Data Encryption Method Research Articles

Mobile forensics tools and techniques for digital crime investigation: a comprehensive review

<p>Extracting and analyzing data from smartphones, IoT devices, and drones is crucial for conducting digital crime investigations. Effective cyberattack mitigation necessitates the use of advanced Android mobile forensics techniques. The investigation necessitates proficiency in manual, logical, hex dump, chip-off, and microread methodologies. This paper provides a comprehensive overview of Android mobile forensics tools and techniques for digital crime investigation, as well as their use in gathering and analyzing evidence. Forensic software tools like Cellebrite UFED, Oxygen Forensic Detective, XRY by MSAB, Magnet AXIOM, SPF Pro by SalvationDATA, MOBILedit Forensic Express, and EnCase Forensic employ both physical and logical techniques to retrieve data from mobile devices. These advanced tools offer a structured approach to tackling digital crimes effectively. We compare dependability, speed, compatibility, data recovery accuracy, and reporting. Mobile-network forensics ensures data acquisition, decryption, and analysis success. Conclusions show that Android mobile forensics tools for digital crime investigations are diverse and have different capabilities. Mobile forensics software offers complete solutions, but new data storage and encryption methods require constant development. The continuous evolution of forensic software tools and a comprehensive tool classification system could further enhance digital crime investigation capabilities.</p>

QR Code-Based Attendance System for Contact Tracking Post-Pandemic

The COVID-19 pandemic has brought about profound changes in daily life and introduced new challenges to public health maintenance. Despite ongoing uncertainties, with certain regions easing or completely lifting community activity restrictions, persistent concerns about the virus's continued threat prompt the need for robust health monitoring measures. In this context, the use of contact tracing apps becomes pivotal for organizing individuals' movements, monitoring social distancing, and ensuring adherence to health protocols. This study introduces a QR code-based attendance system, a meticulously designed web and Android application aimed at efficiently and accurately tracking individuals' whereabouts. The system leverages QR code scanning technology, and to enhance security, employs the Advanced Encryption Standard (AES) method for data encryption. This ensures the safe encryption of sensitive data, preserving its confidentiality and integrity during transmission and storage. The research outcome is a versatile application facilitating seamless access across diverse locations, allowing real-time tracking of individuals' presence. This capability proves crucial for contact tracing efforts in the event of positive cases, contributing to the implementation of post-pandemic security and surveillance policies. The system's design and features align with the evolving landscape of the pandemic, emphasizing adaptability and comprehensive support for public health initiatives.

Design and application of data security privacy protection technology in dance action sequence arrangement and display system

In view of the excessive consumption of difficult resources in traditional dance choreography, insufficient data in choreography and data leakage crisis in the system, this paper puts forward artificial intelligence technology to study the protection of dance choreography and system data security and privacy. In this paper, the directed graph neural network is used to intelligently arrange the dance movements, and the Hidden Markov Model (HMM) is used to process the dance scene data so that the output data is highly similar to the original data. In the protection of data security and privacy, the method of data encryption is used, and the encrypted data needs to be decrypted by algorithm for reading. The experimental results show that the more complete the dance movement display, the higher the dance recognition rate, and the recognition rate of the dynamic light projection algorithm is greater than 90 % regardless of several sets of dance movements, while the recognition rate of the traditional light projection algorithm is not up to the standard regardless of several sets of movements, and the recognition rate of the point cloud segmentation method is higher than 90 % only in 3–4 sets of dance and 5–6 sets of dance movements.

