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Добірка наукової літератури з теми "Adversarial Defence"

Автор: Grafiati

Опубліковано: 10 березня 2023

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Статті в журналах з теми "Adversarial Defence"

Jiang, Guoteng, Zhuang Qian, Qiu-Feng Wang, Yan Wei, and Kaizhu Huang. "Adversarial Attack and Defence on Handwritten Chinese Character Recognition." Journal of Physics: Conference Series 2278, no. 1 (May 1, 2022): 012023. http://dx.doi.org/10.1088/1742-6596/2278/1/012023.

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Abstract Deep Neural Networks (DNNs) have shown their powerful performance in classification; however, the robustness issue of DNNs has arisen as one primary concern, e.g., adversarial attack. So far as we know, there is not any reported work about the adversarial attack on handwritten Chinese character recognition (HCCR). To this end, the classical adversarial attack method (i.e., Projection Gradient Descent: PGD) is adopted to generate adversarial examples to evaluate the robustness of the HCCR model. Furthermore, in the training process, we use adversarial examples to improve the robustness of the HCCR model. In the experiments, we utilize a frequently-used DNN model on HCCR and evaluate its robustness on the benchmark dataset CASIA-HWDB. The experimental results show that its recognition accuracy is decreased severely on the adversarial examples, demonstrating the vulnerability of the current HCCR model. In addition, we can improve the recognition accuracy significantly after the adversarial training, demonstrating its effectiveness.

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Huang, Bo, Zhiwei Ke, Yi Wang, Wei Wang, Linlin Shen, and Feng Liu. "Adversarial Defence by Diversified Simultaneous Training of Deep Ensembles." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (May 18, 2021): 7823–31. http://dx.doi.org/10.1609/aaai.v35i9.16955.

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Learning-based classifiers are susceptible to adversarial examples. Existing defence methods are mostly devised on individual classifiers. Recent studies showed that it is viable to increase adversarial robustness by promoting diversity over an ensemble of models. In this paper, we propose adversarial defence by encouraging ensemble diversity on learning high-level feature representations and gradient dispersion in simultaneous training of deep ensemble networks. We perform extensive evaluations under white-box and black-box attacks including transferred examples and adaptive attacks. Our approach achieves a significant gain of up to 52% in adversarial robustness, compared with the baseline and the state-of-the-art method on image benchmarks with complex data scenes. The proposed approach complements the defence paradigm of adversarial training, and can further boost the performance. The source code is available at https://github.com/ALIS-Lab/AAAI2021-PDD.

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Pawlicki, Marek, and Ryszard S. Choraś. "Preprocessing Pipelines including Block-Matching Convolutional Neural Network for Image Denoising to Robustify Deep Reidentification against Evasion Attacks." Entropy 23, no. 10 (October 3, 2021): 1304. http://dx.doi.org/10.3390/e23101304.

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Artificial neural networks have become the go-to solution for computer vision tasks, including problems of the security domain. One such example comes in the form of reidentification, where deep learning can be part of the surveillance pipeline. The use case necessitates considering an adversarial setting—and neural networks have been shown to be vulnerable to a range of attacks. In this paper, the preprocessing defences against adversarial attacks are evaluated, including block-matching convolutional neural network for image denoising used as an adversarial defence. The benefit of using preprocessing defences comes from the fact that it does not require the effort of retraining the classifier, which, in computer vision problems, is a computationally heavy task. The defences are tested in a real-life-like scenario of using a pre-trained, widely available neural network architecture adapted to a specific task with the use of transfer learning. Multiple preprocessing pipelines are tested and the results are promising.

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Lal, Sheeba, Saeed Ur Rehman, Jamal Hussain Shah, Talha Meraj, Hafiz Tayyab Rauf, Robertas Damaševičius, Mazin Abed Mohammed, and Karrar Hameed Abdulkareem. "Adversarial Attack and Defence through Adversarial Training and Feature Fusion for Diabetic Retinopathy Recognition." Sensors 21, no. 11 (June 7, 2021): 3922. http://dx.doi.org/10.3390/s21113922.

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Due to the rapid growth in artificial intelligence (AI) and deep learning (DL) approaches, the security and robustness of the deployed algorithms need to be guaranteed. The security susceptibility of the DL algorithms to adversarial examples has been widely acknowledged. The artificially created examples will lead to different instances negatively identified by the DL models that are humanly considered benign. Practical application in actual physical scenarios with adversarial threats shows their features. Thus, adversarial attacks and defense, including machine learning and its reliability, have drawn growing interest and, in recent years, has been a hot topic of research. We introduce a framework that provides a defensive model against the adversarial speckle-noise attack, the adversarial training, and a feature fusion strategy, which preserves the classification with correct labelling. We evaluate and analyze the adversarial attacks and defenses on the retinal fundus images for the Diabetic Retinopathy recognition problem, which is considered a state-of-the-art endeavor. Results obtained on the retinal fundus images, which are prone to adversarial attacks, are 99% accurate and prove that the proposed defensive model is robust.

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Johnston, Ed. "The adversarial defence lawyer: Myths, disclosure and efficiency—A contemporary analysis of the role in the era of the Criminal Procedure Rules." International Journal of Evidence & Proof 24, no. 1 (August 26, 2019): 35–58. http://dx.doi.org/10.1177/1365712719867972.

