Verification Tools Research Articles

Deep learning methods for 2D in-vivo dose reconstruction with EPID detector

Over the past two decades, radiotherapy has seen a steep increase in technological complexity of treatment preparation and treatment execution, calling for the development of more and better quality assurance tools and procedures. In-vivo dosimetry has emerged as a very powerful tool for treatment verification in conjunction with Electronic Portal Imaging Devices (EPIDs). However, EPIDs present several drawbacks like non-water equivalence and cumbersome calibration procedures. Artificial intelligence, specifically Deep Learning (DL), plays a crucial role in this context. A critical step is modeling the EPID response to estimate 2D dose distributions (Portal Dose, PD). This work introduces a DL-based methodology aimed at converting EPID responses into PD images. The proposed procedure is fully data driven, being based on advanced DL methods. This approach will allow bypassing the complex calibration steps needed to overcome the non-water equivalent panel.

The Design of the Dummy Arm: A Verification Tool for Arm Exoskeleton Development.

Motorised arm supports for individuals with severe arm muscle weakness require precise compensation for arm weight and elevated passive joint impedance (e.g., joint stiffness as a result of muscle atrophy and fibrosis). Estimating these parameters in vivo, along with the arm's centre of mass, is challenging, and human evaluations of assistance can be subjective. To address this, a dummy arm was designed to replicate the human arm's anthropometrics, degrees of freedom, adjustable segment masses, and passive elbow joint impedance (eJimp). This study presents the design, anthropometrics, and verification of the dummy arm. It successfully mimics the human arm's range of motion, mass, and centre of mass. The dummy arm also demonstrates the ability to replicate various eJimp torque-angle profiles. Additionally, it allows for the tuning of the segment masses, centres of mass, and eJimp to match a representative desired target population. This simple, cost-effective tool has proven valuable for the development and verification of the Duchenne ARm ORthosis (DAROR), a motorised arm support, or 'exoskeleton'. This study includes recommendations for practical applications and provides insights into optimising design specifications based on the final design. It supplements the CAD design, enhancing the dummy arm's application for future arm-assistive devices.

A comprehensive survey of UPPAAL‐assisted formal modeling and verification

AbstractUPPAAL is a formal modeling and verification tool based on timed automata, capable of effectively analyzing real‐time software and hardware systems. In this article, we investigate research on UPPAAL‐assisted formal modeling and verification. First, we propose four research questions considering tool characteristics, modeling methods, verification means and application domains. Then, the state‐of‐the‐art methods for model specification and verification in UPPAAL are discussed, involving model transformation, model repair, property specification, as well as verification and testing methods. Next, typical application cases of formal modeling and verification assisted by UPPAAL are analyzed, spanning across domains such as network protocol, multi‐agent system, cyber‐physical system, rail traffic and aerospace systems, cloud and edge computing systems, as well as biological and medical systems. Finally, we address the four proposed questions based on our survey and outline future research directions. By responding to these questions, we aim to provide summaries and insights into potential avenues for further exploration in this field.

Closing the Gap: Leakage Contracts for Processors with Transitions and Glitches

Security verification of masked software implementations of cryptographic algorithms must account for microarchitectural side-effects of CPUs. Leakage contracts were proposed to provide a formal separation between hardware and software verification, ensuring interoperability and end-to-end security for independently verified components. However, previously proposed leakage contracts did not consider a class of ephemeral hardware effects called glitches, which leaves a considerable gap between security models and the capabilities of real-world attackers. We address this issue by extending the model for leakage contracts to account for glitches and transitions. We further present the first end-to-end verification tool for transient leakage contracts. Our hardware and software verification rely on the same contract as a single source of truth, facilitating fully machine-checked verification from the hardware gate level to the software. By allowing contracts to be written in the C programming language we make power contracts more accessible and intuitive for system-level engineers. To showcase the efficacy of our approach, we apply it to the RISC-V Ibex core. We show that it is possible to write a power contract for Ibex without any modifications to the hardware design. Using this contract, we prove end-to-end security between masked software and gate-level hardware.

