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This work presents a multi-level approximation exploration undertaken on the Ring-Learning-with-Errors (R-LWE) based Public-key Cryptographic (PKC) schemes that belong to quantum-resilient cryptography algorithms. Among the various quantum-resilient cryptography schemes proposed in the currently running NIST’s Post-quantum Cryptography (PQC) standardization plan, the lattice based LWE schemes have emerged as the most viable and preferred class for the IoT applications due to their compact area and memory footprint compared to other alternatives. However, compared to the classical schemes used today, R-LWE is much harder a challenge to fit on embedded IoT (end-node) devices, due to their stricter resource constraints (lower area, memory, energy budgets) as well as their limited computational capabilities. To the best of our knowledge, this is the first endeavour exploring the inherent approximate nature of LWE problem to undertake a multi-level Approximate R-LWE (AxRLWE) architecture with respective security estimates opt for lightweight IoT devices. Undertaking AxRLWE on Field Programmable Gate Arrays (FPGAs), we benchmarked a 64% area reduction cost compared to earlier accurate R-LWE designs at the cost of reduced quantum-security. For the Application Specific Integrated Circuits (ASICs) with 45nm CMOS technology, AxRLWE was benchmarked to fit well within the same area-budget of lightweight ECC processor and consume a third of energy compared to special class of R-Binary LWE (R-BLWE) designs being proposed for an IoT, with better security level.

Open-source pulse sequence programs offer an accessible and transparent approach to sequence development and deployment. However, a common framework for testing, documenting, and sharing open-source sequences is still needed to ensure sequence usability and repeatability. We propose and demonstrate such a framework by implementing two sequences, Inversion Recovery Spin Echo (IRSE) and Turbo Spin Echo (TSE), with PyPulseq, and testing them on a commercial 3 T scanner. We used the ACR and ISMRM/NIST phantoms for qualitative imaging and T1/T2 mapping, respectively. The qualitative sequences show good agreement with vendor-provided counterparts (mean Structural Similarity Index Measure (SSIM) = 0.810 for IRSE and 0.826 for TSE). Both sequences passed five out of the seven standard ACR tests, performing at similar levels to vendor counterparts. Compared to reference values, the coefficient of determination R2 was 0.9946 for IRSE T1 mapping and 0.9331 for TSE T2 mapping. All sequences passed the scanner safety check for a 70 kg, 175 cm subject. The framework was demonstrated by packaging the sequences and sharing them on GitHub with data and documentation on the file generation, acquisition, reconstruction, and post-processing steps. The same sequences were tested at a second site using a 1.5 T scanner with the information shared. PDF templates for both sequence developers and users were created and filled.

Purpose Accurate radiation dose is required to ensure reproducibility in establishing the radiobiological effect in biological systems among institutions. The dose should be the most precise and accurate parameter of the entire process. The goal is a system to provide uniform radiation dose verification among institutions that is traceable to the National Institute of Standards and Technology (NIST) through an Accredited Dosimetry Calibration Laboratory. Methods and Materials Radiobiological beams are not NIST traceable but can be approximated based on the radiograph's half value layer. Phantoms have been developed containing detectors to measure the dose from total body irradiation of mice and others. Ionization chambers calibrated to NIST-traceable beams are the best detectors for precise and accurate dose determinations. However, thermoluminescent dosimeters have been mostly used for this application for comparison between institutions. Results A comparison of thermoluminescent dosimeters results among surveyed institutions showed a large variation in delivered dose. The range of radiograph doses that were measured deviated from the standard dose by 12% to 42%. The results have an uncertainty of 2.5% at 1 standard deviation. The surveyed radionuclide irradiators demonstrated a dose range variation of 1.6% to 13.5% from target dose. There is less variation among high energy (linacs) because a calibrated ionization chamber is generally used by personnel (eg, medical physicist) and the output is determined for radiation therapy applications as well. Conclusions Radiobiological dosimetry is lacking with respect to its precision and accuracy. The accuracy of radiograph calibrations for radiobiology can be estimated to be approximately 5%, because there are no NIST-traceable beams. However, among institutions, the variations can be up to 42%. Intercomparisons between institutions is important to have a clear understanding of the transference of dose between given studies.

In recent years, industrial demand for energy harvesting from the indoor environment using photovoltaic (PV) solar cells has grown substantially. Much of this demand is focused on powering Internet of Things devices such as remote sensors and actuators because their power requirements can be easily met by indoor PV cells that convert, otherwise, wasted indoor light energy into low power electricity. However, accurate measurement of PV cells’ indoor performance is challenging because there are currently no broad consensus approaches or standards for doing such measurements. Here, we have taken the first steps toward establishing such a consensus by performing an interlaboratory comparison (ILC) of measurements of a PV solar cell under three distinct low illumination reporting conditions. In this bilateral comparison, each laboratory uses a different technique for reporting the performance parameters of the cell under a fixed set of agreed upon illumination conditions. Our results demonstrate good agreements under some reporting conditions and divergent results under another. Yet, first steps have been taken toward understanding the challenges of establishing a universally acceptable method of measurement.

The DryGASCON scheme was one of authenticated encryption (AE) algorithms submitted to the ongoing NIST Lightweight Cryptography Standardization Process. Such a competition aims to standardize lightweight cryptographic algorithms and determine lightweight AE schemes that are suitable for use in constrained environments suitable for several emerging areas in which highly-constrained devices are interconnected. This article deals with DryGASCON and aims to evaluate its security. The reasons for this choice are twofold. The first reason is related to its unique design. The second one is that no forgery cryptanalysis has been performed on it in the literature to the best of our knowledge. Specifically, this paper presents practical forgery attacks on DryGASCON by exploiting internal collisions of the underlying permutation. During our cryptanalysis, we investigate collisions and discuss how to find them. Next, we mounted forgery attacks on DryGASCON128 with an optimal probability 2− 13 for a class of weak keys and with certainty (optimal probability 1) for pairs of related keys. We show that the number of elements from the weak-key class depends on the size of the secret keys. In addition, we also find forgeries of DryGASCON256 in the related-key scenario. Forgery attacks succeeded without the reuse of nonce. Our results threaten the authenticity and robustness of DryGASCON. However, thanks to our analysis, we shed light on the causes of its weaknesses, and we manage to draw constructive conclusions and recommendations for future AE designs schemes, notably similar to DryGASCON.

To properly respond to ever-growing threats to information security, there is a pressing need for more effective encryption techniques. This paper offers an innovative block-based encryption technique that combines effective random manipulations of a block’s symbols with tricky substitution techniques. Furthermore, the proposed technique offers a block diffusion method in which minor variations to the block’s symbols will magnify and then propagate to the entire block, largely affecting every individual symbol in the block. Experiments with the prototype implementation showed that the output of the proposed encryption technique passed effective randomness tests (NIST and ENT batteries) with a success rate greater than 94%. The simulations of the block diffusion technique showed that it has a high avalanche effect, which greatly boosts the security of the resulting ciphertext.

