Relevant bibliographies by topics / White-box Analysis

Academic literature on the topic 'White-box Analysis'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "White-box Analysis"

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Chitic, Raluca, Ali Osman Topal, and Franck Leprévost. "Empirical Perturbation Analysis of Two Adversarial Attacks: Black Box versus White Box." Applied Sciences 12, no. 14 (July 21, 2022): 7339. http://dx.doi.org/10.3390/app12147339.

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Through the addition of humanly imperceptible noise to an image classified as belonging to a category ca, targeted adversarial attacks can lead convolutional neural networks (CNNs) to classify a modified image as belonging to any predefined target class ct≠ca. To achieve a better understanding of the inner workings of adversarial attacks, this study analyzes the adversarial images created by two completely opposite attacks against 10 ImageNet-trained CNNs. A total of 2×437 adversarial images are created by EAtarget,C, a black-box evolutionary algorithm (EA), and by the basic iterative method (BIM), a white-box, gradient-based attack. We inspect and compare these two sets of adversarial images from different perspectives: the behavior of CNNs at smaller image regions, the image noise frequency, the adversarial image transferability, the image texture change, and penultimate CNN layer activations. We find that texture change is a side effect rather than a means for the attacks and that ct-relevant features only build up significantly from image regions of size 56×56 onwards. In the penultimate CNN layers, both attacks increase the activation of units that are positively related to ct and units that are negatively related to ca. In contrast to EAtarget,C’s white noise nature, BIM predominantly introduces low-frequency noise. BIM affects the original ca features more than EAtarget,C, thus producing slightly more transferable adversarial images. However, the transferability with both attacks is low, since the attacks’ ct-related information is specific to the output layers of the targeted CNN. We find that the adversarial images are actually more transferable at regions with sizes of 56×56 than at full scale.
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Pintelas, Emmanuel, Ioannis E. Livieris, and Panagiotis Pintelas. "A Grey-Box Ensemble Model Exploiting Black-Box Accuracy and White-Box Intrinsic Interpretability." Algorithms 13, no. 1 (January 5, 2020): 17. http://dx.doi.org/10.3390/a13010017.

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Machine learning has emerged as a key factor in many technological and scientific advances and applications. Much research has been devoted to developing high performance machine learning models, which are able to make very accurate predictions and decisions on a wide range of applications. Nevertheless, we still seek to understand and explain how these models work and make decisions. Explainability and interpretability in machine learning is a significant issue, since in most of real-world problems it is considered essential to understand and explain the model’s prediction mechanism in order to trust it and make decisions on critical issues. In this study, we developed a Grey-Box model based on semi-supervised methodology utilizing a self-training framework. The main objective of this work is the development of a both interpretable and accurate machine learning model, although this is a complex and challenging task. The proposed model was evaluated on a variety of real world datasets from the crucial application domains of education, finance and medicine. Our results demonstrate the efficiency of the proposed model performing comparable to a Black-Box and considerably outperforming single White-Box models, while at the same time remains as interpretable as a White-Box model.
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Velez, Miguel, Pooyan Jamshidi, Florian Sattler, Norbert Siegmund, Sven Apel, and Christian Kästner. "ConfigCrusher: towards white-box performance analysis for configurable systems." Automated Software Engineering 27, no. 3-4 (August 5, 2020): 265–300. http://dx.doi.org/10.1007/s10515-020-00273-8.

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Pang, Siyu, Tingting Lin, Xuejia Lai, and Zheng Gong. "A White-Box Implementation of IDEA." Symmetry 13, no. 6 (June 15, 2021): 1066. http://dx.doi.org/10.3390/sym13061066.