Pharmacy Compounding Regulation in the German Pharmaceutical Market. Part 2. Organisational Features (Review)

INTRODUCTION. The Russian Federation has decided to restore the system of compounding pharmacies as an element of the critical national healthcare infrastructure and pharmaceutical supply chain. To improve Russian regulatory practices, develop novel advanced approaches to pharmacy compounding and quality control, and implement these approaches, it is necessary to study relevant good compounding practices applied in healthcare systems of other countries.AIM. The study aimed to analyse the German experience in the organisation and regulation of pharmaceutical compounding to suggest recommendations for the development and implementation of Russian guidelines on good compounding and dispensing practices.DISCUSSION. This work continues a comprehensive study that delves into the current provisions of German legislation governing the system of good compounding practices. This article examines the differences between approaches to compounding by medical and pharmaceutical specialists. According to the findings, compounding by medical specialists is guided by the “free practice of medicine” principle and is subject to minimal regulatory oversight. All pharmacy organisations operate as compounding pharmacies, thereby enhancing the physical accessibility of compounded medicinal products to the population. The authors highlight the features of a process-based quality assurance system encompassing production process controls and quality control methods for compounded medicinal products. Additionally, the authors discuss the applicability of rapid test methods to compounding. In accordance with the German concept of good pharmacy practices, a compounding pharmacy may use the available validation, qualification, and verification tools in the pharmaceutical development of compounded medicinal products and may outsource its internal quality control function. Using the concept of risk ranking, compounding pharmacies may design their own sampling programmes. The article describes approaches to and requirements for organising the evaluation of compounding prescriptions. In Germany, compounding pharmacies may independently assign shelf lives to the compounded medicinal products they produce.CONCLUSIONS. Some German solutions are of considerable practical importance and are applicable to the development and implementation of Russian guidelines on good compounding and dispensing practices. In particular, pharmacy organisations may outsource the quality control of their compounded medicinal products. Additionally, pharmacies can conduct the full-scale pharmaceutical development of compounding technologies and quality control methods (including rapid test methods) using the validation, qualification, and verification tools available to drug manufacturers. Moreover, pharmacy organisations may independently assign shelf lives to the compounded medicinal products they produce. Finally, pharmacy organisations may design their individual sampling programmes.

Review on high spatial resolution dosimetry with pixelated semiconductor detectors for radiation therapy

Current and emerging radiation therapy treatment techniques are characterized by complex and spatially non-uniform dose distributions with steep dose gradients delivered through high-precision dose placement with small radiation fields. Such approaches necessitate advanced verification tools. For accurate dose profile representation in stereotactic radiation therapy using megavoltage X-rays, the Nyquist theorem places the minimum sampling step as 2.5 mm that determines the required spatial resolution of the detectors for dose verification. For techniques such as micro- and mini-beam radiotherapy, micron-scale sampling is required, and sub-millimeter for particle therapy. Silicon semiconductor detectors provide the possibility of producing small sensitive volumes (including in arrays) without compromising mechanical robustness or sensitivity, therefore allowing for high spatial resolution dosimetry. They exhibit many properties of an ideal detector, while the properties of silicon detectors known to negatively influence response can be compensated for and minimized. As such, this work reviews the current status of semiconductor radiation detectors providing dose sampling by diodes with submillimeter sensitive volumes and a pitch of 2.5 mm or smaller for relative dosimetry in X-ray and electron external beam radiation therapy, brachytherapy, microbeam radiation therapy, proton, and heavy ion therapy. The following types of devices are discussed in this work, including commercial systems and those under development: one-dimensional and two-dimensional pixelated arrays (monolithic and single diode based).

Understanding and Combating Misinformation: An Evolutionary Perspective.

