High Level Of Security Research Articles

Conceptional Pure-Tungsten Metasurfaces Based on Femtosecond Laser Nanomanufacturing

A laser-induced periodic surface structure (LIPSS), which can be easily produced by femtosecond laser ablation, is a unique nanostructure with a visible refractive color that can be controlled by altering its orientation and uniformity, making it suitable for use in colorful marking, camouflage, and anti-counterfeiting measures. However, single-mode information camouflage can no longer meet increasingly higher-level security requirements. Therefore, metasurfaces offer revolutionary solutions. In this study, conceptual metasurfaces of pure tungsten are theoretically proposed and verified using hierarchical LIPSS/nanoparticle (NP) nanostructures as meta-atoms. The anisotropy of the LIPSS nanostructure enables polarization-sensitive optical modulation, whereas the spatial configuration, particle size, and period of LIPSS in the LIPSS/NP meta-atoms provide flexibility for tailoring broadband optical responses. In x-polarization, the LIPSS/NP meta-atom system provides more visible colors and divergent infrared absorbance (emission) than in y-polarized and unpolarized modes, paving the way for vividly colorful polarization-sensitive displays and information camouflage in infrared bands. A simplified rendition of the world-famous painting “The Starry Night” by Van Gogh is used as a proof-of-concept. Preliminary experimental results are presented, based on which the feasibility and challenges for laser nanomanufacturing of the proposed conceptual metasurfaces are discussed, aiming to provide inspiration for the development of novel metasurfaces through interdisciplinary studies.

ANALYSIS OF BLOCKCHAIN TYPES AND THEIR SUITABILITY FOR IMAGE STORAGE

There different types of blockchains and their possible use for creating an image repository are investigated. The purpose of the study was to evaluate the advantages and limitations of different types of blockchains in terms of image storage. Data processing methods were applied to analyze the technical characteristics of various types of blockchains and comparative analysis of efficiency and reliability parameters. The results were obtained, which made it possible to formulate the principles of choosing the type of blockchain for creating image storage and to identify the advantages and limitations of each type from the point of view of image storage, depending on the priorities of the software product. The conclusion is that the use of blockchain provides a high level of security and integrity of images, some types of blockchains exhibit high speed and scalability. However, it is important to understand that the preservation process may remain centralized, so more research is needed to optimally use and develop these technologies. Future research may include an analysis of the possibilities of ensuring the privacy of participants and the development of standards for the sharing of multimedia content via blockchain. It is important to consider that the use of blockchain can contribute to increasing transparency and trust in the process of storing and sharing multimedia content, which is important for the development of the digital economy. However, in order to achieve the full potential of blockchain in the field of multimedia, it is necessary to develop effective strategies to solve the problems of privacy, scalability and centralization that arise when implementing these technologies. Such a comprehensive approach will provide a stable and effective infrastructure for managing multimedia content in the digital environment.

ЕФЕКТИВНІ СХОВИЩА ДАНИХ ДЛЯ РІШЕНЬ МАШИННОГО НАВЧАННЯ

Awareness of the importance of using effective data warehouses to develop machine learning solutions in today's world is becoming increasingly relevant in connection with the growth of data volumes and the growing need for accurate and productive models. The article identifies major vital requirements for data storage systems to ensure effective data management in building machine learning solutions. The study underscores the practical implications of rapid data access and minimal latency, reliable storage systems with robust backup and recovery mechanisms, high-level security, flexibility in handling different data types, and cost-effectiveness. These factors are not just theoretical considerations but directly impact the efficiency and success of machine learning solutions. Together with describing the concepts of block storage and object storage, the article also compares major cloud platforms—AWS (Amazon Web Services), Microsoft Azure, and Google Cloud Platform (GCP)—each providing a comprehensive range of flexible and customizable storage, security, and data processing services. These platforms enable users to manage their information resources flexibly and efficiently, offering unique features that cater to the specific needs of machine learning applications. Understanding the nuances of each provider's offerings empowers engineers and researchers to make informed decisions that align with their unique requirements. The article provides a thorough overview of the key considerations and available options, guiding strategic decisions to support machine learning initiatives effectively. Also the importance of staying up to date with the evolution of major platforms offerings is emphasized. In conclusion, selecting the proper data storage solution is critical for enhancing the performance, security, and cost-efficiency of machine learning models.