Dynamically Securing the Data by 1O2 Sensitization of Fluorescent Composites with a High Latency and Uncrackable Features

Comprehensive SummaryDynamic fluorescent materials play a crucial role in secure inks for data encryption; however, they are still plagued by issues such as photodegradation, poor latency, and susceptibility to unauthorized access. Herein, we propose a photochemically modulated dynamic fluorescent encryption system based on 1O2 sensitization of fluorescent composites, comprising a 1O2‐sensitive fluorophore (F2) and non‐emissive polymers. After UV irradiation, in‐situ generated 1O2 from the polymer effectively binds with F2 to form endoperoxides (F2EPO), resulting in a significant redshift in emission, up to 150 nm. The 1O2 concentration is closely related to the irradiation time, rendering different fluorescent colors in a time‐gated fashion. Moreover, the emission of F2EPO can be regulated by polymer chemical structure, molecular weight, and crosslinking density. Relying on these merits, we develop a dynamic data encryption method with various non‐emissive polymers as the data storage media, UV light irradiation as the data encoder, and F2 as the data decoder. UV light irradiation of diverse polymer solutions generates 1O2 at different concentrations, effectively encoding the data, which remains invisible under both UV and natural lights. The addition of F2 to these irradiated polymer solutions produces different redshifted fluorescence, enabling secure data decryption. Attributing to the non‐emissive nature of the polymers, time‐gated readout fashion, excellent latency of 1O2, and subtle interactions between 1O2 and F2, this data encryption is nearly undecipherable. This work offers an advantage data encryption approach beyond the reach of conventional fluorophores.

Physical encryption-compression and decryption-decompression of data using the Fourier transform

In lieu of the traditional method of data encryption using Hadamard matrices we here propose a method which change in the encryption part mathematical with physical means, namely the mathematical Hadamard transform with the physical Fourier transform using a lens. The Fourier transform has a lower power of compression, but the advantage of using physical encoding compensated for this disadvantage. Our approach has two parts, an encryption-compression stage, and a decryption-decompression stage, which are supposed to be complementary and are coupled by means of a computer which controls both experiments and uses the output of the encryption-compression stage as input for the decryption-decompression stage.

FCMPR:A multi-path secure transmission method based on link security assessment and fountain coding

The security of network data transmission has always been a focus of attention. With the rapid development of quantum computers and the rise of intelligent algorithms such as semantic analysis, traditional data encryption methods struggle to ensure the secure transmission of data. The avoidance routing protocol improves transmission security by circumventing malicious nodes and dangerous areas, but it misses the actual optimal path setup, reducing routing opportunities and increasing communication delays, thus failing to meet the application requirements that demand high security and low latency. To address these issues, this paper proposes a multi-path secure transmission method (FCMPR) based on link security assessment and fountain coding. We have designed a link security assessment method based on a random forest traffic detection model, which can obtain the link's confidence level to assess its security. Furthermore, we have proposed a secure multi-path routing transmission mechanism based on fountain code, enabling safe and rapid data transmission without avoiding malicious nodes. Experimental results show that even with a high proportion of malicious nodes in the network, FCMPR can significantly improve the data transmission rate, reduce the transmission delay, and enhance communication quality while ensuring data security.

Interface Control and Status Monitoring of Electronic Information Equipment based on Nonlinear Data Encryption

An advanced electronic information equipment interface control and status monitoring system is proposed to ensure the fairness, objectivity, and security of information while identifying responsibility for traffic accidents. Through an in-depth analysis of the system's security requirements and the current landscape of information security technology, a robust security strategy is developed for each crucial system stage. A PC-based platform is developed for efficient data acquisition, secure processing, reliable transmission, and fortified storage, focusing on implementing nonlinear data encryption methods. Performance evaluation of the system involved rigorous testing using files ranging from 3MB to 10MB. The results of the proposed system revealed a significant improvement in the system's overall speed and efficiency, showcasing an average performance enhancement of one quarter compared to the original platform. The proposed system demonstrated an impressive 15% to 30% increase in processing speed, establishing its capability to ensure data integrity protection during information transmission, facilitate accurate identification of data recording equipment post-accident, and safeguard the security of stored data. The developed electronic information equipment interface control and status monitoring system effectively addresses critical challenges associated with ensuring data integrity and security in traffic accident investigations.