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This article contends that piecemeal changes to the adversarial process since the dawn of the new millennium have transformed the CJS. The advent of (near) compulsory disclosure means the defendant has to reveal many elements of his defence. This dilutes the adversarial battle and leaves a process which is managerialist in nature. The Early Guilty Plea system is a mechanism to increase the efficiency by stemming the amount of cases reaching the trial stage. This has an impact on the defence lawyer’s role and renders him conflicted between advancing the best interest of the client against other pre-trial obligations. This small empirical study suggests that classic adversarial lawyers are seen as a relic of a bygone era. The modern criminal justice system prioritises speed and efficiency. If a case reaches court, the defendant is treated as an ‘informational resource’ of the court reminiscent of his position in the 17th century.

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Xu, Enhui, Xiaolin Zhang, Yongping Wang, Shuai Zhang, Lixin Lu, and Li Xu. "WordRevert: Adversarial Examples Defence Method for Chinese Text Classification." IEEE Access 10 (2022): 28832–41. http://dx.doi.org/10.1109/access.2022.3157521.

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Bruce, Neil. "Defence expenditures by countries in allied and adversarial relationships." Defence Economics 1, no. 3 (May 1990): 179–95. http://dx.doi.org/10.1080/10430719008404661.

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Striletska, Oksana. "Establishment and Development of the Adversarial Principle in the Criminal Process." Path of Science 7, no. 7 (July 31, 2021): 1010–16. http://dx.doi.org/10.22178/pos.72-2.

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The article is devoted to studying the history of the origin and development of adversarial principles in criminal proceedings. The evolution of the adversarial principle in the criminal process is studied in chronological order, in historical retrospective. Based on the development of legal regulations and the level of public administration, specific historical periods related to the development of the adversarial principle in criminal proceedings are distinguished. A retrospective suggests that adversarial proceedings should be taken as the basis for the organization of the entire criminal process. Only in this case, it is possible to clearly separate the functions of prosecution, defence, and resolution of criminal proceedings at all its stages and give the parties equal opportunities to provide evidence and defend their positions.

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Macfarlane, Julie. "The Anglican Church’s sexual abuse defence playbook." Theology 124, no. 3 (May 2021): 182–89. http://dx.doi.org/10.1177/0040571x211008547.

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This article is written by a law professor who is also a survivor of sexual abuse by the Anglican priest Meirion Griffiths. In her attempt to get restitution, she recounts her experience of the adversarial tactics used against sexual abuse claimants by the Church of England through the Ecclesiastical Insurance Company. She argues, from her own experience, that the reliance on rape myth, the defence of limitations and the use of biased ‘expert’ medical witnesses are deeply offensive, especially when used by the Church.

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Zhang, Bowen, Benedetta Tondi, Xixiang Lv, and Mauro Barni. "Challenging the Adversarial Robustness of DNNs Based on Error-Correcting Output Codes." Security and Communication Networks 2020 (November 12, 2020): 1–11. http://dx.doi.org/10.1155/2020/8882494.

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The existence of adversarial examples and the easiness with which they can be generated raise several security concerns with regard to deep learning systems, pushing researchers to develop suitable defence mechanisms. The use of networks adopting error-correcting output codes (ECOC) has recently been proposed to counter the creation of adversarial examples in a white-box setting. In this paper, we carry out an in-depth investigation of the adversarial robustness achieved by the ECOC approach. We do so by proposing a new adversarial attack specifically designed for multilabel classification architectures, like the ECOC-based one, and by applying two existing attacks. In contrast to previous findings, our analysis reveals that ECOC-based networks can be attacked quite easily by introducing a small adversarial perturbation. Moreover, the adversarial examples can be generated in such a way to achieve high probabilities for the predicted target class, hence making it difficult to use the prediction confidence to detect them. Our findings are proven by means of experimental results obtained on MNIST, CIFAR-10, and GTSRB classification tasks.

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Більше джерел

Дисертації з теми "Adversarial Defence"

Stiff, Harald. "Explainable AI as a Defence Mechanism for Adversarial Examples." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260347.

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Deep learning is the gold standard for image classification tasks. With its introduction came many impressive improvements in computer vision outperforming all of the earlier machine learning models. However, in contrast to the success it has been shown that deep neural networks are easily fooled by adversarial examples, data that have been modified slightly to cause the neural networks to make incorrect classifications. This significant disadvantage has caused an increased doubt in neural networks and it has been questioned whether or not they are safe to use in practice. In this thesis we propose a new defence mechanism against adversarial examples that utilizes the explainable AI metrics of neural network predictions to filter out adversarial examples prior to model interference. We evaluate the filters against various attacks and models targeted at the MNIST, Fashion-MNIST, and Cifar10 datasets. The results show that the filters can detect adversarial examples constructed with regular attacks but that they are not robust against adaptive attacks that specifically utilizes the architecture of the defence mechanism.
Djupinlärning är den bästa metoden för bildklassificeringsuppgifter. Med dess introduktion kom många imponerande förbättringar inom datorseende som överträffade samtliga tidigare maskininlärningsmodeller. Samtidigt har det i kontrast till alla framgångar visat sig att djupa neuronnät lätt luras av motstridiga exempel, data som har modifierats för att få neurala nätverk att göra felaktiga klassificeringar. Denna nackdel har orsakat ett ökat tvivel gällande huruvida neuronnät är säkra att använda i praktiken. I detta examensarbete föreslås en ny försvarsmekanism mot motstridiga exempel som utnyttjar förklarbar AI för att filtrera bort motstridiga exempel innan de kommer i kontakt med modellerna. Vi utvärderar filtren mot olika attacker och modeller riktade till MNIST-, Fashion-MNIST-, och Cifar10-dataseten. Resultaten visar att filtren kan upptäcka motstridiga exempel konstruerade med vanliga attacker, men att de inte är robusta mot adaptiva attacker som specifikt utnyttjar försvarsmekanismens arkitektur.