Job insecurity and fertility: Evidence from massive lay-offs in urban China

We exploit a staggered reform of state-owned enterprises (SOEs) in the late 1990s in China to provide plausibly causal evidence that job insecurity has a first-order impact on fertility. Prior to the reform, unemployment rates were low and job security for SOE workers paralleled that of government employees. Post-reform, numerous SOE employees were laid off and their contracts were no longer permanent, but government employees continued to enjoy high levels of job security. We find that the reform caused SOE employees who retained their positions to delay having their first child by 0.718 years. The spillover effects are sizable: employees in the untargeted private sector delay starting a family by 0.387 years. Despite the importance of family lineage in China at the time, our findings indicate that the fertility response transcended mere birth timing adjustments, and decreased couples’ likelihood of having children. Specifically, the reform initially reduced the number of births by 8.4 % in the short run and had a more pronounced long-term effect on completed fertility at age 45.

Legal Aspects of Using Blockchain Technologies in the Field of E-Commerce on SDG'S

Objective: The objective of this study is legal aspects of blockchain. Theoretical Framework: Blockchain is one of the most prominent technologies and it has become a driving factor in business transformation. Method: Methods of historical and logical analysis and comparison, expert opinions, system analysis and forecasting were used. The research materials included legal aspects, in particular, in the development of blockchain technology. Results and Discussion: Blockchain, like any electronic technology, can have different forms of social implementation. Their openness is manifested in the fact that anyone can become a network node participating in the consensus procedure. Information in public blockchains is actually and legally publicly available. The listed qualities ensure a high level of security of public blockchains and a high level of users’ trust toward them. Research Implications: The legal regulation of digital technologies is becoming an important tool for ensuring a balance between public and private interests, benefits and risks of the digital age. Originality/Value: The global blockchain market will grow significantly in the coming years. The new vector of blockchain technology will be aimed at accelerating the pace of digitalization, financial inclusion and enhancing security. There is no doubt that blockchain is a disruptive technology and will continue to dominate the business world in the coming years.

Hyperentanglement quantum communication over a 50 km noisy fiber channel

High-dimensional entanglement not only offers a high security level for quantum communication but also promises improved information capacity and noise resistance of the system. However, due to various constraints on different high-dimensional degrees of freedom, whether these advantages can bring improvement to the actual implementation is still not well proven. Here we present a scheme to fully utilize these advantages over long-distance noisy fiber channels. We exploit polarization and time-bin hyperentanglement to achieve high-dimensional coding, and observe significant enhancements in secure key rates and noise tolerance that surpass the capabilities of qubit systems. Moreover, the demonstration achieves a distribution up to 50 km, which is the longest distance for high-dimensional entanglement-based quantum key distribution up to date, to our knowledge. Our demonstration validates the potential of high-dimensional entanglement for quantum communications over long-distance noisy channels, paving the way for a resilient and resource-efficient quantum network.

Fast and Efficient UserID Lookup in Distributed Authentication: A Probabilistic Approach Using Bloom Filters

Purpose: User authentication in distributed systems presents unique challenges due to the decentralized nature of these environments and the potential for high-volume login attempts. This paper proposes an efficient method for UserID existence checking during the login process using Bloom filters, a space-efficient probabilistic data structure. Our approach aims to reduce authentication latency and minimize network traffic while maintaining a high level of security. Methodology: We present a novel system architecture that incorporates Bloom filters at strategic points within the distributed system to perform rapid preliminary checks on UserID existence. This method allows for quick rejection of non-existent UserIDs without querying the main user database, significantly reducing the load on central authentication servers. The paper details the implementation of Bloom filters optimized for UserID storage and lookup, including considerations for filter size, hash function selection, and false positive rate management. We also describe the integration of this method into a typical authentication workflow, highlighting the points at which Bloom filter checks are performed and how they interact with existing security measures. Findings: To evaluate the effectiveness of our approach, we conducted extensive experiments simulating various scales of distributed systems and login attempt patterns. Our results demonstrate that the Bloom filter-based UserID existence checking method reduces authentication latency by an average of 37% compared to traditional database lookup methods. Additionally, we observed a 42% decrease in network traffic related to authentication processes, indicating improved scalability for large-scale distributed systems. The paper also discusses the trade-offs inherent in using probabilistic data structures for security-critical operations, addressing potential vulnerabilities and proposing mitigation strategies. We conclude by outlining future research directions, including adaptive Bloom filter sizing and the potential application of this method to other aspects of distributed system security. Unique Contribution to Theory, Policy and Practice: This research contributes to the field of distributed systems security by providing a practical, efficient, and scalable solution for UserID existence checking, potentially improving the performance and user experience of large-scale authentication systems.