A COMPARATIVE REVIEW OF DATA ENCRYPTION METHODS IN THE USA AND EUROPE

Data encryption is a critical aspect of modern information security, and understanding the approaches taken by different regions is vital for a comprehensive analysis. In the United States and Europe, data encryption methods vary in implementation, legal frameworks, and overall priorities. In the United States, encryption methods are primarily governed by a combination of federal laws and industry standards. The National Institute of Standards and Technology (NIST) plays a central role in recommending cryptographic standards, while the Department of Commerce oversees export controls on encryption technology. The focus in the U.S. is on balancing national security needs with individual privacy rights. The tension between law enforcement's desire for access to encrypted data for criminal investigations and the right to privacy has sparked debates and legal battles. On the other hand, Europe has taken a more privacy-centric approach to data protection. The General Data Protection Regulation (GDPR) is a cornerstone in the European Union's efforts to safeguard individual privacy rights. GDPR mandates the use of encryption to protect personal data, and failure to implement adequate measures can result in hefty fines. European countries also emphasize the importance of end-to-end encryption in communication services to ensure confidentiality. Both regions prioritize encryption, but their approaches reflect different values and legal philosophies. The U.S. tends to navigate a delicate balance between national security and individual rights, while Europe places a stronger emphasis on the protection of personal data as a fundamental right. In terms of technological implementation, the encryption algorithms adopted in both regions are often aligned with global standards. Advanced Encryption Standard (AES) is widely accepted and implemented in various sectors. However, the choice of key management and the level of regulatory oversight differ, contributing to the nuanced landscape of data protection. In conclusion, a comparative review of data encryption methods in the USA and Europe reveals the complex interplay between security, privacy, and legal frameworks. Understanding these differences is crucial for multinational organizations and individuals navigating the intricate landscape of global data protection.
 Keywords: Data, Encryption, USA, Europe, Review.

Coding theory for h(x)-Fibonacci polynomials

The amount of information transmitted over the internet network has dramatically increased with the prevailing of internet use. As a result of this increase, the algorithms used in data encryption methods have gained importance. In this paper, h(x)-Fibonacci coding/decoding method for h(x)-Fibonacci polynomials is introduced. The proposed method is fast because it is based on basic matrix operations, and it is suitable for cryptographic applications because it uses the ASCII character encoding system. For this reason, it differs from the classical algebraic methods in literature. Furthermore, the fact that h(x) is a polynomial improves the security of cryptography.

A statistical Markov-based password strength meter

Although multi-factor authentication is gaining popularity, password-based authentication remains the most commonly employed method for both online login and data encryption. To help users choose secure passwords, password strength meters (PSMs) are a well-known and important tool. However, many PSMs still use simple rule sets or rely on heuristic results. With the continuous development of password-cracking methods, it is difficult for such PSMs to provide accurate assessment results. In this paper, we present a new PSM based on statistical results from a huge number of leaked passwords. The proposed method has a very simple structure, requires only a small amount of storage space, and succeeds in providing reliable feedback in real time. We also confirm the influence of linguistic features on user-created passwords and, therefore, recommend evaluating passwords based on the users’ language.

TO DISTRIBUTE THE ABNORMAL EVENT USING CM-DDS ALGORITHM, WITH SECURELY USING RSA RSA-IVDE ALGORITHM

Automating the secure distribution and storage of video data addresses inefficiencies in manual processes. The emphasis on secure distributed storage aligns with the increasing importance of safeguarding video data. Traditional approaches in distributed video data storage face limitations, like lack of scalability, privacy challenges in surveillance systems and suboptimal storage efficiency. This research addresses the existing limitations in distributed storage for video data by proposing a Central Moment-Driven Distributed Structure (CM-DDS) and an incremental RSA-driven Incremental Video Data Encryption (RSA-IVDE) method. The framework optimizes video data distribution across nodes, enhancing redundancy and fault tolerance for continuous data availability, even in the event of node failures. Emphasizing simplicity and accessibility, the user-friendly interface facilitates efficient management of large video datasets across various applications, including social networks, video games, surveillance and transportation networks. This comprehensive approach aims to provide a robust solution for secure distributed storage and transmission of video data while addressing the challenges identified in the existing research. The proposed approach surpasses other traditional methods with minimal decryption mean time (0.208s), minimal encryption mean time (0.182s) and minimal distribution mean time (1.620s).