Purpose For many innovative organisations, Industry 4.0 paves the way for significant operational efficiencies, quality of goods and services and cost reductions. One of the ways to realise these benefits is to embark on digital transformation initiatives that may be summed up as the intelligent interconnectivity of people, processes, data and cyber-connected things. Sadly, this interconnectivity between the enterprise information technology (IT) and industrial control systems (ICS) environment introduces new attack surfaces for critical infrastructure (CI) operators. As a result of the ICS cybersecurity risk introduced by the interconnectivity between the enterprise IT and ICS networks, the purpose of this study is to identify the cybersecurity capabilities that CI operators must have to attain good cybersecurity resilience. Design/methodology/approach A scoping literature review of best practice international CI protection frameworks, standards and guidelines were conducted. Similar cybersecurity practices from these frameworks, standards and guidelines were grouped together under a corresponding National Institute of Standards and Technology (NIST) cybersecurity framework (CF) practice. Practices that could not be categorised under any of the existing NIST CF practices were considered new insights, and therefore, additions. Findings A CI cybersecurity capability framework comprising 29 capability domains (cybersecurity focus areas) was developed as an adaptation of the NIST CF with an added dimension. This added dimension emphasises cloud computing and internet of things (IoT) security. Each of the 29 cybersecurity capability domains is executed through various capabilities (cybersecurity processes and procedures). The study found that each cybersecurity capability can further be operationalised by a set of cybersecurity controls derived from various frameworks, standards and guidelines, such as COBIT®, CIS®, ISA/IEC 62443, ISO/IEC 27002 and NIST Special Publication 800-53. Practical implications CI sectors are immediately able to adopt the CI cybersecurity capability framework to evaluate their levels of resilience against cyber-attacks, given new attack surfaces introduced by the interconnectivity of cyber-connected things between the enterprise and ICS levels. Originality/value The authors present an added dimension to the NIST framework for CI cyber protection. In addition to emphasising cryptography, IoT and cloud computing security aspects, this added dimension highlights the need for an integrated approach to CI cybersecurity resilience instead of a piecemeal approach.

The Supersingular Isogeny Key Encapsulation mechanism (SIKE) is the only post-quantum key encapsulation protocol based on elliptic curves and isogeny maps between them. Despite the quantum security of the protocol, SIKE requires a greater number of clock cycles and hence does not provide competitive timing and energy consumption results. However, it is more attractive offering the smallest public key as well as ciphertext sizes, which considering the impact of the communication costs and storage of the keys could become a good fit for resource-constrained devices. In this work, we present the fastest practical implementation of SIKE, targeting the platform Cortex-M4 based on the ARMv7-M architecture. We performed our measurements on the STM32F407VG microcontroller for benchmarking the clock cycles and on Nucleo-F411RE attached to X-NUCLEO-LPM01A (Power Shield) for measuring the energy consumption of the protocol. The low-level finite field arithmetic operations play main role in determining the efficiency of SIKE. Therefore, we mainly focus on their optimization and apply them to all NIST-required security levels. Our SIKEp434 implementation for NIST security level 1 is about 22.97% faster than the counterparts appeared in Seo et al. (2020), where for the SIKEp503, SIKEp610 and SIKEp751 the speedup reaches 21.10%, 19.21% and 19.08%. Finally, we benchmark energy consumption and report optimization of up to 11.9% depending on the NIST security level implementation.

Physical unclonable function (PUF) is an emerging hardware security primitive which is increasingly used to authenticate and identify Internet of Things (IoT) devices. Spin-transfer torque magnetoresistive random access memory (STT-MRAM) provides new opportunities for novel PUFs due to inherent randomness sources, such as process variations, stochastic switching, and chaotic magnetization. In this article, we propose a hybrid STT-MRAM/complementary metal-oxide semiconductor (CMOS)-based reconfigurable arbiter PUF (MPUF) with enhanced performance metrics in terms of reliability, uniqueness, and uniformity. This design has a mean intra-hamming distance (HD) of 0.147%, a mean inter-HD of 50.21%, and passes the National Institute of Standards and Technology (NIST) statistical tests. The proposed arbiter MPUF features distinct advantages, such as reconfigurable architecture, challenge-dependent stage delays, and huge challenge-response pair (CRP) space. Moreover, the robustness of the proposed MPUF against machine learning (ML)-based modeling attacks is tested using three ML algorithms, namely support vector machine (SVM), linear regression (LR), and multilayer perceptron (MLP). Results show that the proposed reconfigurable arbiter MPUF is resistant to ML attacks and minimizes the ML attack prediction accuracy to less than 65.12% without XOR and less than 44.34% with XOR. Meanwhile, the correlation power analysis demonstrates that the proposed MPUF is also resilient to side-channel attacks.

Recently, National Institute of Standards and Technology (NIST) in the U.S. had initiated a global-scale competition to standardize the lightweight authenticated encryption with associated data (AEAD) and hash function. Gimli is one of the Round 2 candidates that is designed to be efficiently implemented across various platforms, including hardware (VLSI and FPGA), microprocessors, and microcontrollers. However, the performance of Gimli in massively parallel architectures like Graphics Processing Units (GPU) is still unknown. A high performance Gimli implementation on GPU can be especially useful to Internet of Things (IoT) applications, wherein the gateway devices and cloud servers need to handle a massive number of communications protected by AEAD. In this paper, we show that with careful optimization, Gimli can be efficiently implemented in desktop and embedded GPU to achieve extremely high throughput. Our experiments show that the proposed Gimli implementation can achieve 661.44 KB/s (encryption), 892.24 KB/s (decryption), and 4344.46 KB/s (hashing) in state-of-the-art GPUs.

We propose a new lattice-based digital signature scheme \(\textsf {MLWRSign} \) by modifying \(\textsf {Dilithium} \), which is one of the second-round candidates of NIST’s call for post-quantum cryptographic standards. To the best of our knowledge, our scheme MLWRSign is the first signature scheme whose security is based on the (module) learning with rounding (LWR) problem. Due to the simplicity of the LWR, the secret key size is reduced by approximately 30% in our scheme compared to Dilithium, while achieving the same level of security. Moreover, we implemented MLWRSign and observed that the running time of our scheme is comparable to that of Dilithium.

Purpose To determine baseline accuracy and reproducibility of T1 and T2 relaxation times over 12 months on a dedicated radiotherapy MRI scanner. Methods An International Society of Magnetic Resonance in Medicine/National Institute of Standards and Technology (ISMRM/NIST) System Phantom was scanned monthly on a 3T MRI scanner for 1 year. T1 was measured using inversion recovery (T1‐IR) and variable flip angle (T1‐VFA) sequences and T2 was measured using a multi‐echo spin echo (T2‐SE) sequence. For each vial in the phantom, accuracy errors (%bias) were determined by the relative differences in measured T1 and T2 times compared to reference values. Reproducibility was measured by the coefficient of variation (CV) of T1 and T2 measurements across monthly scans. Accuracy and reproducibility were mainly assessed on vials with relaxation times expected to be in physiological ranges at 3T. Results A strong linear correlation between measured and reference relaxation times was found for all sequences tested (R 2 > 0.997). Baseline bias (and CV[%]) for T1‐IR, T1‐VFA and T2‐SE sequences were +2.0% (2.1), +6.5% (4.2), and +8.5% (1.9), respectively. Conclusions The accuracy and reproducibility of T1 and T2 on the scanner were considered sufficient for the sequences tested. No longitudinal trends of variation were deduced, suggesting less frequent measurements are required following the establishment of baselines.