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IDEA is a classic symmetric encryption algorithm proposed in 1991 and widely used in many applications. However, there is little research into white-box IDEA. In traditional white-box implementations of existing block ciphers, S-boxes are always converted into encoded lookup tables. However, the algebraic operations of IDEA without S-boxes, make the implementation not straight forward and challenging. We propose a white-box implementation of IDEA by applying a splitting symmetric encryption method, and verify its security against algebraic analysis and BGE-like attacks. Our white-box implementation requires an average of about 2800 ms to encrypt a 64-bit plaintext, about 60 times more than the original algorithm would take, which is acceptable for practical applications. Its storage requirements are only about 10 MB. To our knowledge, this is the first public white-box IDEA solution, and its design by splitting can be applied to similar algebraic encryption structures.
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Hasan, Md Moudud, Md Shariot Ullah, Ajoy Kumar Saha, and MG Mostofa Amin. "Comparing the performances of multiple rainfall-runoff models of a karst watershed." Asian-Australasian Journal of Bioscience and Biotechnology 6, no. 1 (July 18, 2021): 26–39. http://dx.doi.org/10.3329/aajbb.v6i1.54878.

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Different modeling concepts, a simple (black-box) to a fully distributed modeling (white-box), were used to develop a rainfall-runoff model based on the watershed characteristics to estimate runoff at the watershed outlet. A conceptual (grey-box) model is usually a balance between the black-box and white-box model. In this study, three grey-box models were developed by varying model structures for a karst watershed. The performance of the grey-box models was evaluated and compared with a semi-distributed type (white-box) model that was developed using the Soil and Water Assessment Tool in a previous study. The evaluation was carried out using goodness-of-fit statistics and extreme flow analysis using WETSPRO (Water Engineering Time Series Processing tool). Nash-Sutcliffe efficiencies (NSE) of the grey-box models were from 0.39 to 0.77 in the calibration period and from 0.30 to 0.61 in the validation period. However, the white-box model performed better in terms of NSE but has a higher bias. The best grey-box model performed better in simulating extreme flow, whereas the white-box (SWAT) model adequately simulated daily flows. Asian Australas. J. Biosci. Biotechnol. 2021, 6 (1), 26-39
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LEE, Seungkwang. "A White-Box Cryptographic Implementation for Protecting against Power Analysis." IEICE Transactions on Information and Systems E101.D, no. 1 (2018): 249–52. http://dx.doi.org/10.1587/transinf.2017edl8186.

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Grujicic, M., V. Chenna, R. Galgalikar, J. S. Snipes, S. Ramaswami, and R. Yavari. "Computational analysis of gear-box roller-bearing white-etch cracking." International Journal of Structural Integrity 5, no. 4 (November 11, 2014): 290–327. http://dx.doi.org/10.1108/ijsi-10-2013-0028.

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Purpose – A simple economic analysis has revealed that in order for wind energy to be a viable alternative, wind-turbines (convertors of wind energy into electrical energy) must be able to operate for at least 20 years, with only regular maintenance. However, wind-turbines built nowadays do not generally possess this level of reliability and durability. Specifically, due to the malfunction and failure of drive-trains/gear-boxes, many wind-turbines require major repairs after only three to five years in service. The paper aims to discuss these issues. Design/methodology/approach – The subject of the present work is the so-called white etch cracking, one of the key processes responsible for the premature failure of gear-box roller-bearings. To address this problem, a multi-physics computational methodology is developed and used to analyze the problem of wind-turbine gear-box roller-bearing premature-failure. The main components of the proposed methodology include the analyses of: first, hydrogen dissolution and the accompanying grain-boundary embrittlement phenomena; second, hydrogen diffusion from the crack-wake into the adjacent unfractured material; third, the inter-granular fracture processes; and fourth, the kinematic and structural response of the bearing under service-loading conditions. Findings – The results obtained clearly revealed the operation of the white-etch cracking phenomenon in wind-turbine gear-box roller-bearings and its dependence on the attendant loading and environmental conditions. Originality/value – The present work attempts to make a contribution to the resolution of an important problem related to premature-failure and inferior reliability of wind-turbine gearboxes.
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Zhang, Chao, and Yu Wang. "Research on the Structure of Authentication Protocol Analysis Based on MSCs/Promela." Advanced Materials Research 989-994 (July 2014): 4698–703. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4698.

