability to guarantee the unchangeability of records. Then an E2EE enhancement maintains the medical data integrity using dual level-Hybrid encryption: symmetric Advanced Encryption Standard (AES) and asymmetric Elliptic Curve Cryptography (ECC) cryptographic techniques. The proposed system is implemented using the Ethereum blockchain system for EHR data sharing and integration utilizing a web-based interface for the patient and all users to initiate the EHR sharing transactions over the IPFS cloud. The proposed system performance is evaluated in a working system prototype. For different file sizes between 512 KB to 100 MB, the performance metrics used to evaluate the proposed system were the time consumed for generating key, encryption, and decryption. The results demonstrate the proposed system's superiority over other cutting-edge systems and its practical ability to share secure health data in cloud environments. [ABSTRACT FROM AUTHOR]

With the number of attacks and cyberincidents affecting Internet of Things (IoT) devices on the rise, the need for carrying out forensic investigations to determine what has happened has grown at the same pace. However, due to the characteristics and requirements of this environment, the solutions used until now in the field are not suitable to be followed, as they are not able to guarantee the effective retrieval and study of the pieces of evidence. Under these circumstances, new ways of interacting with IoT units are needed, and the edge computing paradigm has emerged as an interesting asset to complement IoT networks. Attack, anomaly and intrusion detection, or data encryption are some of the fields in which this approach has been successfully applied. Following this concept, this article presents an IoT forensic methodology that integrates the edge computing technology in order to assist in the investigation process, trying to address some of the issues that are hindering the effectiveness of examinations in this scenario. In addition, this proposal is compared with the existing ones in the research community, and evaluated by testing it in two case studies representing real-life scenarios, ultimately demonstrating suitability to be used for IoT forensic examinations. [ABSTRACT FROM AUTHOR]

Cloud Service Providers, exemplified by industry leaders like Google Cloud Platform, Microsoft Azure, and Amazon Web Services, deliver a dynamic array of cloud services in an ever-evolving landscape. This sector is witnessing substantial growth, with enterprises such as Netflix and PayPal heavily relying on cloud infrastructure for various needs such as data storage, computational resources, and various other services. The adoption of cloud solutions by businesses not only facilitates cost reduction but also fosters flexibility and supports scalability. Despite the undeniable advantages, concerns surrounding security and privacy persist in the realm of Cloud Computing. Given that Cloud services are accessible via the internet, there is a potential vulnerability to unauthorized access by hackers or malicious entities from anywhere in the world. A crucial aspect of addressing this challenge is the implementation of robust security measures, particularly focusing on data protection. To safeguard data in the Cloud, a fundamental recommendation is the encryption of data prior to uploading. Encryption should be maintained consistently, both during storage and in transit. While encryption enhances security, it introduces a potential challenge for data owners who may need to perform various operations on their encrypted data, such as accessing, modifying, updating, deleting, reading, searching, or sharing them with others. One viable solution to balance the need for data security and operational functionality is the adoption of Searchable Encryption (SE). SE operates on encrypted data, allowing authorized users to perform certain operations without compromising the security of sensitive information. The effectiveness of SE has notably advanced since its inception, and ongoing research endeavors aim to further enhance its capabilities. This paper provides a comprehensive review of the functionality of Searchable Encryption, with a primary focus on its applications in Cloud services during the period spanning 2019 to 2023. Additionally, the study evaluates one of its prominent schemes, namely Fully Homomorphic Encryption (FHE). The analysis indicates an overall positive trajectory in SE research, showcasing increased efficiency as multiple functionalities are aggregated and rigorously tested. [ABSTRACT FROM AUTHOR]