Aplikasi Absensi Berbasis Android Pada Sekolah Boarding Sebagai Transformasi Digital Bidang Pendidikan

Boarding schools require students and staff to reside on campus for a set period, necessitating high levels of security and comfort to optimize educational outcomes through effective human resource management. Managing staff and student attendance is crucial in these settings, exemplified by the manual attendance system at Insan Cendikia Magnet School in Bogor. However, manual systems often suffer from inefficiencies, inaccuracies leading to data errors, fraud, and real-time monitoring challenges. To address these issues, this study developed a digital attendance system using FlutterFlow, employing barcode scanning for both academic and non-academic staff. Implementation of this system improved digital attendance processes, with testing confirming its reliable performance. The system effectively met user needs and conditions, integrating attendance data with real-time reporting features. These accessible reports facilitate evaluation and decision-making regarding staff attendance.

Perancangan Aplikasi Enkripsi dan Dekripsi Gambar Cetak Biru Pada PT. Patco Elektronik Teknologi Menggunakan Algoritma RSA Berbasis Android

PT. Patco Elektronik Teknologi, a leading company in the Electronics industry, urgently needs to enhance the security of blueprint mold data in its Moldshop division. The process of mold repair using CNC machines requires secure access to the company's standard blueprint drawings. Hence, this study aims to develop an Android-based application for encrypting and decrypting blueprint images using the Rivest Shamir Adleman algorithm. It also addresses challenges such as budget constraints, Android device availability, and data security. The method chosen, Rivest Shamir Adleman, is renowned for its asymmetric cryptography and will be implemented in the Android application for securing blueprint images. The research successfully resulted in the creation, implementation, and testing of the Rivest Shamir Adleman Android application. Testing demonstrated that the program can efficiently encrypt and decrypt blueprint images, with encryption averaging 4 to 15 seconds and decryption 2 to 5 seconds using this method. By employing Rivest Shamir Adleman, the application ensures high-level security for blueprint image files.

HAETAE: Shorter Lattice-Based Fiat-Shamir Signatures

We present HAETAE (Hyperball bimodAl modulE rejecTion signAture schemE), a new lattice-based signature scheme. Like the NIST-selected Dilithium signature scheme, HAETAE is based on the Fiat-Shamir with Aborts paradigm, but our design choices target an improved complexity/compactness compromise that is highly relevant for many space-limited application scenarios. We primarily focus on reducing signature and verification key sizes so that signatures fit into one TCP or UDP datagram while preserving a high level of security against a variety of attacks. As a result, our scheme has signature and verification key sizes up to 39% and 25% smaller, respectively, compared than Dilithium. We provide a portable, constanttime reference implementation together with an optimized implementation using AVX2 instructions and an implementation with reduced stack size for the Cortex-M4. Moreover, we describe how to efficiently protect HAETAE against implementation attacks such as side-channel analysis, making it an attractive candidate for use in IoT and other embedded systems.

Strategies and Pathways for High-Quality Development in Primary-level Governance of Campus Security in Higher Education Institutions from a High-Level Security Perspective

At present, China s development is at a critical juncture where strategic opportunities coexist with risks and challenges. Against the backdrop of a risk society, the sudden and frequent occurrence of safety incidents in Chinese universities is evident, characterized by complex causes, severe harm, and far-reaching impacts. To integrate high-level safety throughout all fields and processes of campus safety work, and to strengthen the foundation for campus environmental stability on a broader scale, at a higher starting point, and at a higher level, the governance philosophy should first shift to multi-dimensional co-governance, proactively enhancing systemic resilience, and precise feedback loop governance. Secondly, the framework construction should focus on content expansion, the cultivation of stakeholders, and mechanism construction. Finally, through key strategies and optimization paths, promote high-quality development of Primary-level governance in university campus safety and maintain a safe and stable campus environment.