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To discover the existing or possibly existing vulnerability of present authentication protocol, we proposed a structure of authentication protocol analysis, which consist of white box analysis, black box analysis and indicator system as the three main functional components. White box analysis makes use of the transformation from MSCs (Message Sequence Charts) to Promela (Process Meta Language), the input language of the remarkable model checker SPIN; black box analysis is based on the attack platform of authentication protocol analysis; indicator system is decided by deducibility restraint methods. Compared with the UML modeling methods based on Promela, the MSC2Promela methods we figured out on the context have more advantages than its disadvantages. Finally, we proposed a structure of authentication protocol analysis based on the transformation from MSC2Promela, which makes sense to the later work on the area of authentication protocol analysis.
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KRISHNA MOHAN, K., A. K. VERMA, A. SRIVIDYA, and LJUBISA PAPIC. "INTEGRATION OF BLACK-BOX AND WHITE-BOX MODELING APPROACHES FOR SOFTWARE RELIABILITY ESTIMATION." International Journal of Reliability, Quality and Safety Engineering 17, no. 03 (June 2010): 261–73. http://dx.doi.org/10.1142/s0218539310003792.

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Quality of a software product should be tracked during the software lifecycle right from the architectural phase to its operational phase. Heterogeneous systems consist of several globally distributed components, thus rendering their reliability evaluation more complex with respect to the conventional methods. The objective of our work is to expand the evaluation process for effective reliability analysis by using both white box and black box approaches at prototype and at module/component level before the actual development. In this paper the, Black box testing is based on non-functional requirements for early quantitative analysis for the reliability estimation of the application development based on the output results of the prototype development. White box testing is based on inter-component interactions which deal with probabilistic software behavior. It uses an internal perspective of the system to design test cases based on internal structure at requirements and design phases. This paper has been applied for evolution of effective reliability quantification analysis at prototype level of a financial application case study with both non functional test data of software Development Life cycle (SDLC) phases captured from defect consolidation table in the form orthogonal defect classification as well functional requirements at requirement and design phases captured through software architectural modeling paradigms.
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Xie, Li, Jiang Yu, Shuang Li, and Sha Sha Diao. "Analysis of Volatile Organic Compounds in Disposable Food Packages at Three types of Temperature." Advanced Materials Research 476-478 (February 2012): 2625–29. http://dx.doi.org/10.4028/www.scientific.net/amr.476-478.2625.

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Eight volatile organic compounds (VOCs) in the four disposable food packages at refrigeration temperature, room temperature and heating temperature have been analyzed by a headspace gas chromatography and mass spectrometry method. The results of external standard method show that the amount of VOCs in the four disposable packages at different temperatures are arranged in the following order: black plastic lunch box, white plastic lunch box, paper cup, paper bowl. Under the three types of temperature for an hour, the amount of VOCs in the black plastic lunch box at heating temperatures is higher (1.2382 mg/m2at 90 °C), room temperature has smaller content (0.6682 mg/m2and 0.9105 mg/m2at 20 °C and 30 °C, repectively). Content of VOCs in the white plastic lunch box increases gradually with temperature rising.
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Dissertations / Theses on the topic "White-box Analysis"

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Truong, Nghi Khue Dinh. "A web-based programming environment for novice programmers." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16471/1/Nghi_Truong_Thesis.pdf.

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Learning to program is acknowledged to be difficult; programming is a complex intellectual activity and cannot be learnt without practice. Research has shown that first year IT students presently struggle with setting up compilers, learning how to use a programming editor and understanding abstract programming concepts. Large introductory class sizes pose a great challenge for instructors in providing timely, individualised feedback and guidance for students when they do their practice. This research investigates the problems and identifies solutions. An interactive and constructive web-based programming environment is designed to help beginning students learn to program in high-level, object-oriented programming languages such as Java and C#. The environment eliminates common starting hurdles for novice programmers and gives them the opportunity to successfully produce working programs at the earliest stage of their study. The environment allows students to undertake programming exercises anytime, anywhere, by "filling in the gaps" of a partial computer program presented in a web page, and enables them to receive guidance in getting their programs to compile and run. Feedback on quality and correctness is provided through a program analysis framework. Students learn by doing, receiving feedback and reflecting - all through the web. A key novel aspect of the environment is its capability in supporting small "fill in the gap" programming exercises. This type of exercise places a stronger emphasis on developing students' reading and code comprehension skills than the traditional approach of writing a complete program from scratch. It allows students to concentrate on critical dimensions of the problem to be solved and reduces the complexity of writing programs.
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Truong, Nghi Khue Dinh. "A web-based programming environment for novice programmers." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16471/.