Misinformation represents an evolutionary paradox: despite its harmful impact on society, it persists and evolves, thriving in the information-rich environment of the digital age. This paradox challenges the conventional expectation that detrimental entities should diminish over time. The persistence of misinformation, despite advancements in fact-checking and verification tools, suggests that it possesses adaptive qualities that enable it to survive and propagate. This paper explores how misinformation, as a blend of truth and fiction, continues to resonate with audiences. The role of narratives in human history, particularly in the evolution of Homo narrans, underscores the enduring influence of storytelling on cultural and social cohesion. Despite the increasing ability of individuals to verify the accuracy of sources, misinformation remains a significant challenge, often spreading rapidly through digital platforms. Current behavioral research tends to treat misinformation as completely irrrational, static, finite entities that can be definitively debunked, overlooking their dynamic and evolving nature. This approach limits our understanding of the behavioral and societal factors driving the transformation of misinformation over time. The persistence of misinformation can be attributed to several factors, including its role in fostering social cohesion, its perceived short-term benefits, and its use in strategic deception. Techniques such as extrapolation, intrapolation, deformation, cherry-picking, and fabrication contribute to the production and spread of misinformation. Understanding these processes and the evolutionary advantages they confer is crucial for developing effective strategies to counter misinformation. By promoting transparency, critical thinking, and accurate information, society can begin to address the root causes of misinformation and create a more resilient information environment.

Food profiling goes green: Sustainable analysis strategies for food authentication.

Omics technologies, such as genomics, proteomics, metabolomics, isotopolomics, and metallomics, are important tools for analytical verification of food authenticity. However, in many cases, their application requires the use of high-resolution technological platforms as well as careful consideration of sample collection, storage, preparation and, in particular, extraction. In this overview, the individual steps and disciplines are explained against the background of the term "Green Chemistry," and the various instrumental procedures for the respective omics disciplines are discussed. Furthermore, new approaches and developments are presented on how such analyses can be made sustainable in the future.

The Multilateral Integration of Blockchain, Ethical Packet Sniffing and AI for Cybersecurity in BRICS Countries

This policy brief proposes that the BRICS (Brazil, Russia, India and South Africa) should plan and coordinate on ways to mitigate cybersecurity risks on a multilateral level. The BRICS countries are ideal for such a meta-governance mechanism which could coordinate toward the circumvention of some cyber risks. This Policy brief proposes that there should be an integration of blockchain technologies, packet sniffing technologies and AI detection tools to help mitigate emerging cybersecurity risks. The policy brief outlines the risks and challenges prevalent in this current climate, whilst also proposing potential remedies sourced from rigorous academic studies. The precise amendments include the synthesised mechanism of blockchain-based internet registries, packet sniffing technologies AI verification tools and capacity building to aid in the mitigation of cybersecurity risks. In 2007, a cyber-attack in Brazil plunged more than 3 million people into darkness. Cyberattacks collectively cost the BRICS countries $50.3bn in 2013. These funds could have been reinvested into the economy. BRICS needs the rapid technological integration of cyber-crime mitigation tools, tools which this policy brief will outline.

The Role of QR Code Technology in Revolutionizing Banking

The financial services industry has undergone a significant digital revolution, with QR code technology playing a crucial role in the development of the banking sector. Evolving from basic barcodes, QR codes have become essential tools for identity verification, secure online transactions, and financial account management. They represent a shift from conventional banking practices, offering enhanced security and user convenience. In banking, QR codes are used for account management, payments, and robust security protocols. The widespread adoption of QR codes has transformed how customers interact with banks and has led to stronger security measures for online banking. This article examines the growing use of QR codes in banking, highlighting the convenience, security, and improved customer experience these codes offer. The increasing importance of QR technology in banking is further demonstrated by emerging trends such as Data Matrix QR Codes, Blockchain-Enabled QR Codes, Secure Timestamping, Encryption, and Dynamic QR Codes.

Formal analysis of an AUTOSAR-based basic software module

The widespread use of advanced driver assistance systems in modern vehicles, together with their integration with the Internet and other road nodes, has made vehicle more vulnerable to cyber-attacks. To address these risks, the automotive industry is increasingly focusing on the development of security solutions: formal methods and software verification techniques, which have been successfully applied to a number of safety-critical systems, could be a promising approach in the automotive area. In this work, we concentrate on in-vehicle communications, provided by many Electronic Control Units (ECUs) that work together thanks to serial protocols such as Controller Area Network (CAN). However, increasing connectivity exposes the internal network to a variety of cyber-risks. Our aim is to formally verify the AUTOSAR-based Basic Software module called CINNAMON, designed to ensure confidentiality, integrity, and authentication at the same time for traffic exchanged over CAN protocol. More precisely, it adds confidentiality guarantees to the Secure Onboard Communication (SecOC) module. We formally analyze CINNAMON with the verification tool Tamarin. Our analysis shows that CINNAMON could be an effective security solution, as it can ensure the desired properties, in particular, confidentiality in a send-receive scenario between two ECUs. Finally, we describe a potential application scenario.