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Garcia, Dennis Alberto. "Peer-to-peer network modeling for adversarial proactive cyber defenses." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112849.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 49-50).
This thesis implements a novel peer-to-peer network simulator that integrates co-evolutionary algorithms in order to model adversarial attack and defense dynamics in networks. Modeling this behavior is desirable as it allows for network designers to better develop network defense strategies against adaptive cyber attackers. By developing a network simulator that implements a peer-to-peer protocol, we were able to control the environment and abstract away many of the complex details that would normally arise from using a live network. Because of this environment, we were able to design attack and defense models and grammars, construct arbitrary network topologies, and rapidly test adversarial behavior using the integrated coevolutionary algorithms. Second, the thesis implements the integration of the coevolutionary algorithms with a more complex, proprietary emulator that implements an advanced version of Chord. Our experiments with this system start to investigate the effectiveness of peer-to-peer networks as defenders as well as elucidate the issues of integrating coevolutionary algorithms in a real-world system.
by Dennis Alberto Garcia.
M. Eng.

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Coulibaly, Ibrahima. "Les droits de la défense en droit mauritanien." Thesis, Paris 8, 2018. http://www.theses.fr/2018PA080008.

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L’universalisme des droits a fait accéder au concept des droits de la défense des diversités procédurales. Au niveau de chaque pays, qu’il soit petit ou grand, quelle que soit sa culture, il est accepté et officiel qu’on ne peut juger sans se référer aux règles fondamentales, et sans se faire assister par un avocat. Les droits à la défense sont garantis en Mauritanie par la loi n° 2007-036 portant approbation d'un Code de Procédure Pénale, la loi n° 2007- 012 portant l'Organisation Judiciaire et la loi n° 99-035 portant code de Procédure Civile Commerciale et Administrative. Les règles des droits de la défense ne peuvent être atteintes sans la mise en place d’organes qui encadrent les dispositions de celle-ci. L’égalité devant la Justice est expressément considérée de droit fondamental dans la constitution du 20 juillet 1991. Cependant, le principe n'ait aucune portée réelle malgré la précision du texte. Ce qui paraît absurde avec notre modèle de système de « droit ineffectif », implique, que les règles du procès équitable ne sont pas affectées de manière égalitaire à tous. Ce n’est pas la seule difficulté ou ambigüité. La présente étude soutient, d’une part, que l’exercice des principes du contradictoire et de l’égalité des armes garantit l’effectivité des droits de la défense, et d’autre part, que le développement des principes participe à un renouveau des droits. La position contemporaine des droits de la défense emploie cette notion, démontrant souvent les droits de la défense comme une implication supérieure et d’une évidence logique de la procédure, obéissant donc aux critères fondamentaux du droit à un procès équitable. Il se détermine par toute une série de procédures menées dans un procès et se déclare, aujourd’hui, sous un ensemble de bases juridiques protégeant les droits de la défense. Pour ce faire nous avons essayé de faire un travail d’évaluation sociologique sans prétention de scientificité parfaite. Evitant tout juridisme ou positivisme, le travail reste néanmoins à dominance juridique
Universalism of the rights have come the concept the rights of the defenses diversity of procedural. A the level of each country, however big or small, whatever is its culture, he (It) is accepted and official that we cannot judge without referring to the fundamental rules (rulers), and without being attended by a lawyer. Rights of defence are guaranteed in Mauritanie by the law number 2007-036 carrying Code of criminal procedure, the law number 2007-012 carrying the judicial organization, the law number 99–035 carrying Code of civil procedure, commercial and administrative. The rules of rights of defence not wind not to be reached without the implementation of organs which frame the capacities of this one. The equality before the courts is expressly considered by fundamental law in the of the constitution owed July 20th, 1991. However, the principle is of no real reach in spite of the precision of the text. What seems absurd with our model of system of ineffective right, imply that the rules of the fair trial are not allocated in a egalitarian way to all. It is not the only difficulty or the ambiguity. The present study supports on one hand that the exercice of the equality of the contradictory and the equality of weapons guarantees the effectiveness of rights of defence, and on the other hand, that the development of the principles participates in a revival oo the rights.The contemporary position of rights of defence uses this notion demonstrating, often rights of defence as a superior implication and of a logical obvious fact of the procedure, thus obeying the fundamental criteria of the right to fair trial. He is determined by a whole series of procedures led in a trial and declares itself, today, under a set of legal bases protecting rights of defence. To this end we had tried to make a work of unpretentious sociological evaluation of perfect scientificity. Avoiding any legalism or positivism, the work stays nevertheless in legal dominance

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Wood, Adrian Michael. "A defensive strategy for detecting targeted adversarial poisoning attacks in machine learning trained malware detection models." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2021. https://ro.ecu.edu.au/theses/2483.