This article examines the verification procedure of coplanar calibration standards based on the calibration comparison technique. For the first time, different commercially available alumina calibration substrates were compared using the NIST multiline TRL calibration procedure, calibration comparison approach, and the NIST GaAs CPW calibration reference material RM8130. The characteristic impedance of the verified calibration line standards is extracted using the multiline TRL procedure and the definition of the load standard resistance. The error circuit, describing difference of the substrate medium and the standard design is extracted. Finally, the worst case error bounds for the measurement of passive devices compared to the reference multiline TRL on the RM8130 are calculated for each tested substrate.

In this article the accuracy of the LRM+ calibration is compared to that of the benchmark NIST multiline TRL procedure for the first time. The comparison is performed on NIST verified GaAs coplanar waveguide calibration reference material 8130. The NIST calibration comparison method is used to quantify the difference between measured S-parameters corrected by NIST multiline TRL and an advanced LRM+ calibration. The worst-case error bounds for LRM+ corrected S-parameter measurements are determined up to 110 GHz. It is demonstrated that the difference between benchmark multiline TRL and LRM+ is comparable with the measurement system drift. Verification results prove that LRM+ can be successfully used for accurate GaAs on-wafer calibration with customized standards. This overcomes some drawbacks of multiline TRL while providing the same calibration accuracy.

This paper will present the results of extracting the electrical characteristics of planar lines using the calibration comparison method for standards realized in IBM's advanced 0.13 µm CMOS process. For the first time, this method is applied to characterizing the customized standards on silicon up to 110 GHz. Additionally, this paper considers the influences of the reference benchmark calibration standards, included with GaAs reference material RM8130, on the characterization accuracy of silicon wafer-embedded lines at mm-wave frequencies.

Detecting the singular point accurately and efficiently is one of the most important tasks for fingerprint recognition. In recent years, deep learning has been gradually used in the fingerprint singular point detection. However, the existing deep learning-based singular point detection methods are either two-stage or multi-stage, which makes them time-consuming. More importantly, their detection accuracy is yet unsatisfactory, especially for the low-quality fingerprint. In this paper, we make a Real One-Stage Effort to detect fingerprint singular points more accurately and efficiently, and therefore, we name the proposed algorithm ROSE for short, in which the multi-scale spatial attention, the Gaussian heatmap and the variant of focal loss are integrated together to achieve a higher detection rate. Experimental results on the datasets FVC2002 DB1 and NIST SD4 show that our ROSE outperforms the state-of-the-art algorithms in terms of detection rate, false alarm rate and detection speed.

Electrically induced ionic motion offers a new way to realize voltage-controlled magnetism, opening the door to a new generation of logic, sensor, and data storage technologies. Here, we demonstrate an effective approach to magneto-ionically and electrically tune exchange bias in Gd/Ni$_{1-x}$Co$_{x}$O thin films (x=0.50, 0.67), where neither of the layers alone is ferromagnetic at room temperature. The Gd capping layer deposited onto antiferromagnetic Ni$_{1-x}$Co$_{x}$O initiates a solid-state redox reaction that reduces an interfacial region of the oxide to ferromagnetic NiCo. Exchange bias is established after field cooling, which can be enhanced by up to 35% after a voltage conditioning and subsequently reset with a second field cooling. These effects are caused by the presence of an interfacial ferromagnetic NiCo layer, which further alloys with the Gd layer upon field cooling and voltage application, as confirmed by electron microscopy and polarized neutron reflectometry studies. These results highlight the viability of the solid-state magneto-ionic approach to achieve electric control of exchange bias, with potentials for energy-efficient magneto-ionic devices., 25 pages, 5 figures; 8 pages of Supporting Information with 5 figures

Infrastructure is an important thing in an organization/company that is used to support activities carried out within the organization. Infrastructure that includes STMIK Rosma, including hardware, software, data, and information, and human resources that support information systems. Hardware resources include PCs that are used for clients with application program software. Windows 10 professional 32 and 64 bit as the operating system. While the software on the server uses Linux OS and PHP programming language. Data and information include infrastructure data, device data, server data and data on staff, students and lecturers at STMIK Rosma. So the need for the sustainability of this system is increasingly important. Problems that have existed in the STMIK Rosma infrastructure, such as those related to information security vulnerabilities. If this problem cannot be fixed in a sustainable manner, it will have an impact or risk on the sustainability of this infrastructure, especially the academic community. This study uses NIST SP 800-30 as the method used to solve these problems. Keywords: Information Security, NIST SP 800-30, Infrastructure, Risk Assessment

It is known, that existing public-key cryptography algorithms based on RSA and elliptic curves provide security guarantees accompanied by complexity. Based on this one can talk about the impossibility to solve problems of integer factorization and discrete logarithm. However, experts predict that the creation of a quantum computer will be able to crack classical cryptographic algorithms. Due to this future problem, the National Institute of Standards and Technologies (NIST), together with leading scientists in the field of cryptography, began an open process of standardizing public-key algorithms for quantum attacks. An important feature of the post-quantum period in cryptography is the significant uncertainty regarding the source data for cryptanalysis and counteraction in terms of the capabilities of quantum computers, their mathematical and software, as well as the application of quantum cryptanalysis to existing cryptotransformations and cryptoprotocols. Mathematical methods of electronic signature (ES) have been chosen as the main methods of NIST USA, which have undergone significant analysis and substantiation in the process of extensive research by cryptographers and mathematicians at the highest level. These methods are described in detail and passed the research at the first stage of the international competition NIST USA PQC. Historically, in 1997, NIST sought public advice to determine the replacement of the data encryption standard (DES), Advanced Encryption Standard (AES). Since then, open cryptographic estimations have become a way of choosing cryptographic standards. For example, NESSIE (2000-2002), eSTREAM (2004-2008), CRYPTREC (2000-2002), SHA-3 (2007-2012) and CAESAR (2013-2019) have adopted this approach. Security was the main parameter in these estimations. Performance in software, performance in application-specific integrated circuits (ASICs), performance in FPGAs, and feasibility with limited resources (small microprocessors and low-power hardware) are secondary criteria. This paper presents the comparison of the hardware of three signature algorithms (qTesla, Crystals-Dilitium, MQDSS), which, in particular, are the candidates for the 2nd round of the NIST PQC competition, and the Crystals-Dilitium algorithm is the finalist of this competition. The objective of this work is to analyze and compare three hardware implementations of candidates for the second round of the NIST PQC contest for an electronic signature algorithm.