Facial recognition - A literature review

This paper analyses the main technologies for face recognition, a critical biometric tool for identity verification and security across various sectors. A comprehensive overview of traditional and modern facial recognition technologies will be provided, examining their key features such as age, pose, and illumination. The study discusses the evolution and current state of facial recognition, highlighting significant advancements and applications in recent years. The objective is to offer a detailed understanding of how these technologies function and their implications for security and identity verification.

Technical note: An automated document verification tool in radiation oncology EMR: Application for LDR prostate brachytherapy.

This study aims to illustrate how a script-based automated tool can efficiently verify documentation for LDR prostate brachytherapy. An in-house Python-scripts-based tool was developed to automatically verify the specific checklists, aligned with our institutional practice guidelines for prostate seed implants (PSI). The scripts, compatible with our radiation oncology information system, could be executed with an optional web-based middleware to access and evaluate Aria documents. Optimized based on data from the previous 400 patients, the automated tool was applied to a random cohort of 50 LDR patients. It evaluated the adequacy of specific EMR documents by performing checks for data completeness, consistency, and allowable value range. We analyzed the efficiency of using this tool against conventional manual checks in two LDR processes: seed ordering and monthly audits for our PSI programs. The automated tool effectively performed chart checks on the involved PSI documents. Human errors, such as typos and inconsistent information, were identified in 7 out of 50 patients during the seed ordering process and in 2 out of 50 patients during the monthly audit. Meanwhile, this automation reduced the majority of manual chart-checking time by an average of 5 and 10 min per patient for these processes, respectively. The anticipated efficiency gains will continue to accrue as more check items are digitalized and assessable to the scripts. The implementation of an automated tool tailored for LDR prostate brachytherapy has demonstrated its efficiency benefits. Such an approach can help other clinics substantially enhance routine chart checks, periodic audits, and other applications in similar clinical settings.

A Quantum-Resistant Identity Authentication and Key Agreement Scheme for UAV Networks Based on Kyber Algorithm

Unmanned aerial vehicles (UAVs) play a critical role in various fields, including logistics, agriculture, and rescue operations. Effective identity authentication and key agreement schemes are vital for UAV networks to combat threats. Current schemes often employ algorithms like elliptic curve cryptography (ECC) and Rivest–Shamir–Adleman (RSA), which are vulnerable to quantum attacks. To address this issue, we propose LIGKYX, a novel scheme combining the quantum-resistant Kyber algorithm with the hash-based message authentication code (HMAC) for enhanced security and efficiency. This scheme enables the mutual authentication between UAVs and ground stations and supports secure session key establishment protocols. Additionally, it facilitates robust authentication and key agreement among UAVs through control stations, addressing the critical challenge of quantum-resistant security in UAV networks. The proposed LIGKYX scheme operates based on the Kyber algorithm and elliptic curve Diffie–Hellman (ECDH) key exchange protocol, employing the HMAC and pre-computation techniques. Furthermore, a formal verification tool validated the security of LIGKYX under the Dolev–Yao threat model. Comparative analyses on security properties, communication overhead, and computational overhead indicate that LIGKYX not only matches or exceeds existing schemes but also uniquely counters quantum attacks effectively, ensuring the security of UAV communication networks with a lower time overhead for authentication and communication.