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Machine learning is a subset of Artificial Intelligence which is utilised in a variety of different fields to increase productivity, reduce overheads, and simplify the work process through training machines to automatically perform a task. Machine learning has been implemented in many different fields such as medical science, information technology, finance, and cyber security. Machine learning algorithms build models which identify patterns within data, which when applied to new data, can map the input to an output with a high degree of accuracy. To build the machine learning model, a dataset comprised of appropriate examples is divided into training and testing sets. The training set is used by the machine learning algorithm to identify patterns within the data, which are used to make predictions on new data. The test set is used to evaluate the performance of the machine learning model. These models are popular because they significantly improve the performance of technology through automation of feature detection which previously required human input. However, machine learning algorithms are susceptible to a variety of adversarial attacks, which allow an attacker to manipulate the machine learning model into performing an unwanted action, such as misclassifying data into the attackers desired class, or reducing the overall efficacy of the ML model. One current research area is that of malware detection. Malware detection relies on machine learning to detect previously unknown malware variants, without the need to manually reverse-engineer every suspicious file. Detection of Zero-day malware plays an important role in protecting systems generally but is particularly important in systems which manage critical infrastructure, as such systems often cannot be shut down to apply patches and thus must rely on network defence. In this research, a targeted adversarial poisoning attack was developed to allow Zero-day malware files, which were originally classified as malicious, to bypass detection by being misclassified as benign files. An adversarial poisoning attack occurs when an attacker can inject specifically-crafted samples into the training dataset which alters the training process to the desired outcome of the attacker. The targeted adversarial poisoning attack was performed by taking a random selection of the Zero-day file’s import functions and injecting them into the benign training dataset. The targeted adversarial poisoning attack succeeded for both Multi-Layer Perceptron (MLP) and Decision Tree models without reducing the overall efficacy of the target model. A defensive strategy was developed for the targeted adversarial poisoning attack for the MLP models by examining the activation weights of the penultimate layer at test time. If the activation weights were outside the norm for the target (benign) class, the file is quarantined for further examination. It was found to be possible to identify on average 80% of the target Zero-day files from the combined targeted poisoning attacks by examining the activation weights of the neurons from the penultimate layer.

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Kanerva, Anton, and Fredrik Helgesson. "On the Use of Model-Agnostic Interpretation Methods as Defense Against Adversarial Input Attacks on Tabular Data." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20085.

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Context. Machine learning is a constantly developing subfield within the artificial intelligence field. The number of domains in which we deploy machine learning models is constantly growing and the systems using these models spread almost unnoticeably in our daily lives through different devices. In previous years, lots of time and effort has been put into increasing the performance of these models, overshadowing the significant risks of attacks targeting the very core of the systems, the trained machine learning models themselves. A specific attack with the aim of fooling the decision-making of a model, called the adversarial input attack, has almost exclusively been researched for models processing image data. However, the threat of adversarial input attacks stretches beyond systems using image data, to e.g the tabular domain which is the most common data domain used in the industry. Methods used for interpreting complex machine learning models can help humans understand the behavior and predictions of these complex machine learning systems. Understanding the behavior of a model is an important component in detecting, understanding and mitigating vulnerabilities of the model. Objectives. This study aims to reduce the research gap of adversarial input attacks and defenses targeting machine learning models in the tabular data domain. The goal of this study is to analyze how model-agnostic interpretation methods can be used in order to mitigate and detect adversarial input attacks on tabular data. Methods. The goal is reached by conducting three consecutive experiments where model interpretation methods are analyzed and adversarial input attacks are evaluated as well as visualized in terms of perceptibility. Additionally, a novel method for adversarial input attack detection based on model interpretation is proposed together with a novel way of defensively using feature selection to reduce the attack vector size. Results. The adversarial input attack detection showed state-of-the-art results with an accuracy over 86%. The proposed feature selection-based mitigation technique was successful in hardening the model from adversarial input attacks by reducing their scores by 33% without decreasing the performance of the model. Conclusions. This study contributes with satisfactory and useful methods for adversarial input attack detection and mitigation as well as methods for evaluating and visualizing the imperceptibility of attacks on tabular data.
Kontext. Maskininlärning är ett område inom artificiell intelligens som är under konstant utveckling. Mängden domäner som vi sprider maskininlärningsmodeller i växer sig allt större och systemen sprider sig obemärkt nära inpå våra dagliga liv genom olika elektroniska enheter. Genom åren har mycket tid och arbete lagts på att öka dessa modellers prestanda vilket har överskuggat risken för sårbarheter i systemens kärna, den tränade modellen. En relativt ny attack, kallad "adversarial input attack", med målet att lura modellen till felaktiga beslutstaganden har nästan uteslutande forskats på inom bildigenkänning. Men, hotet som adversarial input-attacker utgör sträcker sig utom ramarna för bilddata till andra datadomäner som den tabulära domänen vilken är den vanligaste datadomänen inom industrin. Metoder för att tolka komplexa maskininlärningsmodeller kan hjälpa människor att förstå beteendet hos dessa komplexa maskininlärningssystem samt de beslut som de tar. Att förstå en modells beteende är en viktig komponent för att upptäcka, förstå och mitigera sårbarheter hos modellen. Syfte. Den här studien försöker reducera det forskningsgap som adversarial input-attacker och motsvarande försvarsmetoder i den tabulära domänen utgör. Målet med denna studie är att analysera hur modelloberoende tolkningsmetoder kan användas för att mitigera och detektera adversarial input-attacker mot tabulär data. Metod. Det uppsatta målet nås genom tre på varandra följande experiment där modelltolkningsmetoder analyseras, adversarial input-attacker utvärderas och visualiseras samt där en ny metod baserad på modelltolkning föreslås för detektion av adversarial input-attacker tillsammans med en ny mitigeringsteknik där feature selection används defensivt för att minska attackvektorns storlek. Resultat. Den föreslagna metoden för detektering av adversarial input-attacker visar state-of-the-art-resultat med över 86% träffsäkerhet. Den föreslagna mitigeringstekniken visades framgångsrik i att härda modellen mot adversarial input attacker genom att minska deras attackstyrka med 33% utan att degradera modellens klassifieringsprestanda. Slutsats. Denna studie bidrar med användbara metoder för detektering och mitigering av adversarial input-attacker såväl som metoder för att utvärdera och visualisera svårt förnimbara attacker mot tabulär data.