Comparing experts’ and users’ perspectives on the use of password workarounds and the risk of data breaches

Purpose The increased use of Information Systems (IS) as a working tool for employees increases the number of accounts and passwords required. Despite being more aware of password entropy, users still often participate in deviant password behaviors, known as “password workarounds” or “shadow security.” These deviant password behaviors can put individuals and organizations at risk, resulting in a data breach. This paper aims to engage IS users and Subject Matter Experts (SMEs), focused on designing, developing and empirically validating the Password Workaround Cybersecurity Risk Taxonomy (PaWoCyRiT) – a 2x2 taxonomy constructed by aggregated scores of perceived cybersecurity risks from Password Workarounds (PWWAs) techniques and their usage frequency. Design/methodology/approach This research study was a developmental design conducted in three phases using qualitative and quantitative methods: (1) A set of 10 PWWAs that were identified from the literature were validated by SMEs along with their perspectives on the PWWAs usage and risk for data breach; (2) A pilot study was conducted to ensure reliability and validity and identify if any measurement issues would have hindered the results and (3) The main study data collection was conducted with a large group of IS users, where also they reported on coworkers' engagement frequencies related to the PWWAs. Findings The results indicate that statistically significant differences were found between SMEs and IS users in their aggregated perceptions of risks of the PWWAs in causing a data breach, with IS users perceiving higher risks. Engagement patterns varied between the two groups, as well as factors like years of IS experience, gender and job level had statistically significant differences among groups. Practical implications The PaWoCyRiT taxonomy that the we have developed and empirically validated is a handy tool for organizational cyber risk officers. The taxonomy provides organizations with a quantifiable means to assess and ultimately mitigate cybersecurity risks. Social implications Passwords have been used for a long time to grant controlled access to classified spaces, electronics, networks and more. However, the dramatic increase in user accounts over the past few decades has exposed the realization that technological measures alone cannot ensure a high level of IS security; this leaves the end-users holding a critical role in protecting their organization and personal information. Thus, the taxonomy that the authors have developed and empirically validated provides broader implications for society, as it assists organizations in all industries with the ability to mitigate the risks of data breaches that can result from PWWAs. Originality/value The taxonomy the we have developed and validated, the PaWoCyRiT, provides organizations with insights into password-related risks and behaviors that may lead to data breaches.

Cyclopentadithiophene-based conjugated polymer artificial synapses for dual information encryption

High-performance polymer memristors with analog-type switching behaviors and low power consumption, which is a perfect candidate for brainoid intelligence, have triggered the research campaign of the novel in-memory computing paradigm. A novel poly[cyclopentadithiophene- alt-thiophene] with triazole and ferrocene moieties in the sidechains (PCTF) is synthesized by copper-catalyzed azide-alkyne Click chemistry reaction of poly[4,4-bis(6-azidohexyl)-4H- cyclopenta(1,2-b: 5,4-b′) dithiophene-alt-thiophene], which is prepared by the reaction of poly[thiophene-alt-4,4- bis(6-bromohexyl)- 4H-cyclopenta(1,2-b:5,4-b′)dithiophene](PTT-Br) with NaN3, with ethynylferrocene. The PTT-Br film sandwiched between the Al and ITO electrodes shows a typical history-dependent memristive switching performance at a small sweep voltage range of ± 1 V, with 6 distinguishable conductance states. The device current can be modulated continuously when being subjected to consecutive positive and negative voltage sweeps. In contrast to PTT-Br, PCTF exhibits excellent nonvolatile memristive performance, with 16 distinguishable conductance states due to the combined action of charge transfer between the triazole and ferrocene moieties, and redox activity from both the ferrocene and polymer backbone. As an important component related to human memory, the short-term synaptic plasticity to long-term potentiation/plasticity transition is, for the first time, successfully used to realize dual information encryption at a high information security level. Only by inputting a given number of voltage pulses and at a specific time can classified information be correctly read out.

MOMTA-HN: A Secure and Reliable Multi-Objective Optimized Multipath Transmission Algorithm for Heterogeneous Networks

With the rapid development of heterogeneous network technologies, such as mobile edge computing, satellite communications, self-organizing networks, and the wired Internet, satisfying users’ increasingly diversified and complex communication needs in dynamic and evolving network environments has become a critical research topic. Ensuring secure and reliable information transmission is essential for stable network operation in these complex environments. Addressing this challenge, this study proposed a secure and reliable multi-objective optimized multipath transmission algorithm for heterogeneous networks to enhance security and reliability during data transmission. The core principle of this algorithm was that multipath transmission can provide additional protection through redundant paths. This redundancy ensured that even if one path is attacked or fails, alternative paths can maintain data integrity and reachability. In this study, we employed the Optimized Non-dominated Sorting Genetic Algorithm II (ONSGA-II) to determine the range of the initial population and filter suitable paths by optimizing them according to different demand objectives. In the path selection process, we introduced an innovative deletion graph method, which ensures that redundant paths do not share any common links with the original paths, except when there are unique links. This approach enhances the independence of transmission paths and improves the security of the transmission process. It effectively protects against security threats such as single points of failure and link attacks. We have verified the effectiveness of the algorithm through a series of experiments, and the proposed algorithm can provide decision-makers with high-reliability and low-latency transmission paths in heterogeneous network environments. At the same time, we verified the performance of the algorithm when encountering attacks, which is superior to other classical algorithms. Even in the face of network failures and attacks, it can maintain a high level of data integrity and security.