In this brief, we present an ultracompact physical unclonable function (PUF) based on the resistive random access memory (RRAM) with the in-cell salicide-blocked (SAB) contact. Different from most previously reported RRAM PUFs with only the RRAM cell’s high-resistance state (HRS) utilized as the static entropy, its low-resistance state (LRS) is enabled with the proposed SAB contact resistance as a novel entropy source. Concretely, by adding a photolithography mask of “SAB” that widely exists in standard CMOS process to the source/drain contact of the mainstream one-transistor-one-resistor (1T1R) RRAM cell’s access transistor, an SAB contact featuring large resistance stochasticity can be formed with zero design overhead of silicon area. With the SAB contact resistance connected in series, both HRS and LRS can be well-exploited to generate much more challenge–response pairs (CRPs), leading to significantly extended CRP space. In addition, the proposed RRAM PUF with in-cell SAB contact is validated using 0.18- $\mu \text{m}$ standard CMOS process plus postprocessing steps for RRAM devices, and the normalized bitcell area is reported to be $77~{F}^{{2}}$ /bit. By varying the operating temperature from −50 °C to 150 °C, the worst case bit error rate (BER) is measured to be 0.13% at 150 °C. Moreover, the excellent randomness of the proposed implementation is verified by passing both the National Institute of Standards and Technology (NIST) test and the autocorrelation function (ACF) test.

Cryptanalysis is the development and study of attacks against cryptographic primitives and protocols. Many cryptographic properties rely on the difficulty of generating an adversary who, given an object sampled from one of two classes, correctly distinguishes the class used to generate that object. In the case of cipher suite distinguishing problem, the classes are two different cryptographic primitives. In this paper, we propose a methodology based on machine learning to automatically generate classifiers that can be used by an adversary to solve any distinguishing problem. We discuss the assumptions, a basic approach for improving the advantage of the adversary as well as a phenomenon that we call the “blind spot paradox”. We apply our methodology to generate distinguishers for the NIST (DRBG) cipher suite problem. Finally, we provide empirical evidence that the distinguishers might statistically have some advantage to distinguish between the DRBG used.

The integrity of wireless networks that make up the clear majority of IoT networks lack the inherent security of their wired counterparts. With the growth of the internet of things (IoT) and its pervasive nature in the modern home environment, it has caused a spike in security concerns over how the network infrastructure handles, transmits, and stores data. New wireless attacks such as KeySniffer and other attacks of this type cannot be tracked by traditional solutions. Therefore, this study investigates if wireless spectrum frequency monitoring using interference analysis tools can aid in the monitoring of device signals within a home IoT network. This could be used enhance the security compliance guidelines set forth by OWASP and NIST for these network types and the devices associated. Active and passive network scanning tools are used to provide analysis of device vulnerability and as comparison for device discovery purposes. The work shows the advantages and disadvantages of this signal pattern testing technique compared to traditional network scanning methods. The authors demonstrate how RF spectrum analysis is an effective way of monitoring network traffic over the air waves but also possesses limitations in that knowledge is needed to decipher these patterns. This article demonstrates alternative methods of interference analysis detection.

This article presents the construction and consumption of hyperjerk system having chaotic nature with the commensurate ordered fractional derivative on rapidly digitalized emerging technologies. The system analyzed analytically using Lipschitz condition and numerically with the help of predictor corrector approaches. Originality of constructed system is confirmed using log error plots which gives satisfactory small values on finite time scale. The dynamical performances of the complex system are termed in multiple phase planes by the mean of their significant nature. Stability and bifurcation analysis around the fractional derivative is also studies for the various parameter of system to check the visibility of chaotic solution. The system is also designed in analog circuit simulator with the aid of operational amplifier, anti-parallel semiconductor diodes for validation of the system. With the help of random number generators (RNGs), binary array generated from the hyperjerk system and plugged in to the NIST 800–22 test suite to measure the randomness. The array having high randomness is used as strong cypher key for the cryptographic execution straightforwardly in both direction encryption and decryption.

In this article, an area-efficient dynamic ring oscillator-based physical unclonable function design utilizing field-programmable gate arrays technology is proposed. An enormous amount of secret keys are generated to securely authenticate advanced metering infrastructure (AMI) nodes throughout their useful lifetime meting National Institute of Science and Technology (NIST) real-time authentication key and security standards. A secure key exchange scheme between a smart meter and utility center is implemented within an AMI network while preserving the privacy and identity of the meter using lightweight encryption. The proposed framework is demonstrated for six different security levels (L0 to L5), which have authentication keys with different length and robustness according to the NIST standards. Experimental results show that our AMI scheme meets the NIST real-time requirements (efficiency) with security levels, L1 and L2, taking, respectively, 6.45 ms and 12.9 ms, which is considerably smaller than the existing techniques.

Fourier transform infrared spectroscopy (FTIR) is a ubiquitous spectroscopic technique. Spectral interpretation is a time-consuming process, but it yields important information about functional groups present in compounds and in complex substances. We develop a generalizable model via a machine learning (ML) algorithm using convolutional neural networks (CNNs) to identify the presence of functional groups in gas-phase FTIR spectra. The ML models reduce the amount of time required to analyze functional groups and facilitate interpretation of FTIR spectra. Through web scraping, we acquire intensity-frequency data from 8728 gas-phase organic molecules within the NIST spectral database and transform the data into spectral images. We successfully train models for 15 of the most common organic functional groups, which we then determine via identification from previously untrained spectra. These models serve to expand the application of FTIR measurements for facile analysis of organic samples. Our approach was done such that we have broad functional group models that infer in tandem to provide full interpretation of a spectrum. We present the first implementation of ML using image-based CNNs for predicting functional groups from a spectroscopic method.

Today, pseudo-random number generators are used in various systems and applications, including as key generators in stream ciphers. The implementation of the latest information and communication technologies (in particular, 5G networks) strengthens the requirements for ensuring the confidentiality of critical data and forces the development of new methods and means for cryptographic protection. Existing generators, like other cryptographic algorithms, do not meet the requirements for processing speed and security against known types of attacks. From this position, in the paper a method for constructing pseudo-random sequence generators was developed. It allows to build efficient generators for cryptographic applications. Based on this method, software generators of pseudo-random numbers have been developed and implemented. These will be useful for cryptographic applications in modern 5G networks. The developed pseudo-random number generators have passed complex statistical testing by the NIST STS technique (showed results not worse than the results of known pseudo-random sequence generators used in practice to solve similar problems). Besides, they are faster in comparison with analogues used today in 5G networks (for example, with algorithms SNOW and Trivium). In further works it is planned to investigate the security of the developed pseudo-random generators against different types of cryptanalytic attacks, as well as to simulate the work of the developed pseudo-random sequence generators using the base station equipment of modern 5G networks.

Building a high precision statistical model requires ample amounts of supervised (labeled) data to train the models. In certain domains, it is difficult to acquire large amounts of labeled data, especially applications involving images, speech and video data. At the same time, lots of unlabeled data is available in such applications. Self-training is one of the semi-supervised approaches that enables the use of vast unlabeled data to boost the efficiency of the model along with minimal labeled data. In this work, we propose a variant of the self-training approach that embraces soft labeling of unlabeled examples rather than the hard labeling used in conventional self-training. As our work focuses on image and speaker recognition tasks, Gaussian Mixture Model (GMM) based Bayesian classifier is used as a wrapper in the self-training approach. Our experimental studies on STL10, CIFAR10, MIT (image recognition task) and NIST (speaker recognition task) benchmark datasets indicate that the proposed modified self-training approach offers enhanced efficiency over conventional self-training.