Design of Data Encryption and Compression Methods

Big data, cloud computing and other hot areas are the use of personal information, but in the process of using this data, a large number of improper behavior is used to steal personal information. Most of the encryption algorithms in common use nowadays are based on ones that are no longer absolutely secure, such as RSA attacked by factorization, elliptic curves attacked by Pollard's lambda algorithm, and symmetric encryption algorithms attacked by collisions. In this paper, an integrated encryption and compression algorithm is designed, firstly, the data is transformed into the form of matrix, and the Jordan decomposition is used for preliminary compression and encryption from the two-dimensional point of view, and then based on the sparsity of matrix vectors, the compression-aware technique is used for compressing the set of key vectors, and the ciphertext group J produced by Jordan decomposition (which is a string of numbers with matrix diagonal length base √2 N), as well as the set of key vectors Y and the intermediate value Θ produced by compression awareness are obtained in the end. This sidesteps the common algorithms that have already been breached and is able to combine better encryption performance with compression performance while being innovative.

Application of Fast Fourier Transform to the Speech Signals Scrambling

The article is devoted to the closure of speech signals by implementing a fast Fourier transform in a bandpass scrambler. The most radical measure to prevent the interception of speech signals is the use of cryptographic security methods. The first technical security systems began to be developed immediately after the invention of the telephone. The main goal when developing speech transmission systems is to preserve those characteristics that are most important for the listener to perceive. Communication security in the transmission of voice messages is based on the use of a large number of different methods of blocking signals that change the characteristics of speech in such a way that it becomes illegible and unrecognizable to attackers who listen to or intercept the closed voice message. The choice of closure methods depends on the specific application and the technical characteristics of the transmission channel. That is, technical channels of information leakage are a source of information for technical intelligence, which extracts information using technical means. Therefore, the problem of protecting information from technical intelligence is of particular relevance. The object of the study is the transmission of voice messages. The subject of the research is real-time speech closing systems. The purpose of the paper is to use fast Fourier transform to close speech signals in a bandpass scrambler. To do this, it is necessary to assess the capabilities of technical intelligence to intercept information of limited distribution; analyze types of speech signal closing systems.
 The paper presents a block diagram of a combined scrambler, an algorithm for rearranging input signal values using the fast Fourier transform, and hashing functions that are used to obtain a speech signal from a combined scrambler. It has been determined that "through-window" scramblers are the most reliable, and for greater levels of closure, combination scramblers should be used. The task set for further development of the topic is the development of a software application for the operation of streaming data encryption methods in real time.

3 Smartphone Digital Phenotyping for Unobtrusive and Continuous Assessment of Everyday Cognition and Movement Trajectories in Older Adults

Objective:To evaluate the feasibility, usability, and preliminary validity of a digital phenotyping protocol to capture everyday cognition and activities in vivo among older adults.Participants and Methods:Eight participants (M age=69.1 + 2.6; M education=18.0 + 1.4; 50% female; 88% non-Hispanic White) with normal cognition or mild cognitive impairment used an open-source smartphone application (mindLAMP) to passively and continuously capture sensor data including global positioning system (GPS) trajectories for a 4-week study period. Baseline neuropsychological tests and measures of depression, self-reported cognitive decline and mobility patterns were collected as external validators for digital data. Participants downloaded mindLAMP onto their smartphones and resumed their daily routines for 4 weeks before removing mindLAMP and completing a debriefing questionnaire. A cognitive composite was derived by averaging T-scores across domains of attention, executive functioning, processing speed, memory, and language. GPS raw data were processed to generate monthly average and standard deviation mobility metrics for each participant, including time spent at home, distance travelled, radius of gyration, flight length, and circadian routine. Feasibility and usability findings are presented along with correlation coefficients >.4 between GPS metrics and external validators.Results:100% of enrolled participants completed the 4-week study without requesting to withdraw. Usability ratings ranged from poor to excellent. 75% of participants agreed that mindLAMP was easy to use, whereas only 1 participant enjoyed using mindLAMP. 100% of participants were satisfied with the study team’s explanation of procedures, privacy safeguards, data encryption methods and risks/benefits, reflected in an average score of 98.8% on the comprehension of consent quiz. No participants reported feeling uncomfortable, suspicious, or paranoid due to the study application running on their smartphone. No participants endorsed new problems using their smartphone, though 75% reported charging it more frequently during the study period. On average each day, participants spent 1121 + 227 minutes at home, travelled 38727 + 36210 geodesic units, and had 201 + 149 minutes of missing GPS data. Overall, greater amounts of activity (monthly average) and higher variability (monthly standard deviation) in GPS metrics were associated with better outcomes. Specifically, less time spent at home, greater distance travelled, larger radius of gyration, greater flight length, and greater variability in home time, distance travelled, radius of gyration and flight length were associated with less depression, less self-reported cognitive decline, better cognition, and greater self-reported mobility (.40< |r| <.69). On the other hand, greater circadian routine was associated with more self-reported cognitive decline (r=.66) and less self-reported mobility (r=-.43).Conclusions:Smartphone digital phenotyping is a feasible and acceptable method to capture everyday activities in older adults. Continuous collection of data from personal devices warrants caution; however, participants denied privacy concerns and expressed an overall positive experience. High frequency GPS data collection impacts battery life and should be considered among relative risks and confounds to naturalistic assessment. Patterns of behavior from passive smartphone data show promise as an unobtrusive method to identify cognitive risk and resilience in older adults. Subsequent analyses will evaluate additional sensor metrics across a larger and more heterogeneous cohort.