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Branlat, Matthieu. "Challenges to Adversarial Interplay Under High Uncertainty: Staged-World Study of a Cyber Security Event." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1316462733.

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Jobert, Sylvain. "La connaissance des actes du procès civil par les parties." Thesis, Paris 2, 2016. http://www.theses.fr/2016PA020070.

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En procédure civile, la connaissance des actes du procès par les parties est essentielle ; des garanties importantes y sont attachées, à commencer par le respect du principe du contradictoire. Une difficulté se pose, toutefois : il est malaisé de déterminer si une partie a eu connaissance de l’acte qui lui a été communiqué. Toute la question est alors de savoir comment le droit s’accommode de cette difficulté. À cette fin, deux modèles contraires peuvent être dégagés. Dans le premier, formaliste, il est fait le choix de favoriser la connaissance des actes du procès par les parties en amont, pour pouvoir se désintéresser de leur connaissance effective en aval, tous les moyens ayant été mis en oeuvre pour y parvenir. Dans le second, réaliste, on se désintéresse de la façon dont les actes du procès sont portés à la connaissance des parties, mais, par la suite, on prête beaucoup d’intérêt à la connaissance que les parties en ont réellement eue. L’étude révèle que le droit du procès civil reposait initialement sur un modèle à dominante formaliste, mais que ce modèle a évolué, particulièrement au cours des dix dernières années. Sous l’influence des soucis contemporains de rationalisation des coûts de la justice et de protection accrue des droits fondamentaux des parties, le formalisme du droit du procès civil s’est tempéré. Faudrait-il qu’il le soit davantage ? Ce travail ne plaide ni pour la subversion du modèle classique, ni pour son rétablissement. Plutôt, c’est une évolution nuancée du droit qui est suggérée, proposant d’exalter le formalisme lorsque la sécurité juridique l’exige, sans renoncer à tirer profit de règles l’atténuant quand cela s’impose
In civil law procedures, the parties’ knowledge of the acts of the trial is essential; it guarantees that certain principles, such as the adversarial principle, will be respected. However, a difficulty arises: it is hard to determine whether a party has in fact become aware of the act which was communicated to him. The question is to determine whether the law can accept such a difficulty. To this end, two divergent models can be provided. In the formalistic one, the choice is made to favor the knowledge of the acts of the trial beforehand, in order to be able to become disinterested in their actual knowledge afterwards, all the means having been implemented to carry this out. In the realistic one, the way in which the acts of the trial are brought to the parties' attention is neglected, but thereafter, there is a resurgent focus on the knowledge the parties have genuinely had. The study reveals that the law of civil trial was initially based on a predominantly formalistic model, but this model has evolved, especially during the last decade. Under the influence of contemporary concerns in order to rationalize justice costs and increase the protection of the parties' fundamental rights, the formalism of civil lawsuit has been tempered. Should it be even more moderate? This work neither pleads for the subversion of the classical model nor for its reinstatement. Instead, it is a nuanced evolution of the law which is suggested. It suggests to promote formalism when legal certainty requires it, without sacrificing the benefit of lightening the rules when it is necessary

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Metenier, Julian. "La protection pénale de l'accusé." Thesis, Aix-Marseille, 2014. http://www.theses.fr/2014AIXM1065.