Rejection sampling technology is a core tool in the design of lattice-based signatures with ‘Fiat–Shamir with Aborts’ structure, and it is related to signing efficiency and signature, size as well as security. In the rejection sampling theorem proposed by Lyubashevsky, the masking vector of rejection sampling is chosen from discrete Gaussian distribution. However, in practical designs, the masking vector is more likely to be chosen from bounded uniform distribution due to better efficiency and simpler implementation. Besides, as one of the third-round candidate signatures in the NIST postquantum cryptography standardization process, the 3rd round version of CRYSTALS-Dilithium has proposed a new method to decrease the rejection probability in order to achieve better efficiency and smaller signature size by decreasing the number of nonzero coefficients of the challenge polynomial according to the security levels. However, it is seen that small entropies in this new method may lead to higher risk of forgery attack compared with former schemes proposed in its 2nd version. Thus, in this paper, we first analyze the complexity of forgery attack for small entropies and then introduce a new method to decrease the rejection probability without loss of security including the security against forgery attack. This method is achieved by introducing a new rejection sampling theorem with tighter bound by utilizing Rényi divergence where masking vector follows uniform distribution. By observing large gaps between the security claim and actual security bound in CRYSTALS-Dilithium, we propose two series of adapted parameters for CRYSTALS-Dilithium. The first set can improve the efficiency of the signing process in CRYSTALS-Dilithium by factors of 61.7 % and 41.7 % , according to the security levels, and ensure the security against known attacks, including forgery attack. And, the second set can reduce the signature size by a factor of 14.09 % with small improvements in efficiency at the same security level.

Mp3 is one form of audio file extension that is widely used today. With a variety of uses in a variety of mp3 systems become one of the audio extensions that are commonly found in technology systems of the Internet of Things era. However, with the many uses of the .mp3 file extension, there is a new problem, namely the security of the data itself. From these problems, the author aims to examine the security of the mp3 file by designing cryptographic science-based applications. The cryptographic algorithm used in the application is a combination of the asymmetric RSA 2048 algorithm and symmetric columnic transpositions. RSA 2048 algorithm was chosen because it has a key length in accordance with NIST standards in securing data. By combining the two algorithms, the application system will have the ability to manage mp3 files and encrypt mp3 files with the results of data that cannot be played like mp3 files in general. This application system will be developed by prototype method which is the best method in developing a system with trial and error in algorithm development. &nbsp, Mp3 merupakan salah satu bentuk ekstensi file audio yang banyak digunakan saat ini. Dengan beragam penggunaan dalam beragam sistem mp3 menjadi salah satu ekstensi audio yang banyak ditemui dalam sistem – sistem teknologi era Internet Of Things. Tetapi, dengan banyaknya kegunaan dari file berekstensi .mp3 terdapat masalah baru yaitu keamanan dari data itu sendiri. Dari permasalahan tersebut, penulis bertujuan untuk meneliti tentang pengamanan dari file mp3 tersebut dengan merancang aplikasi berbasis ilmu kriptografi. Algoritma kriptografi yang digunakan dalam aplikasi tersebut merupakan algoritma kombinasi dari algoritma asimetris RSA 2048 dan simetris transposisi kolumnar. Algoritma RSA 2048 dipilih karena memiliki panjang kunci yang sesuai dengan standar NIST dalam pengamanan suatu data. Dengan menggabungkan kedua algoritma tersebut, sistem aplikasi akan memiliki kemampuan untuk mengelola file mp3 dan mengenkripsi file mp3 dengan hasil data yang tidak dapat di putar layaknya file mp3 pada umumnya. Sistem aplikasi ini akan dikembangan dengan metode prototype yang menjadi metode terbaik dalam mengembangkan sistem dengan trial dan error dalam pengembangan algoritma.

Advancements in quantum computing present a security threat to classical cryptography algorithms. Lattice-based key exchange protocols show strong promise due to their resistance to theoretical quantum-cryptanalysis and low implementation overhead. By contrast, their physical implementations have shown vulnerability against side-channel attacks (SCAs) even with a single power measurement. The state-of-the-art SCAs are, however, limited to simple, sequentialized executions of post-quantum key-exchange (PQKE) protocols, leaving the vulnerability of complex, parallelized architectures unknown. This article proposes 2Deep—a deep-learning (DL)-based SCA—targeting parallelized implementations of PQKE protocols, namely, Frodo and NewHope with data augmentation techniques. Specifically, we explore approaches that convert 1-D time-series power measurement data into 2-D images to formulate SCA an image recognition task. The results show our attack’s superiority over conventional techniques including horizontal differential power analysis (DPA), template attacks (TAs), and straightforward DL approaches. We demonstrate improvements up to $1.5\times $ to recover a 100% success rate compared to DL with 1-D input data while using fewer data. We furthermore show that machine learning improves the results up to $1.25\times $ compared to TAs. Furthermore, we perform cross-device attacks that obtain profiles from a single device, which has never been explored. Our 2-D approach is especially favored in this setting, improving the success rate of attacking Frodo from 20% to 99% compared to the 1-D approach. Our work thus urges countermeasures even on parallel architectures and single-trace attacks.

This paper shows the use of four sets of coefficient values of the 2D chaotic map to generate pseudo-random number generators. We demonstrate that the generated sequences are random by applying NIST suite 800-22-a and TestU01 tests. The generated random sequences are used to implement a stream cipher and are applied to encrypt images. To detect if the images have been modified, we propose to use the random sequences as keys for a hash function based on the pseudo-dot product. This hash can be used as a message authentication code in the images to detect if the stored information has been compromised. The proposed schemes can be used to encrypt and authenticate any digital data not only images. The random sequences generator is probed also in a high-performance microcontroller STM32F746ZG obtaining a throughput of 173.35 Kbit/s.

Cyber threats have been growing tremendously in recent years. There are significant advancements in the threat space that have led towards an essential need for the strengthening of digital infrastructure security. Better security can be achieved by fine-tuning system parameters to the best and optimized security levels. For the protection of infrastructure and information systems, several guidelines have been provided by well-known organizations in the form of cybersecurity standards. Since security vulnerabilities incur a very high degree of financial, reputational, informational, and organizational security compromise, it is imperative that a baseline for standard compliance be established. The selection of security standards and extracting requirements from those standards in an organizational context is a tedious task. This article presents a detailed literature review, a comprehensive analysis of various cybersecurity standards, and statistics of cyber-attacks related to operating systems (OS). In addition to that, an explicit comparison between the frameworks, tools, and software available for OS compliance testing is provided. An in-depth analysis of the most common software solutions ensuring compliance with certain cybersecurity standards is also presented. Finally, based on the cybersecurity standards under consideration, a comprehensive set of minimum requirements is proposed for OS hardening and a few open research challenges are discussed.

This research investigates the strengths and opportunities for improvement of the National Institute of Standards and Technology’s (NIST’s) Baldrige Performance Excellence Program (BPEP) in terms o...