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Learning to program is acknowledged to be difficult; programming is a complex intellectual activity and cannot be learnt without practice. Research has shown that first year IT students presently struggle with setting up compilers, learning how to use a programming editor and understanding abstract programming concepts. Large introductory class sizes pose a great challenge for instructors in providing timely, individualised feedback and guidance for students when they do their practice. This research investigates the problems and identifies solutions. An interactive and constructive web-based programming environment is designed to help beginning students learn to program in high-level, object-oriented programming languages such as Java and C#. The environment eliminates common starting hurdles for novice programmers and gives them the opportunity to successfully produce working programs at the earliest stage of their study. The environment allows students to undertake programming exercises anytime, anywhere, by "filling in the gaps" of a partial computer program presented in a web page, and enables them to receive guidance in getting their programs to compile and run. Feedback on quality and correctness is provided through a program analysis framework. Students learn by doing, receiving feedback and reflecting - all through the web. A key novel aspect of the environment is its capability in supporting small "fill in the gap" programming exercises. This type of exercise places a stronger emphasis on developing students' reading and code comprehension skills than the traditional approach of writing a complete program from scratch. It allows students to concentrate on critical dimensions of the problem to be solved and reduces the complexity of writing programs.
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Harston, Walter Andrew. "Facies and Reservoir Characterization of the Permian White Rim Sandstone, Black Box Dolomite, and Black Dragon Member of the Triassic Moenkopi Formation for CO2 Storage and Sequestration at Woodside Field, East-Central Utah." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/3567.

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Geologic sequestration of anthropogenic carbon dioxide (CO2) greenhouse gas emissions is an engineering solution that potentially reduces CO2 emissions released into the atmosphere thereby limiting their effect on climate change. This study focuses on Woodside field as a potential storage and sequestration site for CO2 emissions. The Woodside field is positioned on a doubly plunging, asymmetrical anticline on the northeast flank of the San Rafael Swell. Particular focus will be placed on the Permian White Rim Sandstone, Black Box Dolomite and Black Dragon Member of the Triassic Moenkopi Formation as the reservoir/seal system to store and sequester CO2 at Woodside field. The White Rim Sandstone, the primary target reservoir, is divided into three stratigraphic intervals based on facies analysis: a lower sand sheet facies (about 60 ft or 18 m), a thick middle eolian sandstone facies (about 390 ft or 119 m), and an upper marine reworked facies (about 70 ft or 21 m). Porosity and permeability analyses from the outcrop indicate good reservoir quality in the eolian sandstone and reworked facies. Porosity in the White Rim Sandstone ranges from 7.6 to 24.1% and permeability reaches up to 2.1 D. The maximum combined thickness of the three facies is 525 ft (160 m) at Woodside field providing a significant volume of porous and permeable rock in which to store CO2. The Black Box Dolomite is the secondary potential reservoir for CO2 storage at Woodside field and has a gross thickness up to 76 ft (23 m). The Black Box Dolomite is divided into four lithofacies: a basal nodular dolomudstone (8.2 -15 ft or 3.5-4.5 m), a dolowackestone (25-37 ft or 7.5-11 m), a dolomitic sandstone (0-8.2 ft or 0-2.5 m), and an upper sandy dolowackestone (0-16 ft or 0-4.9 m). Porosity and permeability analyses indicate reservoir potential in the dolowackestone, dolomitic sandstone, and sandy dolowackestone lithofacies. Porosity in the Black Box Dolomite ranges from 6.6 to 29.2% and permeability reaches up to 358 mD. The nodular dolomudstone lithofacies has relatively poor reservoir quality with porosity up to 9.4% and permeability up to 0.182 mD. This lithofacies could act as a baffle or barrier to fluid communication between the White Rim Sandstone and Black Box Dolomite. The Black Dragon Member of the Triassic Moenkopi Formation will serve as the seal rock for the relatively buoyant CO2 stored in the underlying formations. The Black Dragon Member is comprised of four lithofacies: a chert pebble conglomerate; an interbedded sandstone, siltstone, and shale; a trough cross-stratified sandstone, and an oolitic and algal limestone. The Black Dragon Member has a maximum thickness of 280 ft (85 m) at Woodside field. Mudstone beds contain from 0.16 to 0.47% porosity. QEMSCAN analysis indicates several minerals within shale beds that may react with a CO2-rich brine including calcite (18.73 to 23.43%), dolomite (7.56 to 7.89%), alkali feldspar (4.12 to 4.43 %), glauconite (0.04 to 0.05%), and plagioclase (0.03 to 0.04%). Silty mudstones comprise 75% of this member at Black Dragon Canyon. Volumetric estimates for Woodside field were calculated based on the 10th, 50th, and 90th percent probabilities (P10, P50, and P90). The White Rim Sandstone is the primary target reservoir and has capacity to hold 2.2, 8.8, or 23.7 million metric tonnes (P10, P50, and P90 respectively) of CO2 within the structural closure of Woodside field. The Black Box Dolomite may hold 0.5, 1.8, or 4.5 million metric tonnes, respectively of additional CO2 within the structural closure of Woodside field. These two formations combined have the capacity to store up to 28.3 million metric tonnes (P90) of CO2.
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Shao, Danhua. "Application of local semantic analysis in fault prediction and detection." Thesis, 2010. http://hdl.handle.net/2152/ETD-UT-2010-05-1086.