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Le thème de la protection pénale de l'accusé, connu des pénalistes, mérite aujourd'hui d'être renouvelé sous un angle essentiellement probatoire, au regard de l'évolution actuelle du procès pénal. Situés au confluent de l'innocence et de la culpabilité, les droits et garanties accordés à l'accusé, entendu dans son acception conventionnelle, doivent être analysés en considération des principes fondateurs que sont la présomption d'innocence et les droits de la défense. L'évolution continue de ces deux principes, dans un sens diamétralement opposé, rejaillit inévitablement sur l'intensité et les modalités de la protection dont bénéficie toute personne suspectée ou poursuivie dans le cadre d'une procédure pénale.La présente étude, volontairement limitée à la phase préparatoire du procès pénal, se propose d'appréhender, dans un souci pratique et technique, les différentes évolutions jurisprudentielles et législatives opérées en la matière. Y seront ainsi abordées les principales problématiques actuellement rencontrées en procédure pénale telles que la question du statut juridique du suspect ou encore l'effectivité du principe du contradictoire dans l'avant-procès pénal. S'il peut être tentant, au premier abord, de conclure à un renforcement indiscutable de la protection pénale accordée à l'accusé, il conviendra alors de reconsidérer cette question à l'aune de l'étude des limites procédurales attachées au procès pénal. Loin d'aborder ce thème dans une optique partisane, il sera question de modération dans les propos tenus. En effet, peut-être plus que sur toute autre question de procédure pénale, il est impératif de savoir raison garder
The theme of the criminal protection of the accused, well-known to criminal specialists, today deserves to be renewed under a probationary essentially angle, in the light of current developments in the criminal trial. Located at the confluence of innocence and guilt, the rights and guarantees granted to the accused understood in its conventional sense, must be analyzed in consideration of the founding principles of presumption of innocence and the rights of the defense. The continuing evolution of these two principles, in a sense diametrically opposite, inevitably reflects the intensity and the terms of the protection afforded any person suspected or prosecuted under criminal proceedings.This study deliberately limited to the pre-trial phase, proposes to understand, in a practical and technical problems, the various case law and legislative developments carried out in the field. Will thus addressed the key issues currently faced in criminal proceedings such as the question of the legal status of the suspect or the effectiveness of the adversarial principle in the preliminary criminal trial. While it may be tempting, at first, to conclude an indisputable strengthening the criminal protection afforded to the accused, then it will be necessary to reconsider this issue in terms of the study of procedural limitations attached to the criminal trial. Far from addressing this issue in a partisan way, it will be about moderation in the remarks. Indeed, perhaps more than any other issue of criminal procedure, it is imperative to keep a sense of proportion

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Borges, Lélia Moreira. "Adolescente em conflito com a lei: uma análise do direito à ampla defesa em Goiânia/Goiás." Universidade Federal de Goiás, 2017. http://repositorio.bc.ufg.br/tede/handle/tede/8806.

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This dissertation had as its objective verify whether the adolescents submitted to the institutionalization measures in Goiânia, Goiás – Brazil, were guaranteed their right to the adversarial principle and full defense in their trials. The empirical field of this investigation consisted of the analysis of cases filed between the periods of 2014 to 2016, and the observation of hearings carried out in the infractions court of Child and Youth Court of Goiânia, GO and interviews with public defenders. The Federal Constitution of 1988, the Child and Adolescent Statute, Criminal Code, Criminal Procedure and Civil Procedure Codes were used as the main legal references for this study. As theoretical support, Emílio G. Mendez, Pierre Bourdieu and Loïc Wacquant were also used. These references were useful in the understanding of the infraction persecution dynamics operationalized by the security and justice system of the State. As well as that, the understanding of the socio-juridical paradigm in force at each moment of history that justified the penalization of children and adolescents; the concept of field as a social space in competition, subject to internal disputes hierarchically established by the monopoly of the significance of such space, and the intensification of punitive actions by the State allow the perception of the permanence of the irregular situation paradigm in the professionals’ performances and judicial decisions. Decisions marked by inequality between institutions that operate in the juvenile criminal justice system, facing the recent entry of the public defense counsel, not yet totally structured, in the game of signification and legitimation of a trial that is preponderantly inquisitive. It brings loss to the exercise of full defense of the adolescents accused of acts of infraction. Evidence of a mismatch is noticed between the advances in the children’s and adolescents’ acquisition of rights and guarantees and the criminal control operationalized by the juvenile criminal justice system of Goiânia / GO.
Essa dissertação teve como objetivo verificar se os adolescentes submetidos à medida de internação em Goiânia/Goiás tiveram garantidos o direito ao contraditório e a ampla defesa nos seus julgamentos. O campo empírico desta investigação consistiu na análise de processos arquivados entre os períodos de 2014 a 2016, da observação de audiências realizadas na vara de atos infracionais do Juizado da Infância e Juventude de Goiânia/GO e de entrevistas aos defensores públicos. A Constituição Federal de 1988, Estatuto da Criança e do Adolescente, Códigos Penal, de Processo Penal e de Processo Civil foram referência para este estudo. Como suportes teóricos foram utilizados, entre outros, Emílio G. Mendez, Pierre Bourdieu e Loïc Wacquant. Esses referenciais serviram de suporte para entender os diferentes paradigmas jurídicos que justificaram a aplicação de penalização de crianças e adolescentes no decorrer da história apresentados por Mendez: nas considerações para uma sociologia do campo jurídico deixadas por Pierre Bourdieu sobre a força do direito, enquanto instrumento de poder da reprodução social e, nas discussões apresentas por Wacquant acerca do controle social e do estado punitivo. Permitindo assim, perceber a permanência do paradigma da situação irregular na atuação dos profissionais e nas decisões judiciais; a desigualdade entre instituições que atuam no sistema de justiça penal juvenil, dada a recente entrada da Defensoria Pública ainda não totalmente estruturada, no jogo da significação e legitimação de um julgamento preponderantemente inquisitivo, ocasionando com isso, prejuízo ao exercício pleno da defesa dos(as) adolescentes acusados(as) de atos infracionais. Evidenciando um descompasso entre os avanços na conquista de direitos e garantias das crianças e adolescentes e o controle social operacionalizado pelo sistema de justiça penal juvenil de Goiânia/GO.