The competition for lightweight cryptography (LWC) launched by the National Institute of Standards and Technology (NIST) is an ongoing project calling for the standardization of lightweight cryptographic algorithms. The Report on Lightweight Cryptography specifically asks that submissions be quantum safe when long-term security is needed. However, this was not included in the “Submission Requirements and Evaluation Criteria for the Lightweight Cryptography Standardization Process.” Consequently, most candidates, including sESTATE and Elephant, make no claim regarding security with respect to quantum attacks. We propose quantum key recovery attacks on those second-round candidates. sESTATE is an authenticated encryption mode inspired by SUNDAE, as proposed in ToSC 2018. It claims that the adversary can get no information regarding the simplified tweakable block cipher. However, we show that quantum adversaries could extract the internal values, leading to a key-recovery attack on the only recommended scheme, sESTATE_TweAES-128-6, with $$2^{42.3}$$ Q2 queries and a time equivalent to $$2^{52}$$ AES encryptions. Technically, the attack is based on the combination of a quantum extracting method and quantum square attack. For Elephant mode, which internally uses a permutation masked by linear feedback shift registers (LFSRs) similar to the masked Even-Mansour construction proposed in EUROCRYPT 2016, we launch the attack based on the quantum attack proposed by Bonnetain et al., which depends on Simon’s algorithm without superposition queries and Grover’s algorithm. Our attack is generic and independent of internal permutation; hence, we obtain the quantum attacks on all instances with a tradeoff of classical and quantum queries. Remarkably, the attack complexities of both recommended instances are lower than that of the generic quantum attack on key, i.e., in time $${\mathcal {O}}({2}^{|K|/{2}})$$ with $${\mathcal {O}}(1)$$ queries.

Improving the reliability of quantification in lipidomic analyses is crucial for its successful application in the discovery of new biomarkers or in clinical practice. In this study, we propose a workflow to improve the accuracy and precision of lipidomic results issued by the laboratory. Lipid species from 11 classes were analyzed by a targeted RPLC-MRM/MS method. The peak areas of species were used to estimate concentrations by an internal standard calibration approach (IS-calibration) and by an alternative normalization signal calibration schema (NS-calibration). The latter uses a long-term reference plasma material as a matrix-matched external calibrator whose accuracy was compared to the NIST SRM-1950 mean consensus values reported by the Interlaboratory Lipidomics Comparison Exercise. The bias of lipid concentrations showed a good accuracy for 69 of 89 quantified lipids. The quantitation of species by the NS-calibration schema improved the within- and between-batch reproducibility in quality control samples, in comparison to the usual IS-calibration approach. Moreover, the NS-calibration workflow improved the robustness of the lipidomics measurements reducing the between-batch variability (relative standard deviation

This paper presents a deep learning-based machine translation (MT) system that translates a sentence of subject-object-verb (SOV) structured language into subject-verb-object (SVO) structured language. This system uses recurrent neural networks (RNNs) and Encodings. Encode embedded RNNs generate a set of numbers from the input sentence, where the second RNNs generate the output from these sets of numbers. Three popular datasets of SOV structured language i.e., EMILLE corpus, Prothom-Alo corpus and Punjabi Monolingual Text Corpus ILCI-II are used as two different case-study to validate. In our experimental case-study 1, for the EMILLE corpus and Prothom-Alo corpus dataset, we have achieved 0.742, 4.11 and 0.18, respectively as Bilingual Evaluation Understudy (BLEU), NIST (metric) and tertiary entrance rank scores. Another case-study for Punjabi Monolingual Text Corpus ILCI-II dataset achieved a BLEU score of 0.75. Our results can be compared with the state-of-the-art results.

Accepted paper for the ACM- Journal on Emerging Technologies in Computing Systems, 2020 [Abstract]The candidates for theNIST Post-Quantum Cryptographystandardization have undergone extensive studies on efficiency and theoretical security, but research on their side-channel security is largely lacking. This remains a considerable obstacle for their real-world deployment, where side-channel security can be a critical requirement. This work describes a side-channel resistant instance ofSaber, one of the lattice-based candidates, using masking as a countermeasure. Saber proves to be very efficient to mask due to two specific design choices: power-of-two moduli, and limited noise sampling of learning with rounding. A major challenge in maskinglattice-based cryptosystemsis the integration of bit-wise operations with arithmetic masking, requiring algorithms to securely convert between masked representations. The described design includes a novel primitive for masked logical shifting on arithmetic shares, as well as adapts an existing masked binomial sampler for Saber. An implementation is provided for an ARM Cortex-M4 microcontroller, and its side-channel resistance is experimentally demonstrated. The masked implementation features a 2.5x overhead factor, significantly lower than the 5.7x previously reported for a masked variant of NewHope. Masked key decapsulation requires less than 3,000,000 cycles on the Cortex-M4 and consumes less than 12kB of dynamic memory, making it suitable for deployment in embedded platforms.

Today, the question of the stability of modern existing cryptographic mechanisms to quantum algorithms of cryptanalysis in particular and quantum computers in general is quite acute. This issue is actively discussed at the international level. Therefore, to solve it, NIST USA has decided to organize and is currently holding a competition for candidates for post-quantum cryptographic algorithms NIST PQC. The result of the competition should be the adoption of various types of cryptographic algorithms for standardization, namely, asymmetric encryption, key encapsulation and electronic signature (at least one algorithm of each type). 82 algorithms were submitted by the start of the competition for the standardization process. Based on the minimum eligibility criteria defined by NIST, 69 algorithms were considered for the 1st round. Given several parameters, namely, security, cost, performance, implementation characteristics, etc., 43 and 11 algorithms were excluded at the end of the 1st and 2nd rounds, respectively, and the other 15 algorithms were left for participation in the 3rd round. The algorithms left in the 2nd round can be divided into 5 different categories depending on their mathematical basis: those based on the isogeny of elliptic curves, those based on algebraic lattices, those based on mathematical code, those based on multivariate transformations and those based on hash functions. Security is the main evaluation criterion that determines competition in the NIST competition, and it is clear that candidates' software implementations are focused mainly on it. However, it is extremely important that the algorithm has an effective hardware implementation. Timely identification of hardware inefficiencies will help focus the cryptographic community efforts on more promising candidates, potentially saving a large amount of time that can be spent on cryptanalysis. This paper discusses and compares the FPGAs of Xilinx family. Data on the implementation of the candidates of the 2nd round in the process of standardization of post-quantum cryptography NIST, which are focused on the FPGA of the Xilinx family, are presented and compared.

As a candidate of the standard of post-quantum cryptography for NIST, Liu, et al. submitted a new public-key encryption scheme Compact-LWE, whose structure is similar to LWE, but with different distribution of errors. They thought that the special error distribution would protect Compact-LWE from known lattice-based attacks. Furthermore, they recommended a set of small parameters to improve the efficiency of Compact-LWE and claimed it can offer 192-bit security. However, in this paper, the authors show that Compact-LWE is not secure under recommended parameters by presenting two ciphertext-only attacks. First, the authors show that the message can be recovered efficiently from the ciphertext. Then the authors go further to recover an equivalent private key efficiently from the public key by exploiting the special structure of Compact-LWE.