Symmetric cryptography provides the best examples of cryptosystems to be applied in lightweight environments (e.g., IoT). A representative example is the cryptosystem TinyJambu, one of the ten finalists in the NIST Lightweight Cryptography Standardization Project. It is an authentication encryption with associated data scheme that is extremely lightweight and fast. In this work, we analyze the security of TinyJambu from two distinct and non-symmetric points of view: (1) the improvement of the best cryptanalytical attack found in the literature and (2) a randomness analysis of the generated sequences. Concerning item (1), we launched a differential forgery attack with probability 2−65.9487, which was improved considerably compared with previous numerical results. Concerning item (2), we analyzed the degree of randomness of the TinyJambu keystream sequences with a complete and powerful battery of statistical tests. This non-symmetric study shows the weakness of TinyJambu against cryptanalytic attacks as well as the strength of TinyJambu against statistical analysis. [ABSTRACT FROM AUTHOR]

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function, a brand-new tristable locally active memristor model is first proposed in this paper. Here, a novel four-dimensional fractional-order memristive cellular neural network (FO-MCNN) model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its performance. Then, its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation platforms. Subsequently, it is used toward secure communication application scenarios. Taking it as the pseudo-random number generator (PRNG), a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing (ASR-CS) model. Eventually, the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance. [ABSTRACT FROM AUTHOR]

The sensing-as-a-service concept has been developed to address the challenges that future smart cities would have in managing an enormous number of sensors. Smart cities must find a solution to the enormous difficulty of effectively sharing user-confidential information without sacrificing quality, privacy, or interruption. The development of blockchain technology has the potential to overcome these problems, but the limitations of the current models include large storage, customizable blockchain, high communication overhead, and high processing costs. The proposed average hybrid leader optimization (AHLO)-PrivPresKey Gen model determined a blockchain-based secure information sharing scheme using a smart contract in a smart city. Blockchain-based smart contracts implement a highly complex midway illustration method to reduce the user's clarification burden. The proposed scheme makes utilize of different safety operators, like 3 Data Encryption Standard, segmenting interpolation, passwords, one time password token and etc. Furthermore, the data privacy phase is improved by utilizing various functionalities, such as dyadic product, Chebyshev polynomial, and keys, where the keys are optimally generated using AHLO. The designed AHLO is obtained by the consolidation of average and subtraction based optimizer and hybrid leader-based optimization. The designed model has delivered minimum memory of 30.5 MB, minimum computational time of 28.467 MB, maximum encryption quality of 0.808, maximum detection rate of 0.898, minimum responsiveness of 41.679 and minimum bandwidth of 95 that surpasses the conventional schemes. [ABSTRACT FROM AUTHOR]

To hide confidential messages from people who are not responsible or who can access the messages, a way is needed to hide the messages. One way to hide messages in transmission is to change the data into something unintelligible by encoding and embedding it using cryptography and steganography techniques. This application was built using the hill cipher algorithm and the Rivest Cipher 4 (RC4) method. This algorithm is a symmetric key algorithm which has several advantages in data encryption. The hill chiper algorithm uses a mxm matrix as the encryption and decryption key. Meanwhile, the RC4 symmetric key is in the form of a stream cipher which can process input data as well as messages or information. Input data is generally in the form of bytes or even bits. The results of this research show that hill cipher and RC4 have their respective advantages and disadvantages. However, currently, RC4 is generally considered less safe for use in securitycritical scenarios due to its vulnerability to attack. It is highly recommended to use an encryption algorithm such as advanced encryption standard (AES) which is modern and strong and has been tested and proven to be more resilient. [ABSTRACT FROM AUTHOR]

The efficiency of tools used to collect private medical data on people has significantly improved over time. These include implanted, surfacemounted, or encircling devices that form a wireless body area network (WBAN). Although the most recent secure authentication techniques in the industry offer privacy and security, these schemes have a higher time cost for authentication and take longer to complete owing to the restricted computational power of WBAN devices. We provide a novel authentication method depending on the lightweight wearable device scheme for the WBAN environment. Wearable devices are used to capture sensor data from the patient's body in the beginning, after which any redundant data is removed by normalization. The method we suggest for encrypting the data is multi-fractional triphase duplex data encryption (MTDDE) with ant colony optimization (ACO). The method considers not only the security of the data but also the many limitations of sensor nodes, such as battery life, throughput, computing power limitations, and dynamic topology. The thorough research demonstrates that our suggested technique saves computing costs while maintaining security and privacy together with anonymous verification. The suggested system's effectiveness in protecting the privacy and confidentiality of patient health data in WBAN is demonstrated by the simulation model. [ABSTRACT FROM AUTHOR]