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Nga, Essomba Tergalise. "La protection des droits de l'accusé devant la cour pénale internationale." Thesis, Lyon 3, 2011. http://www.theses.fr/2011LYO30005.

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La protection des droits de l’accusé est tributaire du respect du procès équitable dans presque tout débat judiciaire. Ce faisant, la création de la CPI suscite une attention particulière en vertu non seulement de son caractère permanent et universel, mais aussi de l’ampleur des crimes internationaux qu’elle connait. Sous l’effet de cette configuration, la recherche laisse découvrir une protection à l’efficacité relative et utopique malgré l’exigence de compatibilité du droit applicable aux droits de l’homme internationalement reconnus. Toutefois, le respect apparent de ces droits, l’application du principe du contradictoire et l’exigence de la présence de l’accusé dans son procès ne garantissent pas l’effectivité de l’égalité des armes, l’exercice des droits de la défense et le respect de la présomption d’innocence. Au contraire, la prééminence du déséquilibre processuel, de la durée excessive des procès et du maintien en détention de l’accusé conduit à faire objection sur l’existence possible de la protection efficace des droits de l’accusé. La dite protection cède plutôt devant la lutte contre l’impunité, la délicatesse des victimes et témoins et la souveraineté des Etats. A l’issue de cette étude, il est nécessaire de procéder à un rééquilibrage des droits entre les parties et à une reconceptualisation de la compétence de la Cour
Protecting the rights of the accused depends in any legal debate on respect for a fair trial. In doing so, the creation of the ICC merits special attention by virtue not only of its being permanent and universal, but also the extent of international crimes with which it deals. As a result of this broad scope, research suggests any protective coverage is relative in its effectiveness and utopian, despite the requirement of compatibility of the law applicable to internationally recognized human rights. The apparent respect for these rights, the principle of due process and the requirement of the presence of the accused at his or her trial do not guarantee an effective equality of arms, the exercise of one’s rights or respect for the presumption of innocence. Instead, the procedural rule of imbalance, the excessive length of trials and the continued detention of the accused have led to objections about effectively protecting the rights of the accused. So-called protection gives way instead to the fight against impunity, the reticence of victims and witnesses and the sovereignty of States. Following this study, it is necessary to rebalance the rights of the parties and rethink the jurisdiction of the Court

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Книги з теми "Adversarial Defence"

Jajodia, Sushil, George Cybenko, Peng Liu, Cliff Wang, and Michael Wellman, eds. Adversarial and Uncertain Reasoning for Adaptive Cyber Defense. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30719-6.

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Hausman, David. Securities law in the adversarial setting. Toronto]: Faculty of Law, University of Toronto, 2014.

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Hausman, David. Securities law in the adversarial setting. Toronto]: Faculty of Law, University of Toronto, 2012.

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Hausman, David. Securities law in the adversarial setting. Toronto]: Faculty of Law, University of Toronto, 2014.

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Hausman, David. Securities law in the adversarial setting. Toronto]: Faculty of Law, University of Toronto, 2013.

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Rose, Clive. Campaigns against western defence: NATO's adversaries and critics. 2nd ed. Basingstoke: Macmillan, 1986.

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Rose, Clive. Campaigns against western defence: NATO's adversaries and critics. New York: St. Martin's Press, 1985.

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Campaigns against Western defence: NATO's adversaries and critics. Basingstoke: Macmillan, 1985.

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Rose, Clive. Campaigns against Western defence: NATO's adversaries and critics. Basingstoke: Macmillan, 1985.

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Campaigns against western defence: NATO's adversaries and critics. 2nd ed. Houndmills, Basingstoke, Hampshire: Macmillan, 1986.

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Частини книг з теми "Adversarial Defence"

Zheng, Yanbin, Hongxu Yun, Fu Wang, Yong Ding, Yongzhong Huang, and Wenfen Liu. "Defence Against Adversarial Attacks Using Clustering Algorithm." In Communications in Computer and Information Science, 323–33. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0118-0_25.

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Kamath, Aayush, Vrinda Bhatu, Tejas Paranjape, and Rupali Sawant. "Malware Classification and Defence Against Adversarial Attacks." In Proceedings of Data Analytics and Management, 267–74. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6285-0_22.