The development of digital video technology which is increasingly advanced makes digital video engineering crimes prone to occur. The change in digital video has changed information communication, and it is easy to use in digital crime. One way to solve this digital crime case is to use the NIST (National Institute of Standards and Technology) method for video forensics. The initial stage is carried out by collecting data and carrying out the process of extracting the collected results. A local hash and noise algorithm can then be used to analyze the resulting results, which will detect any digital video interference or manipulation at each video frame, and perform hash analysis to detect the authenticity of the video. In digital video engineering, histogram analysis can be performed by calculating the histogram value metric, which is used to compare the histogram values ​​of the original video and video noise and make graphical comparisons. The results of the difference in frame analysis show that the results of the video show that the 2nd to 7th frames experience an attack while the histogram calculation of the original video centroid value and video tampering results in different values ​​in the third frame, namely with a value of 124.318 and the 7th frame of the video experiencing a difference in the value of 105,966 videos. tampering and 107,456 in the original video. Hash analysis on video tampering results in an invalid SHA-1 hash, this can prove that the video has been manipulated., Perkembangan teknologi video digital yang semakin maju membuat kejahatan rekayasa video digital rawan terjadi. Perubahan video digital membuat informasi yang disampaikan menjadi berubah dan sangat rawan dimanfaatkan menjadi aksi kejahatan digital. Salah satu cara untuk mengatasi kasus kejahatan digital ini adalah dengan menggunakan digital forensik seperti metode NIST (National Institute of Standards and Technology). Tahapan awal yang dilakukan akuisisi data dan melakukan proses ekstraksi hasil akuisisi tersebut. Hasil yang sudah di dapat selanjutnya dianalisis menggunakan algoritma Localization Tampering dan Hashing, algoritma ini untuk mendeteksi adanya perusakan atau manipulasi video digital pada tiap frame dan analisis hash untuk mendeteksi keaslian video. Dalam rekayasa video digital, analisis histogram dapat dilakukan dengan menghitung metrik nilai histogram, yang digunakan untuk membandingkan nilai histogram pada video asli dan video tampering serta membuat perbandingan grafik. Hasil perbedaan analisis frame menunjukan hasil video bahwa frame ke 2 sampai 7 mengalami attack sedangkan pada perhitungan histogram nilai centroid video asli dan video tampering manghasilkan nilai yang berbeda pada frame ke tiga yaitu dengan nilai 124.318 dan frame ke 7 video mengalami perbedaan nilai yaitu sebesar 105.966 video tampering dan 107.456 di video asli. Analisis hash pada video tampering menghasilkan hash SHA-1 tidak valid, hal Ini dapat membuktikan bahwa video tersebut telah dimanipulasi.

Transmission of the information in any form requires security. Security protocols used for communication rely on the use of random numbers. Pseudo-random numbers are required with good statistical properties and efficiency. The use of a single chaotic map may not produce enough randomness. The turbulence is padded into the existing map to improve its chaotic behaviour and increase the periodicity. A Pseudo-random number generator (PRNG) with this architecture is devised to generate random bit sequences from secret keys. The statistical properties of newly constructed PRNG are tested with NIST SP 800–22 statistical test suite and were shown to have good randomness. To ensure its usability in cryptographic applications, we analysed the size of its key space, key sensitivity, and performance speed. The test results show that the newly designed PRNG has a 3.6% increase in key space and a 5% increase in its performance speed compared to existing chaotic PRNGs. The novel PRNG with faster performance is found suitable for lightweight cryptographic applications.

BACKGROUND: Materials characterization made possible by dual energy CT (DECT) scanners is expected to considerably improve automatic detection of hazardous objects in checked and carry-on luggage at our airports. Training a computer to identify the hazardous items from DECT scans however implies training on a baggage dataset that can represent all the possible ways a threat item can packed inside a bag. Practically, however, generating such data is made challenging by the logistics (and the permissions) related to the handling of the hazardous materials. OBJECTIVE: The objective of this study is to present a software simulation pipeline that eliminates the need for a human to handle dangerous materials and that allows for virtually unlimited variability in the placement of such materials in a bag alongside benign materials. METHODS: In this paper, we present our DEBISim software pipeline that carries out an end-to-end simulation of a DECT scanner for virtual bags. The key highlights of DEBISim are: (i) A 3D user-interactive graphics editor for constructing a virtual 3D bag with manual placement of different types of objects in it; (ii) An automated virtual bag generation algorithm for creating randomized baggage datasets; (iii) An ability to spawn deformable sheets and liquid-filled containers in a virtual bag to represent plasticized and liquid explosives; and (iv) A GPU-based X-ray forward modelling block for spiral cone-beam scanners used in checked baggage screening. RESULTS: We have tested our simulator using two standard CT phantoms: the American College of Radiology (ACR) phantom and the NIST security screening phantom as well as on a set of reference materials representing commonly encountered items in checked baggage. For these phantoms, we have assessed the quality of the simulator by comparing the simulated data reconstructions with real CT scans of the same phantoms. The comparison shows that the material-specific properties as well as the CT artifacts in the scans generated by DEBISim are close to those produced by an actual scanner. CONCLUSION: DEBISim is an end-to-end simulation framework for rapidly generating X-ray baggage data for dual energy cone-beam scanners.

Sharing data between organizations is difficult due to different database management systems imposing different schemas as well as security and privacy concerns. We leverage two proven NIST technologies to address the problem: Next Generation Database Access Control and the data block matrix.

Viber is one of the most popular social media in the Instant Messenger application category that can be used to send text messages, make voice calls, send picture messages and video messages to other users. As many as 260 million people around the world have used this application. Increasing the number of viber users certainly brings positive and negative impacts, one of the negative impacts of this application is the use of digital forensic crime. This research simulates and removes digital crime evidence from the viber application on Android smartphones using the National Institute of Standards Technology (NIST) method, which is a method that has work guidelines on forensic policy and process standards to ensure each investigator follows the workflow the same so that their work is documented and the results can be accounted for. This study uses three forensic tools, MOBILedit Forensic Express, Belkasoft and Autopsy. The results in this study show that MOBILedit Forensic Express gets digital evidence with a percentage of 100% in getting accounts, contacts, pictures and videos. While proof of digital chat is only 50%. Belkasoft gets digital evidence with a percentage of 100% in getting accounts, contacts, pictures and videos. While proof of digital chat is only 50%. For Autopsy does not give the expected results in the extraction process, in other words the Autopsy application gives zero results. It can be concluded that MOBILedit Forensic Express and Belkasoft have a good performance compared to Autopsy and thus this research has been completed and succeeded in accordance with the expected goals., Viber merupakan salah satu media sosial yang popular untuk kategori aplikasi Instant Messenger yang dapat digunakan untuk mengirim pesan teks, melakukan panggilan suara, mengirim pesan gambar dan pesan berupa video kepada sesama penggunanya. Sebanyak 260 juta orang di seluruh dunia telah menggunakan aplikasi ini. Peningkatan jumlah pengguna viber tentu membawa dampak positif dan juga negatif, salah satu dampak negative aplikasi ini adalah penggunaan dalam hal melakukan kejahatan forensik digital. Penelitian ini melakukan simulasi dan pengangkatan barang bukti kejahatan digital dari aplikasi viber pada smartphone Android dengan menggunakan metode National Institute of Standards Technology (NIST) yang merupakan salah satu metode yang memiliki panduan kerja pada kebijakan dan standar proses forensik untuk menjamin setiap investigator mengikuti alur kerja yang sama sehingga pekerjaan mereka terdokumentasikan dan hasilnya dapat dipertanggung jawabkan. Penelitian ini menggunakan tiga alat forensik, MOBILedit Forensic Express, Belkasoft dan Autopsy. Hasil dalam penelitian ini menujukan bahwa MOBILedit Forensic Express mendapatkan hasil bukti digital dengan persentase berupa 100% dalam mendapatkan akun, kontak, gambar dan video. Sedangkan bukti digital chat hanya 50%. Belkasoft mendapatkan hasil bukti digital dengan persentase 100% dalam mendapatkan akun, kontak, gambar dan video. Sedangkan bukti digital chat hanya 50%. Untuk Autopsy tidak memberikan hasil yang diharapkan dalam poses ekstraksi, dengan kata lain aplikasi Autopsy memberikan hasil nol (zero result). Dapat disimpulkan bahwa MOBILedit Forensic Express dan Belkasoft memiliki kinerja yang baik dibandingkan dengan Autopsy dan dengan demikian penelitian ini telah selesai dan berhasil sesuai dengan tujuan yang diharapkan.