Privacy is given top priority as far as communication involving transfer of confidential document or data is concerned. There is therefore a need to keep confidential data secretive from being invaded by unauthorised access, and this is done through cryptography algorithms, where the Advanced Encryption Standard algorithm has been the widely accepted symmetric block encryption algorithm for such purposes. This paper therefore focuses on developing a new AES-512 bits symmetric encryption algorithm through modification of the conventional AES-128 algorithm to be used purposefully in the classroom for document transfer. The development comes with increasing the plaintext bits of the conventional AES-128 algorithm to 512 bits plaintext which undergoes five operational transformations: STATE, SKGF, SRL, SCL and AARC through key size in the Galois field, GF(29 ). A numerical example is then given to explain the use of the algorithm, and finally, we provide a comparative study of this algorithm and other existing symmetric encryption models, such as the AES-128 and DES algorithms. [ABSTRACT FROM AUTHOR]

This paper introduces a methodology for generating secure cryptographic key bits from analog values obtained from the Lorenz chaotic circuit. The analog values are transferred from the chaotic circuit to the computer via an Analog Discovery-2 device and then post-processed by using a fixed-point number representation format and Von-Neumann corrector for the sampled values on the MATLAB program. By employing this method, the analog values are digitized and randomized as the main idea is to obtain secure and efficient statistically random bits. Furthermore, the generated random bits are utilized for secure audio encryption by demonstrating a practical application of the proposed methodology. In addition to the classical randomness test criteria, NIST 800.22 statistical test suite, the throughput bit stream is also subjected to Chi-square and FIPS 140-1 tests to further evaluate its effectiveness. The results of these comprehensive tests confirm the successful performance of the proposed system in generating statistically random bits and its secure audio encryption system. The utilization of the Lorenz chaotic circuit as an entropy source in generating true random bits for secure audio transmission applications showcases the potential of the proposed system. [ABSTRACT FROM AUTHOR]

High security solutions are highly important in wireless medical environments, since patient data is confidential, sensitive and must be transmitted over a secure connection. Accordingly, a hybrid encryption method is proposed to ensure data confidentiality (RSA-2048 for key exchange using ACL in SDN with the addition of AES-256-CTR and a hashed secret key for data encryption), and the encrypted data is stored in a private blockchain with the DBFT consensus algorithm to ensure the integrity of data before it being accessed by a doctor’s application which decrypts and displays the relevant information. The system was programmed using Python, in an NS3.37 simulator installed on Ubuntu with a MySQL database created using the Apache XAMPP. The product turned out to be a highly secure system for transmitting data from a medical sensor to the doctor’s application, offering a throughput of approximately 9 Gbps for both encryption and decryption tasks, while the processing time equaled 0.014 µs per a 128-bit block size for both encryption and decryption, with latency amounting to 0.14 s per 1 KB of data, and the blockchain agreement time equaling 4 ms per 1 KB. [ABSTRACT FROM AUTHOR]

In the contemporary era, technology plays a significant role in our daily lives. Consequently, there is a growing emphasis on securing information transmitted across networks. To meet this need, numerous cryptographic systems have been developed to enhance security. The distinguishing factor among these systems lies in their capability to uphold fundamental criteria for information security, including authentication confidentiality and integrity. This paper introduces a method involving the use of DNA and lightweight cryptography[1-2-3]. This method utilizes for the encryption and decryption of data using DNA sequence and the SIMON cryptographic system—a symmetric encryption algorithm specifically designed for simplicity and efficiency. [ABSTRACT FROM AUTHOR]