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To improve quality of software systems, change-based fault prediction and scope-bounded checking have been used to predict or detect faults during software development. In fault prediction, changes to program source code, such as added lines or deleted lines, are used to predict potential faults. In fault detection, scope-bounded checking of programs is an effective technique for finding subtle faults. The central idea is to check all program executions up to a given bound. The technique takes two basic forms: scope-bounded static checking, where all bounded executions of a program are transformed into a formula that represents the violation of a correctness property and any solution to the formula represents a counterexample; or scope-bounded testing where a program is tested against all (small) inputs up to a given bound on the input size. Although the accuracies of change-based fault prediction and scope-bounded checking have been evaluated with experiments, both of them have effectiveness and efficiency limitations. Previous change-based fault predictions only consider the code modified by a change while ignoring the code impacted by a change. Scope-bounded testing only concerns the correctness specifications, and the internal structure of a program is ignored. Although scope-bounded static checking considers the internal structure of programs, formulae translated from structurally complex programs might choke the backend analyzer and fail to give a result within a reasonable time. To improve effectiveness and efficiency of these approaches, we introduce local semantic analysis into change-based fault prediction and scope-bounded checking. We use data-flow analysis to disclose internal dependencies within a program. Based on these dependencies, we identify code segments impacted by a change and apply fault prediction metrics on impacted code. Empirical studies with real data showed that semantic analysis is effective and efficient in predicting faults in large-size changes or short-interval changes. While generating inputs for scope-bounded testing, we use control-flow to guide test generation so that code coverage can be achieved with minimal tests. To increase the scalability of scope-bounded checking, we split a bounded program into smaller sub-programs according to data-flow and control-flow analysis. Thus the problem of scope-bounded checking for the given program reduces to several sub-problems, where each sub-problem requires the constraint solver to check a less complex formula, thereby likely reducing the solver’s overall workload. Experimental results show that our approach provides significant speed-ups over the traditional approach.
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Fattal, Feras. "High frequency model for transient analysis of transformer windings using multiconductor transmission line theory." 2017. http://hdl.handle.net/1993/32172.