Digital information is any type of data that is stored electronically. These data need to protect its assets and unauthorized access to it and therefore need measures to protect digital privacy. This process is done in different ways, one of which is encryption. Encryption provides secure transfer of unauthorized data over insecure channels. In this paper a method is proposed to create the keys to the El Gamal PKC algorithm based on chaos theory. The proposed algorithm uses 3D chaos maps to create keys used in the encryption and decryption process using an El Gamal algorithm. The time spent encoding and decoding in milliseconds was calculated and compared with methods that used 1D and 2D chaotic maps. Also, the results obtained exceeded most of the statistical and NIST tests. The generated results are tested their reactions against many types of attacks. Then, the results showed that the proposed method had an excellent randomness efficiency for creating public and private keys for El Gamal's algorithm.

The concept of IOT (Internet of Things) prevalent in the era, an enormous increase in the implementation of low resource devices with limited resources to implement various arithmetic primitives for cryptographic applications. Most of the National Institute of Standards and Technology NIST approved conventional security algorithms like the IDEA, RSA etc. involve simple operations like addition, multiplication and complex operations like addition-modulo, multiplication-modulo etc. such algorithms may not be routed to the low resource devices. Even though the NIST approved algorithms may be fitted into the low resource devices their erformance may be a concern. An extensive research has been carried out on designing the cryptographic arithmetic structures over the years, the arithmetic modules have been implemented using different design styles, logic, algorithms and aspects. In this paper the reversible logic and Vedic mathematics have been combined to implement efficient cryptographic arithmetic primitives. A considerable amount of improvement in the performance parameters like Area, power dissipation and delay have been analyzed by the implementation and synthesis.

The strategically acquired gradient echo (STAGE) protocol, developed for 3T scanners, allows one to derive quantitative maps such as T1, T2*, proton density, and quantitative susceptibility mapping in about 5 min. Our aim was to adapt the STAGE sequences for 1.5T scanners which are still commonly used in clinical practice. Furthermore, the accuracy and repeatability of the STAGE-derived T1 estimate were tested. Flip angle (FA) optimization was performed using a theoretical simulation by maximizing signal-to-noise ratio, contrast-to-noise ratio, and T1 precision. The FA choice was further refined with the ISMRM/NIST phantom and in vivo acquisitions. The accuracy of the T1 estimate was assessed by comparing STAGE-derived T1 values with T1 maps obtained with an inversion recovery sequence. T1 accuracy was investigated for both the phantom and in vivo data. Finally, one subject was acquired 10 times once a week and a group of 27 subjects was scanned once. The T1 coefficient of variation (COV) was computed to assess scan-rescan and physiological variability, respectively. The FA1,2 = 7°,38° were identified as the optimal FA pair at 1.5T. The T1 estimate errors were below 3% and 5% for phantom and in vivo measurements, respectively. COV for different tissues ranged from 1.8 to 4.8% for physiological variability, and between 0.8 and 2% for scan-rescan repeatability. The optimized STAGE protocol can provide accurate and repeatable T1 mapping along with other qualitative images and quantitative maps in about 7 min on 1.5T scanners. This study provides the groundwork to assess the role of STAGE in clinical settings. • The STAGE imaging protocol was optimized for use on 1.5T field strength scanners. • A practical STAGE protocol makes it possible to derive quantitative maps (i.e., T1, T2*, PD, and QSM) in about 7 min at 1.5T. • The T1 estimate derived from the STAGE protocol showed good accuracy and repeatability.

Grain-128AEAD is a lightweight authenticated encryption stream cipher and one of the finalists in the National Institute of Standards and Technology (NIST) Lightweight Cryptography (LWC) project. This paper provides an independent third-party analysis of Grain-128AEAD against fault attacks. We investigate the application of three differential fault attack models on Grain-128AEAD. All these attacks can recover the initial state of Grain-128AEAD. First, we demonstrate an attack using a bit-flipping fault that requires access to 27.80 faulty outputs to recover the initial state. Then, we demonstrate an attack with a more relaxed assumption of a random fault with a probabilistic approach. Our probabilistic random fault attack requires access to 211.60 faulty outputs and 210.45 fault injections to recover the initial state with a success rate over 99%. Both of the above two attacks are based on precise control on the fault target. Finally, we apply a random fault attack with a deterministic approach (can conclusively determine the random fault value) and using different precision controls. For the precise control, we use existing approaches that have been applied to other ciphers, such as Tiaoxin-346. We also propose a technique for less stringent precision models, such as moderate control and no control, which are more practical than the precise control. Our result indicates that the deterministic random fault attack with a precise control requires an average of 27.64 fault injections and a data complexity of 28.80. The deterministic random fault attack with moderate control requires a weak assumption on the fault injection and hence, is the best attack presented in this paper; and is expected to require about 29.39 fault injections with a data complexity of about 212.98. All the attacks discussed in this paper are verified experimentally.

All cryptography systems have a True Random Number Generator (TRNG). In the process of validating, these systems are necessary for prototyping in Field Programmable Gate Array (FPGA). However, TRNG uses an entropy source based on non-deterministic effects challenging to replicate in FPGA. This work shows the problems and solutions to implement an entropy source based on frequency collapse in multimodal Ring Oscillators (RO). The entropy source implemented in FPGA pass all SP800-90B tests from the National Institute of Standards and Technology (NIST) with a good entropy compared to related works. The TRNG passes all NIST SP800-22 with and without the post-processing stage. Besides, the TRNG and the post-processing stage pass all tests of Application notes and Interpretation of the Scheme (AIS31). The TRNG implementation on a Xilinx Artix-7 XC7A100TCSG324 FPGA occupies less than 1% of the resources. This work presents $0.62~\mu \text{s}$ up to $9.92~\mu \text{s}$ of sampling latency and 1.1 Mbps up to 9.1 Mbps of bit rate throughput.