Application of Walsh System in Data Encryption

This article explores the application of the Walsh system in modern data encryption methods. The advantages and limitations of this system are reviewed and its effectiveness is analyzed in comparison to other encryption schemes. The article describes the mathematical basis of the Walsh transform, its use for encryption and decryption, and its practical applications. In conclusion, prospects for further research in this area are considered.

A novel data encryption method using an interlaced chaotic transform

We present a novel data encryption approach that utilizes a cascaded chaotic map application. The chaotic map used in both permutation and diffusion is Arnold’s Cat Map (ACM), where the transformation is periodic and the encrypted data can be recovered. The original format of ACM is a two-dimensional mapping, and therefore it is suitable to randomize the pixel locations in an image. Since the values of pixels stay intact during the transformation, the process cannot encrypt an image, and known-text attacks can be used to get back the transformation matrix. The proposed approach uses ACM to shuffle the positions and values of two-dimensional data in an interlaced and nested process. This combination extends the period of the transformation, which is significantly longer than the period of the initial transformation. Furthermore, the nested process's possible combinations vastly expand the key space. At the same time, the interlaced pixel and value transformation makes the encryption highly resistant to any known-text attacks. The encrypted data passes all random-data tests proposed by the National Institute of Standards and Technology. Any type of data, including ASCII text, can be encrypted so long as it can be rearranged into a two-dimensional format.

Conventional Non-Fluorescent Polymers: Unconventional Security Inks for Data Storage and Multidimensional Photonic Cryptography.

Traditional security inks relying on fluorescent/phosphorescent molecules are facing increasing risks of forgery or tampering due to their simple readout scheme (i.e., UV-light irradiation) and the advancement of counterfeiting technologies. In this work, a multidimensional data-encryption method based on non-fluorescent polymers via a "lock-key" mechanism is developed. The non-fluorescent invisible polymer inks serve as the "lock" for data-encryption, while the anti-rigidochromic fluorophores that can distinctively light up the polymer inks with programed emissions are "keys" for decryption. The emission of decrypted data is prescribed by polymer chemical structure, molecular weight, topology, copolymer sequence, and phase structure, and shows distinct intensity, wavelength, and chirality compared with the intrinsic emission of fluorophores. Therefore, the data is triply encrypted and naturally gains a high-security level, e.g., only one out of 20000 keys can access the only correct readout from 40000000 possible outputs in a three-polymers-based data-encryption matrix. Note that fluorophores lacking anti-rigidochrimism cannot selectively light up the inks and fail in data-decryption. Further, the diverse topologies, less well-defined structures, and random-coiled shapes of polymers make it impossible for them to be imitated. This work offers a new design for security inks and boosts data security levels beyond the reach of conventional fluorescent inks.