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Transients encountered by transformers in power stations during normal operation can have complex oscillatory overvoltages containing a large spectrum of frequency components. These transients can coincide with the natural frequencies of the transformers windings, leading to voltages that can be greater or more severe than the current factory proof tests. This may lead to insulation breakdown and catastrophic failures. Existing lumped parameter RLCG transformer models have been proven to be less accurate for very fast transient overvoltages (VFTO) with frequencies over 1 MHz. A white box model for transient analysis of transformer windings has been developed using Multiconductor Transmission Line (MTL) Theory. This model enables the simulation of natural frequencies of the transformer windings up to frequencies of several MHz, and can be used to compute voltages between turns by representing each turn as a separate transmission line. Both continuous and interleaved disk windings have been modelled and a comparison and validation of the results is presented.
May 2017
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Filipe, Ricardo Ângelo Santos. "Client-Side Monitoring of Distributed Systems." Doctoral thesis, 2020. http://hdl.handle.net/10316/91181.

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Tese no âmbito do Programa de Doutoramento em Ciências e Tecnologias da Informação apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra
From critical systems to entertainment, most computer systems have become distributed. Compared to standalone applications, distributed systems are more complex, dificult to operate and maintain, thus increasing the probability for outages or other malfunctions. Properly monitoring the system is therefore even more important. However, recovering a complete image of the system is a herculean task for administrators, who often need to resort to a large plethora of tools. Despite all these tools, the person that many times identifies the degradation or the system outage is the one that is somehow disregarded in the monitoring chain - the client. Almost daily, we have examples in the news from companies that had outages or system degradation perceived by the final client with a direct impact on the companies' revenues and image. The lack of client-side monitoring and the opportunity to improve current monitoring mechanisms paved the way for the key research question in this thesis. We argue that the client has information on the distributed system that monitoring applications should use to improve performance and resilience. In this work, we aim to evaluate the limits of black-box client-side monitoring and to extend white-box with client information. Additionally, we are very interested to understand what kind of information does the system leak to the client. To evaluate this approach, we resorted to several experiments in distinct scenarios from three-tier web sites to microservice architectures, where we tried to identify performance issues from the client-side point-of-view. We used client profiling, machine learning techniques among other methods, to demonstrate that using client information may serve to improve the observability of a distributed system. Properly including client-side information proved to be an interesting and challenging research effort. We believe that our work contributed to advance the current state-ofart in distributed system monitoring. The client has viable information that eludes administrators and provides important insights on the system.
Desde os sistemas críticos ao entretenimento, a maioria dos sistemas computacionais tornou-se distribuída. Quando comparados a aplicações monolíticas, os sistemas distribu ídos são mais complexos, difíceis de operar e manter, aumentando assim a probabilidade de anomalias. A monitoria de um sistema distribuído é desta forma ainda mais importante. Todavia, obter uma imagem completa do sistema é uma tarefa árdua para os administradores, que frequentemente precisam de recorrer a uma grande variedade de ferramentas. Mesmo com a superabundância de ferramentas, a pessoa que muitas vezes identi ca a degradação ou a interrupção do sistema é a mesma que de alguma forma é desconsiderada no uxo de monitoria: o cliente. Quase diariamente, temos exemplos na comunicação social de empresas que tiveram interrupções ou degradação no serviço prestado percebido pelo cliente nal, com impacto direto nas receitas e na imagem dessas empresas. A falta de monitoria do ponto de vista do cliente e a oportunidade de melhorar a monitoria atual abriram o caminho para a questão chave de pesquisa nesta tese. Argumentamos que o cliente possui informação sobre o sistema distribuído que as ferramentas de monitora devem usar para melhorar o desempenho e resiliência. Neste trabalho pretendemos avaliar os limites de uma monitoria do lado do cliente de uma forma caixa-negra , e extender as soluções de caixa-branca com informação do cliente. Além disso, estamos também interessados em entender que tipo de informação é que o sistema escapa para o cliente. Para avaliar esta abordagem, recorremos a várias experiências em cenários distintos desde sites de três camadas até arquiteturas de micro serviços, onde tentamos identi- car problemas do ponto de vista do cliente. Usámos técnicas de criação de pro ling do ponto de vista do cliente, técnicas de Machine Learning, entre outros métodos, para demonstrar que o uso de informações do cliente pode servir para melhorar a observabilidade de um sistema distribuído. A inclusão de informações do cliente provou ser um tópico de pesquisa interessante e desa ador. Acreditamos que o nosso trabalho contribuiu para avançar o atual estado da arte de monitoria em sistemas distribuídos. O cliente possui informações viáveis que escapam ao controlo dos administradores e fornece conhecimento importante sobre o sistema.
Altice Labs
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Books on the topic "White-box Analysis"

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McCleary, Richard, David McDowall, and Bradley J. Bartos. Noise Modeling. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190661557.003.0003.