HCFAIUN: A novel hyperelliptic curve and fuzzy extractor-based authentication for secure data transmission in IoT-based UAV networks

IoT-based UAV networks comprise interconnected UAVs outfitted with sensors and microcontrollers to simplify data exchange in environments such as smart cities. In light of open-access communication landscapes, IoT-based UAV networks could pose security challenges, encompassing authentication vulnerabilities and the inadvertent disclosure of location and other confidential information to unauthorised parties. Henceforth, we have proposed a lightweight and secure authentication protocol: Hyperelliptic Curve and Fuzzy Extractor based Authentication in IoT-based UAV networks (HCFAIUN) leveraging Hyperelliptic Curve Cryptography(HCC), Fuzzy Extractor (FE), XOR operations and hash functions. HCC's maximum key size is 80 bits, differing from the 160-bit requirement of the elliptic curve, making it apt for UAVs with limited resources. The proposed scheme utilises biometrics traits of users to avoid exposing data from stealing smart devices using FE. This protocol facilitates the mutual authentication of users and UAVs, allowing them to exchange a session key for secure communication. The Hyperelliptic Curve (HC) scalar multiplication protects the user's private key from attackers, even in public channels. The obfuscation identity of the user and UAVs generated through the hash function and timestamp makes the external user and UAV anonymous. The efficacy of this proposed framework is examined using the Scyther verification tool and Random oracle model-based formal analysis, and informal analysis is also discussed, which validates its robustness against well-known potential physical and logical attacks. The performance analysis shows that the HCFAIUN scheme has lower computation, communication, and storage costs, i.e., 3.832 ms and 1456 bits and 1128 bits, respectively, compared to existing schemes.

The application of Verilog in the development of casual games

Verilog is a hardware description language (HDL) that is widely used in digital circuit design and simulation. Its development is closely related to computer science and electrical engineering. Verilog gained popularity in the early 1980s as digital circuit designs became increasingly complex, requiring more efficient circuit design and verification tools. At the same time, rapid advances in computer hardware also stimulated the demand for digital circuit design languages. Furthermore, the popularity and adoption of Verilog highlight the growing necessity for digitisation, automation, and intelligence in modern society. As digital technology continues to advance across various industries, the need for effective and dependable digital circuit design languages is also increasing. This paper delves into the complex process of recreating the timeless arcade classic Pac-Man on the Spartan 3E FPGA platform using hardware description and digital circuit techniques and the Verilog programming language. Through a comprehensive review of existing literature and research, this study investigates the fusion of traditional game design principles with state-of-the-art hardware programming methods, demonstrating the seamless integration of software-driven game mechanics with hardware-based implementation. Through careful design and coding strategies, Pac-Man's basic functionality, such as maze traversal, ghost AI, and pellet consumption, is faithfully replicated using Verilog modules customized for the Spartan 3E FPGA board. By bridging the realms of game development and hardware engineering, this paper not only showcases the versatility of Field Programmable Gate Array (FPGA) technology in entertainment applications but also underscores the interdisciplinary nature of modern computing endeavours.

Small field measurements using electronic portal imaging device

Purpose/Objective. Small-field measurement poses challenges. Although many high-resolution detectors are commercially available, the EPID for small-field dosimetry remains underexplored. This study aimed to evaluate the performance of EPID for small-field measurements and to derive tailored correction factors for precise small-field dosimetry verification. Material/Methods. Six high-resolution radiation detectors, including W2 and W1 plastic scintillators, Edge-detector, microSilicon, microDiamond and EPID were utilized. The output factors, depth doses and profiles, were measured for various beam energies (6 MV-FF, 6 MV-FFF, 10 MV-FF, and 10 MV-FFF) and field sizes (10 × 10 cm2, 5 × 5 cm2, 4 × 4 cm2, 3 × 3 cm2, 2 × 2 cm2, 1 × 1 cm2, 0.5 × 0.5 cm2) using a Varian Truebeam linear accelerator. During measurements, acrylic plates of appropriate depth were placed on the EPID, while a 3D water tank was used with five-point detectors. EPID measured data were compared with W2 plastic scintillator and measurements from other high-resolution detectors. The analysis included percentage deviations in output factors, differences in percentage for PDD and for the profiles, FWHM, maximum difference in the flat region, penumbra, and 1D gamma were analyzed. The output factor and depth dose ratios were fitted using exponential functions and fractional polynomial fitting in STATA 16.2, with W2 scintillator as reference, and corresponding formulae were obtained. The established correction factors were validated using two Truebeam machines. Results. When comparing EPID and W2-PSD across all field-sizes and energies, the deviation for output factors ranged from 1% to 15%. Depth doses, the percentage difference beyond dmax ranged from 1% to 19%. For profiles, maximum of 4% was observed in the 100%–80% region. The correction factor formulae were validated with two independent EPIDs and closely matched within 3%. Conclusion. EPID can effectively serve as small-field dosimetry verification tool with appropriate correction factors.