A Long Tweak Goes a Long Way: High Multi-user Security Authenticated Encryption from Tweakable Block Ciphers

We analyze the multi-user (mu) security of a family of nonce-based authentication encryption (nAE) schemes based on a tweakable block cipher (TBC). The starting point of our work is an analysis of the mu security of the SCT-II mode which underlies the nAE scheme Deoxys-II, winner of the CAESAR competition for the defense-in-depth category. We extend this analysis in two directions, as we detail now. First, we investigate the mu security of several TBC-based variants of the counter encryption mode (including CTRT, the encryption mode used within SCT-II) that differ by the way a nonce, a random value, and a counter are combined as tweak and plaintext inputs to the TBC to produce the keystream blocks that will mask the plaintext blocks. Then, we consider the authentication part of SCT-II and study the mu security of the nonce-based MAC Nonce-as-Tweak (NaT) built from a TBC and an almost universal (AU) hash function. We also observe that the standard construction of an AU hash function from a (T)BC can be proven secure under the assumption that the underlying TBC is unpredictable rather than pseudorandom, allowing much better conjectures on the concrete AU advantage. This allows us to derive the mu security of the family of nAE modes obtained by combining these encryption/MAC building blocks through the NSIV composition method. Some of these modes require an underlying TBC with a larger tweak length than what is usually available for existing ones. We then show the practicality of our modes by instantiating them with two new TBC constructions, Deoxys-TBC-512 and Deoxys-TBC-640, which can be seen as natural extensions of the Deoxys-TBC family to larger tweak input sizes. Designing such TBCs with unusually large tweaks is prone to pitfalls: Indeed, we show that a large-tweak proposal for SKINNY published at EUROCRYPT 2020 presents an inherent construction flaw. We therefore provide a sound design strategy to construct large-tweak TBCs within the Superposition Tweakey (STK) framework, leading to new Deoxys-TBC and SKINNY variants. We provide software benchmarks indicating that while ensuring a very high security level, the performances of our proposals remain very competitive.

Photo-responsive anticounterfeiting inks switching between colorless and cyan/magenta/yellow for flexible, full-color, and large-area printing

Inkjet printing of photo-responsive patterns capable of switching between colorless and full-color is regarded as an innovative anticounterfeiting technique with a higher security level. Therefore, colorless inks which can be changed to cyan (C), magenta (M), and yellow (Y) upon photochromism are highly required. Herein, three photochromic (PC) inks C, M, and Y switching between colorless and cyan/magenta/yellow, respectively, have been successfully prepared by dissolving viologen derivatives AV, AEV, and NOV in solvent mixtures of water, ethanol, and ethylene glycol, with sodium dodecyl sulfate (SDS) as surfactant. With a mass fraction of 0.5 wt% for SDS, an optimal rheological property with a viscosity of 3.48 mPa·s, a contact angle of 29.4° on poly (ethylene terephthalate) (PET) substrate, a surface tension of 23.16 mN m−1, and a Z value of 3.85, is realized for ink C. Under the same conditions, inks M and Y are prepared and display suitable rheological properties for inkjet printing. The films are invisible initially and become colorful upon UV irradiation with no significant decay after 20 repetitive PC switching. Subsequently, various colorful patterns with high resolutions were printed on conventional A4 paper and become visible only after irradiation by a UV lamp. Therefore, these photo-responsive tricolor inks can be used in anticounterfeiting field and two practical examples of a stamp and a personal check with cryptical texts and color information have been demonstrated. Overall, the developed photo-responsive C/M/Y inks can be utilized in flexible, full-color, and large-area printing, providing a novel approach towards innovative anticounterfeiting technology.