Internet cloud services come at a price, especially when they provide top-tier security measures. The cost incurred by cloud utilization is directly proportional to the storage requirements. Companies are always looking to increase profits and reduce costs while preserving the security of their data by encrypting them. One of the offered solutions is to find an efficient encryption method that can store data in a much smaller space than traditional encryption techniques. This article introduces a novel encryption approach centered on consolidating information into a single ciphertext by implementing Multi-Key Embedded Encryption (MKEE). The effectiveness of MKEE scales in tandem with the volume of information encapsulated within the ciphertext. MKEE substantially reduced the size of the ciphertext, achieving an 88% decrease when incorporating ten plaintext values. To further reduce the size of the ciphertext in our proposal, a Modular Multiplicative Inverse method (MMI) is introduced. MMI experiments were conducted, demonstrating that we achieved a commendable 50% reduction in the ciphertext size. To validate the practicality of the proposed method, a case study was conducted on a diabetes dataset. By integrating MKEE and MMI, this study showed a data storage reduction of 94%. [ABSTRACT FROM AUTHOR]

The recent development of mobile networks has led to the emergence of new threats and methods of implementing existing ones. Phishing attacks, including robocalls, are causing record losses to both individual users and large corporations. At the same time, existing countermeasures cannot provide protection against such attacks because most existing solutions focus on device authentication, whereas user authentication does not occur during a call. Another problem with mobile networks is that there is no point-to-point encryption, i.e., the speech is encrypted only on the segment from the subscriber to the base station. The subject of study in this article is the process of ensuring user security during a call. The purpose of this study is to develop a model of mutual user authentication and end-to-end data encryption in a mobile network during a call. The main objectives are the protection of users from spoofing and vishing and the proposal of a protection method by implementing mutual authentication of users during a call without storing confidential information on the side of a "trusted third party". Method of secure key exchange and end-to-end encryption during a call in the mobile network was proposed. It prevents the interception of calls by the operator for circuit-switched and packet networks. The methods used are mathematical modelling, ontological approach, and multi-criteria optimization models. Because of this research, an algorithm for mutual authentication of users is proposed by introducing biometric authentication methods and modifying the sequence of messages during a call. The proposed approach can be implemented for CS-call and VoLTE/VoWiFi calls. A call cannot be received without user biometric authentication; such as ear pattern or bone conduction methods. Modified SETUP and CONNECT ACK messages are used to inform the other party about the user verification result. This prevents user spoofing, call masquerading, and robocalls. A combination of the proposed asymmetric encryption, a short authentication string, and hashes of previous calls provides a higher level of confidentiality, integrity, and additional resistance to man-in-the-middle attacks. Conclusions. The scientific novelty of the obtained results is the integration of the above methods into the sequence of call flow messages for providing mutual authentication, end-to-end encryption, and counteraction to the number of network attacks. The proposed methods allow one level to increase the provision of services of privacy and observation groups and can be implemented in the software part of user equipment. [ABSTRACT FROM AUTHOR]

This research exploration presents a comprehensive methodology for conducting penetration testing for networking security protocols and vulnerabilities on the Wi-Fi networks using Kali Linux, an open-source penetration testing platform. The methodology also encompasses four main stages which are Preparation, Information Gathering, Simulated Attack, Reporting. In the Preparation Stage, the scope of the penetration test is defined, authorization is obtained, and within the testing environment the experimentation is prepared. The Information Gathering Stage involves scanning for associated nearby wireless access points (APs), identifying encryption modes, and assessing network coverage. The Simulated Attack Phase verifies the types of vulnerabilities through password cracking, infrastructure penetration tests, and client-side attacks. Finally, the Reporting Phase entails compiling of a very detailed test report with results visualized, findings and recommendations with directions. Experimental results validate the overall effectiveness of the methodology in identifying and mitigating Wi-Fi network vulnerabilities. Through systematic testing and analysis, Kali Linux facilitates proactive security measures to enhance Wi-Fi network defenses. [ABSTRACT FROM AUTHOR]