Harnessing Neuron Stability to Improve DNN Verification

Deep Neural Networks (DNN) have emerged as an effective approach to tackling real-world problems. However, like human-written software, DNNs are susceptible to bugs and attacks. This has generated significant interest in developing effective and scalable DNN verification techniques and tools. Recent developments in DNN verification have highlighted the potential of constraint-solving approaches that combine abstraction techniques with SAT solving. Abstraction approaches are effective at precisely encoding neuron behavior when it is linear, but they lead to overapproximation and combinatorial scaling when behavior is non-linear. SAT approaches in DNN verification have incorporated standard DPLL techniques, but have overlooked important optimizations found in modern SAT solvers that help them scale on industrial benchmarks. In this paper, we present VeriStable, a novel extension of the recently proposed DPLL-based constraint DNN verification approach. VeriStable leverages the insight that while neuron behavior may be non-linear across the entire DNN input space, at intermediate states computed during verification many neurons may be constrained to have linear behavior – these neurons are stable. Efficiently detecting stable neurons reduces combinatorial complexity without compromising the precision of abstractions. Moreover, the structure of clauses arising in DNN verification problems shares important characteristics with industrial SAT benchmarks. We adapt and incorporate multi-threading and restart optimizations targeting those characteristics to further optimize DPLL-based DNN verification. We evaluate the effectiveness of VeriStable across a range of challenging benchmarks including fully- connected feedforward networks (FNNs), convolutional neural networks (CNNs) and residual networks (ResNets) applied to the standard MNIST and CIFAR datasets. Preliminary results show that VeriStable is competitive and outperforms state-of-the-art DNN verification tools, including α-β-CROWN and MN-BaB, the first and second performers of the VNN-COMP, respectively.

Evaluation of AI content generation tools for verification of academic integrity in higher education

Evaluation of AI content generation tools for verification of academic integrity in higher education

Towards AI-Assisted Synthesis of Verified Dafny Methods

Large language models show great promise in many domains, including programming. A promise is easy to make but hard to keep, and language models often fail to keep their promises, generating erroneous code. A promising avenue to keep models honest is to incorporate formal verification: generating programs’ specifications as well as code so that the code can be proved correct with respect to the specifications. Unfortunately, existing large language models show a severe lack of proficiency in verified programming. In this paper, we demonstrate how to improve two pretrained models’ proficiency in the Dafny verification-aware language. Using 178 problems from the MBPP dataset, we prompt two contemporary models (GPT-4 and PaLM-2) to synthesize Dafny methods. We use three different types of prompts: a direct Contextless prompt; a Signature prompt that includes a method signature and test cases, and a Chain of Thought (CoT) prompt that decomposes the problem into steps and includes retrieval augmentation generated example problems and solutions. Our results show that GPT-4 performs better than PaLM-2 on these tasks and that both models perform best with the retrieval augmentation generated CoT prompt. GPT-4 was able to generate verified, human-evaluated, Dafny methods for 58% of the problems, however, GPT-4 managed only 19% of the problems with the Contextless prompt, and even fewer (10%) for the Signature prompt. We are thus able to contribute 153 verified Dafny solutions to MBPP problems, 50 that we wrote manually, and 103 synthesized by GPT-4. Our results demonstrate that the benefits of formal program verification are now within reach of code generating large language models. Likewise, program verification systems can benefit from large language models, whether to synthesize code wholesale, to generate specifications, or to act as a "programmer’s verification apprentice", to construct annotations such as loop invariants which are hard for programmers to write or verification tools to find. Finally, we expect that the approach we have pioneered here — generating candidate solutions that are subsequently formally checked for correctness — should transfer to other domains (e.g., legal arguments, transport signaling, structural engineering) where solutions must be correct, where that correctness must be demonstrated, explained and understood by designers and end-users.