APPLICATION OF A MATHEMATICAL MODEL FOR THE GENERATION OF SEPARATE ELEMENTS OF A STEGANOGRAPHIC SYSTEM IN A HIGHER EDUCATION INSTITUTION

The article presents the method of generating separate elements of the steganographic system based on the combination of cryptography and steganography methods, which makes it possible to increase the level of information protection and develop more effective new non-traditional methods of ensuring information security in the global network. Considering the constant development and improvement of computer cryptography and steganography methods, the study of this particular area of steganoanalysis is the most relevant. 
 It is proposed to apply the method of replacing the least significant bits (LSB method), because it, in combination with the RSA cryptographic algorithm, allows to ensure a high level of information security and the speed of embedding and extraction of a large amount of information.
 The practical value lies in the ability to quickly generate steganographic containers and ensure reliable encryption and decryption of hidden information in them. At the stage of experimental research, the proposed method of replacing the younger bits was compared with other methods that could be used to generate individual elements of the steganographic system. According to research results, the LSB method has clearly confirmed its effectiveness. The results of the experiment showed the high stability and quality of the received data encryption and decryption method when sending it through an open communication channel (e-mail).

Data Class-Specific All-Optical Transformations and Encryption.

Diffractive optical networks provide rich opportunities for visual computing tasks since the spatial information of a scene can be directly accessed by a diffractive processor without requiring any digital pre-processing steps. Here we present data class-specific transformations all-optically performed between the input and output fields-of-view (FOVs) of a diffractive network. The visual information of the objects is encoded into the amplitude (A), phase (P), or intensity (I) of the optical field at the input, which is all-optically processed by a data class-specific diffractive network. At the output, an image sensor-array directly measures the transformed patterns, all-optically encrypted using the transformation matrices pre-assigned to different data classes, i.e., a separate matrix for each data class. The original input images can be recovered by applying the correct decryption key (the inverse transformation) corresponding to the matching data class, while applying any other key will lead to loss of information. The class-specificity of these all-optical diffractive transformations creates opportunities where different keys can be distributed to different users; each user can only decode the acquired images of only one data class, serving multiple users in an all-optically encrypted manner. We numerically demonstrated all-optical class-specific transformations covering A → A, I → I, and P → I transformations using various image datasets. We also experimentally validated the feasibility of this framework by fabricating class-specific I → I transformation diffractive networks and successfully tested them at different parts of the electromagnetic spectrum, i.e., 1550 nm and 0.75 mm wavelengths. Data class-specific all-optical transformations provide a fast and energy-efficient method for image and data encryption, enhancing data security and privacy. This article is protected by copyright. All rights reserved.

Side Channel Analysis: A Novel Intrusion Detection System Based on Vehicle Voltage Signals

Intelligent connected vehicles (ICVs) integrate advanced equipment and communication network technologies to realize information exchange and sharing between vehicles and people, roads, clouds, etc., bringing great convenience to people's lives. However, the interconnection of intelligent equipment and vehicles also brings many vulnerable interfaces, threatening the security of in-vehicle networks, e.g., controller area network (CAN) bus. For protecting the security of CAN bus, some researchers propose a data encryption and decryption protocol-based method. Note that due to the resource constraints of computing and bandwidth and the requirements for low-delay data transmission, the research on protocol-based data encryption and decryption method is progressing slowly. For this reason, more researchers study vehicle intrusion detection systems (IDSs) based on side channel analysis. It does not occupy the bandwidth of CAN bus, and detects intrusion by analyzing the physical characteristics of CAN bus. Nevertheless, most of the existing work either cannot locate the source electronic control unit (ECU) of the malicious data frames, or cannot detect malicious data frames from ECUs and external nodes simultaneously, which greatly limits their practical application value. Therefore, we propose a novel IDS based on vehicle voltage signals. Specifically, we map multiple identifiers (IDs) sent for each ECU without developer documentation. In addition, we creatively design FeatureBagging-CNN combined model to detect malicious intrusion. When the external nodes or compromised ECUs send malicious data frames, the system can accurately detect them and locate their sender.