Database systems play a significant role in structuring, organizing, and managing data of organizations. In this regard, the key challenge is how to protect the confidentiality, integrity, and availability of database systems against attacks launched from within and outside an organization. To resolve this challenge, different database security techniques and mechanisms, which generally involve access control, database monitoring, data encryption, database backups, and strong passwords have been proposed. These techniques and mechanisms have been developed for certain purposes but fall short of many industrial expectations. This study used the design science research method to recommend a new Digital Forensic Readiness Framework, named DFRF, to secure database systems. DFRF involves risk assessments, data classification, database firewalls, data encryption, strong password policies, database monitoring and logging, data backups and recovery, incident response plans, forensic readiness, as well as education and awareness. The proposed framework not only identifies threats and responds to them more effectively than existing models, but also helps organizations stay fully compliant with regulatory requirements and improve their security. The design of the suggested framework was compared with existing models, confirming its superiority. [ABSTRACT FROM AUTHOR]

The article "Evaluation of Current Knowledge Level on Data Security of People Working in a Medical Environment" examines the understanding of data security among individuals in the medical field. Through an online questionnaire, it was found that only about 25% of participants had a good grasp of data security. Many participants struggled to answer important questions correctly. The article concludes that there is a need to enhance the knowledge and awareness of data security among those working in the medical environment. [Extracted from the article]

There is a great need of internet applications that involves data to be sent in an extra safe way. Steganography and cryptography help in providing data safety. Steganography hides the existence of message by inserting data in some other digital media and Cryptography transforms data in to cipher object that can be in unreadable form to normal user. To resume the defense of data defeating and communication over internet, this paper suggests a hybrid heuristic, integrating a genetic algorithm and steganography technique to efficiently solve this problem. Computational results show that the suggested technique can significant improvement the performance of a genetic algorithm for this problem, this was proven by the results of the comparison between the suggested technique and several other proposed systems. Genetic Algorithm is used for pixel variety of image where secret data is to be hidden so that detection of secret data become multifarious. [ABSTRACT FROM AUTHOR]

With current advancement in hybermedia knowledges, the privacy of digital information has developed a critical problem. To overawed the susceptibilities of present security protocols, scholars tend to focus mainly on efforts on alternation of current protocols. Over past decade, various proposed encoding models have been shown insecurity, leading to main threats against significant data. Utilizing the suitable encryption model is very vital means of guard against various such, but algorithm is selected based on the dependency of data which need to be secured. Moreover, testing potentiality of the security assessment one by one to identify the best choice can take a vital time for processing. For faster and precisive identification of assessment algorithm, we suggest a security phase exposure model for cipher encryption technique by invoking Support Vector Machine (SVM). In this work, we form a dataset using usual security components like contrast, homogeneity. To overcome the uncertainty in analysing the security and lack of ability of processing data to a risk assessment mechanism. To overcome with such complications, this paper proposes an assessment model for security issues using fuzzy evidential reasoning (ER) approaches. Significantly, the model can be utilised to process and assemble risk assessment data on various aspects in systematic ways. To estimate the performance of our framework, we have various analyses like, recall, F1 score and accuracy. [ABSTRACT FROM AUTHOR]

This article provides a general overview of the communication protocols used in the IEC61850 standard for the automation of electrical substations. Specifically, it examines the GOOSE and R-GOOSE protocols, which are used for exchanging various types of information. The article then presents real cases of cyber attacks on the industrial sector, highlighting the importance of addressing cybersecurity in the IEC61850 standard. The text presents security drawbacks of the communication protocols mentioned earlier and briefly explains two algorithms defined in the IEC61850 standard to address them. However, the authors suggest that having only a couple of algorithms may not be sufficient to ensure digital security in substations. This article presents a study on the cryptographic algorithms ChaCha20 and Poly1305. The purpose of the study is to experimentally verify their adaptation to the strict time requirements that GOOSE must meet for their operation. These algorithms can operate independently or in combination, creating an Authenticated Encryption with Associated Data (AEAD) algorithm. Both algorithms were thoroughly reviewed and tested using GOOSE and R-GOOSE frames generated by the S-GoSV software. The computational time required was also observed. The frames were analysed using the Wireshark software. It was concluded that the algorithms are suitable for the communication requirements of electrical substations and can be used as an alternative to the cryptographic algorithms proposed under the IEC61850 standard. [ABSTRACT FROM AUTHOR]