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Chapter 3 introduces the Box-Jenkins AutoRegressive Integrated Moving Average (ARIMA) noise modeling strategy. The strategy begins with a test of the Normality assumption using a Kolomogov-Smirnov (KS) statistic. Non-Normal time series are transformed with a Box-Cox procedure is applied. A tentative ARIMA noise model is then identified from a sample AutoCorrelation function (ACF). If the sample ACF identifies a nonstationary model, the time series is differenced. Integer orders p and q of the underlying autoregressive and moving average structures are then identified from the ACF and partial autocorrelation function (PACF). Parameters of the tentative ARIMA noise model are estimated with maximum likelihood methods. If the estimates lie within the stationary-invertible bounds and are statistically significant, the residuals of the tentative model are diagnosed to determine whether the model’s residuals are not different than white noise. If the tentative model’s residuals satisfy this assumption, the statistically adequate model is accepted. Otherwise, the identification-estimation-diagnosis ARIMA noise model-building strategy continues iteratively until it yields a statistically adequate model. The Box-Jenkins ARIMA noise modeling strategy is illustrated with detailed analyses of twelve time series. The example analyses include non-Normal time series, stationary white noise, autoregressive and moving average time series, nonstationary time series, and seasonal time series. The time series models built in Chapter 3 are re-introduced in later chapters. Chapter 3 concludes with a discussion and demonstration of auxiliary modeling procedures that are not part of the Box-Jenkins strategy. These auxiliary procedures include the use of information criteria to compare models, unit root tests of stationarity, and co-integration.
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Book chapters on the topic "White-box Analysis"

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Formal, Thibault, Benjamin Piwowarski, and Stéphane Clinchant. "A White Box Analysis of ColBERT." In Lecture Notes in Computer Science, 257–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72240-1_23.

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Dottax, Emmanuelle, Christophe Giraud, and Agathe Houzelot. "White-Box ECDSA: Challenges and Existing Solutions." In Constructive Side-Channel Analysis and Secure Design, 184–201. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89915-8_9.

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Zeyad, Mohamed, Houssem Maghrebi, Davide Alessio, and Boris Batteux. "Another Look on Bucketing Attack to Defeat White-Box Implementations." In Constructive Side-Channel Analysis and Secure Design, 99–117. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16350-1_7.

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Klemsa, Jakub, and Martin Novotný. "Exploiting Linearity in White-Box AES with Differential Computation Analysis." In Advances in Intelligent Systems and Computing, 404–19. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52243-8_29.

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Baranová, Zuzana, and Petr Ročkai. "Compiling C and C++ Programs for Dynamic White-Box Analysis." In Lecture Notes in Computer Science, 30–45. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54994-7_4.

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Bos, Joppe W., Charles Hubain, Wil Michiels, and Philippe Teuwen. "Differential Computation Analysis: Hiding Your White-Box Designs is Not Enough." In Lecture Notes in Computer Science, 215–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-53140-2_11.

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Ha, Trung, Tran Khanh Dang, and Nhan Nguyen-Tan. "Comprehensive Analysis of Privacy in Black-Box and White-Box Inference Attacks Against Generative Adversarial Network." In Future Data and Security Engineering, 323–37. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91387-8_21.

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Alpirez Bock, Estuardo, and Alexander Treff. "Security Assessment of White-Box Design Submissions of the CHES 2017 CTF Challenge." In Constructive Side-Channel Analysis and Secure Design, 123–46. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68773-1_7.