Perancangan Dan Implementasi Caesar Chiper Untuk Meningkatkan Keamanan Sistem Informasi Akademik Sekolah Berbasis Android

This research focuses on the design and implementation of the Caesar Cipher method to improve the security of an Android-based School Academic Information System. In this digital era, data security is a major concern, especially in school academic information systems that manage important data. The Caesar Cipher method, as a simple and easy to implement encryption technique, is used in this research. The research results show that the implementation of Caesar Cipher has succeeded in increasing data security in the system. While this method does not provide a very high level of security, it can be part of a more complex security approach. Overall, this research shows that the design and implementation of Caesar Cipher is an effective step in improving the security of Android-based school academic information systems.

Genetic algorithms and deep learning for unique facial landmark-based key generation

Generating secure secret keys remains essential in the realm of biometric authentication systems. Traditional methods have often suffered from inefficiency, insecurity, or the requirement for additional hardware. In this study, an innovative approach to secret key generation is proposed, leveraging deep learning, facial feature extraction, genetic algorithms, and linear feedback shift registers (LFSRs). These techniques are combined to create robust, unique keys based on users' facial features. A convolutional neural network (CNN) is employed for the extraction of facial features from user images and for the optimization of LFSR parameters using a genetic algorithm. Furthermore, another neural network is utilized to establish a connection between facial features and the LFSR-generated output, resulting in the secret key. Rigorous evaluation of the method is conducted across various facial datasets, with a comparison against existing approaches. The results demonstrate the effectiveness of the method, yielding secret key length of 92,706 characterized by an entropy value of 3.24, a low average correlation value of 0.1554, and a high level of security. This research represents a significant advancement in secure biometric authentication, addressing the limitations of conventional key generation methods.

Architecture and iot security systems based on fog computing

The subject of the study is is the security architecture of the Internet of Things (IoT) based on fog computing, which allows providing efficient and secure services for many IoT users. The goal is to investigate the security architecture for IoT systems based on fog computing. To achieve the goal, the following tasks were solved: the concept of fog computing is proposed, its architecture is considered and a comparative analysis of fog and cloud computing architectures is made; the principles of designing and implementing the architecture of a fog computing system are outlined; multi-level security measures based on fog computing are investigated; and the areas of use of fog computing-based Internet of Things networks are described. When performing the tasks, such research methods were used as: theoretical analysis of literature sources; analysis of the principles of designing and implementing the security architecture of the Internet of Things; analysis of security measures at different levels of the architecture. The following results were obtained: the architecture of fog computing is considered and compared with the cloud architecture; the principles of designing and implementing the architecture of fog computing systems are formulated; multi-level IoT security measures based on fog computing are proposed. Conclusions: research on IoT security systems based on fog computing has important theoretical implications. The fog computing architecture, in contrast to the cloud architecture, better meets the demand for high traffic and low latency of mobile applications, providing more advantages for systems that require real-time information processing. When designing and implementing the architecture of fog computing systems, the factors of memory capacity, latency, and utility should be taken into account to effectively integrate fog technologies with IoT. To ensure a high level of system security, multi-level security measures should be implemented using both software and hardware solutions.

SignEEG v1.0: Multimodal Dataset with Electroencephalography and Hand-written Signature for Biometric Systems

Handwritten signatures in biometric authentication leverage unique individual characteristics for identification, offering high specificity through dynamic and static properties. However, this modality faces significant challenges from sophisticated forgery attempts, underscoring the need for enhanced security measures in common applications. To address forgery in signature-based biometric systems, integrating a forgery-resistant modality, namely, noninvasive electroencephalography (EEG), which captures unique brain activity patterns, can significantly enhance system robustness by leveraging multimodality’s strengths. By combining EEG, a physiological modality, with handwritten signatures, a behavioral modality, our approach capitalizes on the strengths of both, significantly fortifying the robustness of biometric systems through this multimodal integration. In addition, EEG’s resistance to replication offers a high-security level, making it a robust addition to user identification and verification. This study presents a new multimodal SignEEG v1.0 dataset based on EEG and hand-drawn signatures from 70 subjects. EEG signals and hand-drawn signatures have been collected with Emotiv Insight and Wacom One sensors, respectively. The multimodal data consists of three paradigms based on mental, & motor imagery, and physical execution: i) thinking of the signature’s image, (ii) drawing the signature mentally, and (iii) drawing a signature physically. Extensive experiments have been conducted to establish a baseline with machine learning classifiers. The results demonstrate that multimodality in biometric systems significantly enhances robustness, achieving high reliability even with limited sample sizes. We release the raw, pre-processed data and easy-to-follow implementation details.