Joint image compression and encryption algorithms are intensively investigated due to their powerful capability of simultaneous image data compression and sensitive information protection. Unfortunately, most of the existing algorithms suffered from either poor compression efficiency or weak encryption strength, making them vulnerable to cryptanalysis. To address these limitations, we propose a chaos-based JPEG-compatible joint image compression and encryption algorithm. We separate the luminance and chrominance coefficients to preserve file size and encrypt the discrete cosine transform (DCT) coefficients in parallel. The proposed inter-block DC encryption strategy achieves high encryption intensity based on the permutation-substitution structure. In addition, we apply both inter- and intra-block permutations to AC coefficients and strengthen the encryption using an inter-block substitution for non-zero AC coefficients. The results of security and performance analyses demonstrate that the proposed algorithm offers robust encryption of image data while maintaining compression efficiency for real-time transmission. [ABSTRACT FROM AUTHOR]

In the era of rapid technological advancement, the proper adaptation of legal frameworks and secure technologies is crucial to ensure legal certainty in land ownership. The National Land Agency (Badan Pertanahan Nasional or ATR/BPN) plays a central role in managing the issuance of electronic land certificates. This research aims to investigate the role of electronic land certificates in providing legal protection in Indonesia and analyze the challenges and vulnerabilities that arise with the development of information technology. Employing a normative legal method, this study focuses on the analysis of norms and legal regulations governing the use of electronic land certificates in the land registration system. The research approach includes a legislative approach, a conceptual approach, and the use of primary and secondary legal materials. The results emphasize the importance of careful adaptation to information technology developments to maintain legal certainty in land ownership, highlighting the central role of the ATR/BPN and the necessity of appropriate regulations, data security, legal validity, technical requirements, and technology utilization, including data encryption and network security measures, to address vulnerabilities. Adequate awareness and training are also deemed essential for all stakeholders involved. [ABSTRACT FROM AUTHOR]

This paper proposes a solution to the problem of software absence for the quantitative fire safety analysis of complex objects, which is suitable not only for highly qualified scientists and experts but also for fire safety engineers and inspectors and is compatible with mobile devices. Existing software solutions for quantitative fire safety analysis are desktop-based, and all require a high level of competence of users. We propose a solution by combining the formalism of typical probabilistic structural–logical (TPSL) models, the Software-as-a-Service (SaaS) concept, and end-to-end encryption. Using TPSL models allows the development of cloud-based applications with a simple request-based application programming interface and intuitively understandable user interface to assess the level of safety of complex objects. As a result, we could use such mobile device-ready applications both for developing mobile device applications and developing mobile-device-friendly website-based services to carry out safety control inspections or level of safety management. [ABSTRACT FROM AUTHOR]

In virtual power plants, diverse business scenarios involving user data, such as queries, transactions, and sharing, pose significant privacy risks. Traditional attribute-based encryption (ABE) methods, while supporting fine-grained access, fall short of fully protecting user privacy as they require attribute input, leading to potential data leaks. Addressing these limitations, our research introduces a novel privacy protection scheme using zero-knowledge proof and distributed attribute-based encryption (DABE). This method innovatively employs Merkel trees for aggregating user attributes and constructing commitments for zero-knowledge proof verification, ensuring that user attributes and access policies remain confidential. Our solution not only enhances privacy but also fortifies security against man-in-the-middle and replay attacks, offering attribute indistinguishability and tamper resistance. A comparative performance analysis demonstrates that our approach outperforms existing methods in efficiency, reducing time, cost, and space requirements. These advancements mark a significant step forward in ensuring robust user privacy and data security in virtual power plants. [ABSTRACT FROM AUTHOR]

Summary: Image encryption is crucial for protecting image privacy and ensuring security. Encrypting large batches of images of different types and sizes simultaneously with losslessly decryption is often necessary. This paper proposes an optical asymmetric multi-image encryption algorithm to meet these demands. First, plaintext images are converted into one-dimensional pixels and blocked. Image information, image count, and pixels are stored in corresponding areas and reassembled. Unit equal-modulus vector decomposition (UEMD) and phase truncation generate the ciphertext image and keys. The decrypted image is reconstructed from the ciphertext’s information and quantity areas. Asymmetric encryption with different keys for encryption and decryption enhances security, while UEMD ensures lossless recovery and robustness. Experiments demonstrate the proposed algorithm’s efficiency in encrypting multiple grayscale and color images of varying sizes, providing high security, and lossless recovery. This technology offers superior protection for sensitive image data, enhancing encryption system practicality and digital security.