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Tang, Yufeng, Zheng Gong, Tao Sun, Jinhai Chen, and Fan Zhang. "Adaptive Side-Channel Analysis Model and Its Applications to White-Box Block Cipher Implementations." In Information Security and Cryptology, 399–417. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88323-2_22.

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Bharath Kumar, D. P., Nanda Kumar, Snofy D. Dunston, and V. Mary Anita Rajam. "Analysis of the Impact of White Box Adversarial Attacks in ResNet While Classifying Retinal Fundus Images." In IFIP Advances in Information and Communication Technology, 162–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16364-7_13.

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Conference papers on the topic "White-box Analysis"

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Liu, Zechao, Xuan Wang, Lei Cui, Zoe L. Jiang, and Chunkai Zhang. "White-box traceable dynamic attribute based encryption." In 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2017. http://dx.doi.org/10.1109/spac.2017.8304334.

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Luo, Rui, Xuejia Lai, and Rong You. "A new attempt of white-box AES implementation." In 2014 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2014. http://dx.doi.org/10.1109/spac.2014.6982727.

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Zhang, Lingfeng, Yueling Zhang, and Min Zhang. "Efficient white-box fairness testing through gradient search." In ISSTA '21: 30th ACM SIGSOFT International Symposium on Software Testing and Analysis. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3460319.3464820.

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Fraser, Gordon, Matt Staats, Phil McMinn, Andrea Arcuri, and Frank Padberg. "Does automated white-box test generation really help software testers?" In ISSTA '13: Iitsnternational Symposium on Software Testing and Analysis. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2483760.2483774.

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Balasubramaniam, Jayalakshmi, and Philip W. L. Fong. "A white-box policy analysis and its efficient implementation." In the 18th ACM symposium. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2462410.2462416.

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Li, Bo, and Lichen Zhang. "Analysis of white box test of cyber-physical system." In MATERIALS SCIENCE, ENERGY TECHNOLOGY, AND POWER ENGINEERING I: 1st International Conference on Materials Science, Energy Technology, Power Engineering (MEP 2017). Author(s), 2017. http://dx.doi.org/10.1063/1.4982548.

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Reiter, Sebastian, Alexander Viehl, Oliver Bringmann, and Wolfgang Rosenstiel. "White-Box Error Effect Simulation for Assisted Safety Analysis." In 2015 Euromicro Conference on Digital System Design (DSD). IEEE, 2015. http://dx.doi.org/10.1109/dsd.2015.83.

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Zhang, Zhiqiang, Tianyong Wu, and Jian Zhang. "Boundary value analysis in automatic white-box test generation." In 2015 IEEE 26th International Symposium on Software Reliability Engineering (ISSRE). IEEE, 2015. http://dx.doi.org/10.1109/issre.2015.7381817.

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Shan, Songqing, and G. Gary Wang. "Turning Black-Box Into White Functions." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28958.

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Abstract:
Modeling of high dimensional expensive black-box (HEB) functions is challenging. A recently developed method, radial basis function-based high dimensional model representation (RBF-HDMR), has been found promising. This work extends RBF-HDMR to enhance its modeling capability beyond the current second order form and “uncover” black-box functions so that not only a more accurate metamodel is obtained, but also key information of the function can be gained and thus the black-box function can be turned “white.” The key information that can be gained includes 1) functional form, 2) (non)linearity with respect to each variable, 3) variable correlations. The resultant model can be used for applications such as sensitivity analysis, visualization, and optimization. The RBF-HDMR exploration is based on identifying the existence of certain variable correlations through derived theorems. The adaptive process of exploration and modeling reveals the black-box functions till all significant variable correlations are found. The black-box functional form is then represented by a structure matrix that can manifest all orders of correlated behavior of variables. The proposed approach is tested with theoretical and practical examples. The test result demonstrates the effectiveness and efficiency of the proposed approach.
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Viehl, A., M. Pressler, O. Bringmann, and W. Rosenstiel. "White box performance analysis considering static non-preemptive software scheduling." In 2009 Design, Automation & Test in Europe Conference & Exhibition (DATE'09). IEEE, 2009. http://dx.doi.org/10.1109/date.2009.5090718.

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