In order to address the problems of the single encryption algorithm, such as low encryption efficiency and unreliable metadata for static data storage of big data platforms in the cloud computing environment, we propose a Hadoop based big data secure storage scheme. Firstly, in order to disperse the NameNode service from a single server to multiple servers, we combine HDFS federation and HDFS high-availability mechanisms, and use the Zookeeper distributed coordination mechanism to coordinate each node to achieve dual-channel storage. Then, we improve the ECC encryption algorithm for the encryption of ordinary data, and adopt a homomorphic encryption algorithm to encrypt data that needs to be calculated. To accelerate the encryption, we adopt the dual-thread encryption mode. Finally, the HDFS control module is designed to combine the encryption algorithm with the storage model. Experimental results show that the proposed solution solves the problem of a single point of failure of metadata, performs well in terms of metadata reliability, and can realize the fault tolerance of the server. The improved encryption algorithm integrates the dual-channel storage mode, and the encryption storage efficiency improves by 27.6% on average.

The swift development of the Internet of Things (IoT) has accelerated digitalization across several industries, offering networked applications in fields such as security, home automation, logistics, and quality control. The growth of connected devices, on the other hand, raises worries about data breaches and security hazards. Because of IoT devices’ computational and energy limits, traditional cryptographic methods face issues. In this context, we emphasize the importance of our contribution to image encryption in IoT environments through the proposal of Multiple Map Chaos Based Image Encryption (MMCBIE), a novel method that leverages the power of multiple chaotic maps. MMCBIE uses multiple chaotic maps to construct a strong encryption framework that considers the inherent features of digital images. Our proposed method, MMCBIE, distinguishes itself by integrating multiple chaotic maps like Henon Chaotic Transform and 2D-Logistic Chaotic Transform in a novel combination, a unique approach that sets it apart from existing schemes. Compared to other chaotic-based encryption systems, this feature renders them practically indistinguishable from pure visual noise. Security evaluations and cryptanalysis confirm MMCBIE’s high-level security properties, indicating its superiority over existing image encryption techniques. MMCBIE demonstrated superior performance with NPCR (Number of Pixel Changing Rate) score of 99.603, UACI (Unified Average Changing Intensity) score of 32.8828, MSE (Mean Square Error) score of 6625.4198, RMSE (Root Mean Square Error) score of 80.0063, PSNR (Peak Signal to Noise Ratio) score of 10.2114, and other security analyses.

The edge devices will produce enormous quantities of data daily as the Industrial Internet of Things (IIoT) expands in scope. Still, most IIoT data is stored in data centers, making it challenging to transfer data between domains safely. Smart logistic products have dramatically changed due to the prevalence of decentralized edge computing and blockchain in the industry sector. To address the need to exchange data between logistics networks, we proposed a novel decentralized hierarchical attribute-based encryption (HABE) scheme combining edge computing and blockchain. To begin, we offer an IoT data encryption strategy in which edge devices can send data to a nearby cloud network for data processing while maintaining privacy. In addition, we developed a blockchain-integrated data-sharing scheme that makes it possible for users to share data via the use of edge and cloud storage. In particular, an IoT device incorporates an encryption-based authentication system to verify users’ access rights at the network’s periphery in a decentralized manner. Using HABE, we provide a blockchain-integrated architecture for the IoT that protects user privacy. The suggested design utilizes the edge and cloud network paradigms and HABE to maintain privacy and works well with smart logistics applications. The authentication time of the proposed model is reduced by 1.5 times compared with the centralized model. The analyses and experimental findings show that the proposed blockchain-integrated edge computing architecture is better than the existing schemes in terms of data sharing, data privacy, and security.