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Gittings, T., S. Schneider, and J. Collomosse. "Vax-a-Net: Training-Time Defence Against Adversarial Patch Attacks." In Computer Vision – ACCV 2020, 235–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69538-5_15.

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Taran, Olga, Shideh Rezaeifar, and Slava Voloshynovskiy. "Bridging Machine Learning and Cryptography in Defence Against Adversarial Attacks." In Lecture Notes in Computer Science, 267–79. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11012-3_23.

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Zhou, Jiahui, Nayyar Zaidi, Yishuo Zhang, and Gang Li. "Discretization Inspired Defence Algorithm Against Adversarial Attacks on Tabular Data." In Advances in Knowledge Discovery and Data Mining, 367–79. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05936-0_29.

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Rose, Clive. "Adversaries and Critics." In Campaigns Against Western Defence, 3–18. London: Palgrave Macmillan UK, 1985. http://dx.doi.org/10.1007/978-1-349-07526-3_1.

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Rose, Clive. "Adversaries and Critics." In Campaigns Against Western Defence, 3–18. London: Palgrave Macmillan UK, 1986. http://dx.doi.org/10.1007/978-1-349-18523-8_1.

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Shao, Rui, Pramuditha Perera, Pong C. Yuen, and Vishal M. Patel. "Open-Set Adversarial Defense." In Computer Vision – ECCV 2020, 682–98. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58520-4_40.

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Kuribayashi, Minoru. "Defense Against Adversarial Attacks." In Frontiers in Fake Media Generation and Detection, 131–48. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1524-6_6.

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Xu, Ying, Kiran Raja, Raghavendra Ramachandra, and Christoph Busch. "Adversarial Attacks on Face Recognition Systems." In Handbook of Digital Face Manipulation and Detection, 139–61. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87664-7_7.

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AbstractFace recognition has been widely used for identity verification both in supervised and unsupervised access control applications. The advancement in deep neural networks has opened up the possibility of scaling it to multiple applications. Despite the improvement in performance, deep network-based Face Recognition Systems (FRS) are not well prepared against adversarial attacks at the deployment level. The output performance of such FRS can be drastically impacted simply by changing the trained parameters, for instance, by changing the number of layers, subnetworks, loss and activation functions. This chapter will first demonstrate the impact on biometric performance using a publicly available face dataset. Further to this, this chapter will also present some strategies to defend against such attacks by incorporating defense mechanisms at the training level to mitigate the performance degradation. With the empirical evaluation of the deep FRS with and without a defense mechanism, we demonstrate the impact on biometric performance for the completeness of the chapter.

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Тези доповідей конференцій з теми "Adversarial Defence"

Oneto, Luca, Sandro Ridella, and Davide Anguita. "The Benefits of Adversarial Defence in Generalisation." In ESANN 2021 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Louvain-la-Neuve (Belgium): Ciaco - i6doc.com, 2021. http://dx.doi.org/10.14428/esann/2021.es2021-28.

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Xu, Ying, Xu Zhong, Antonio Jimeno Yepes, and Jey Han Lau. "Grey-box Adversarial Attack And Defence For Sentiment Classification." In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.naacl-main.321.

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Xu, Tongyang, and Zhongxiang Wei. "Waveform Defence Against Deep Learning Generative Adversarial Network Attacks." In 2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). IEEE, 2022. http://dx.doi.org/10.1109/csndsp54353.2022.9907905.

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Couturier, Antonin, and Anton-David Almasan. "Semi-supervised Domain Adaptation via adversarial training." In 2021 Sensor Signal Processing for Defence Conference (SSPD). IEEE, 2021. http://dx.doi.org/10.1109/sspd51364.2021.9541427.

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Gouk, Henry, and Timothy M. Hospedales. "Optimising Network Architectures for Provable Adversarial Robustness." In 2020 Sensor Signal Processing for Defence Conference (SSPD). IEEE, 2020. http://dx.doi.org/10.1109/sspd47486.2020.9272169.

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Zoto, Erjon, Stewart Kowalski, Christopher Frantz, Basel Katt, and Edgar Lopez-Rojas. "CyberAIMs: a tool for teaching adversarial and systems thinking." In The 8th International Defence and Homeland Security Simulation Workshop. CAL-TEK srl, 2018. http://dx.doi.org/10.46354/i3m.2018.dhss.004.

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"CyberAIMs stands for Cyber Agents’ Interactive Modeling and Simulation. We designed this tool in order to use it as an educational tool to teach Master students in a Cyber security course. This paper aims to describe the model and explain the design choices behind CyberAIMs in terms of associating them with the emerging concepts within cyber security curriculum, namely adversarial and systems thinking. The preliminary results indicate that the current distribution of values and entities allows most of the defense agents to avoid losing all their resources to their attack counterparts. We intend to use this tool as part of a lab with students in Information Security and further extend our target users, by including others who need training in adversarial and systems thinking. We conclude by providing rough results from running simulations with the tool and giving further directions of our future research, in order to improve the usability and level of detail for this tool."

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Tan, Wei, Jiajia Zhao, Xinkai Liang, Hanchen Lu, Baogang Song, and Hao Guan. "Adversarial Example Attack and Defence of Object Recognition: A Survey." In 2022 IEEE International Conference on Unmanned Systems (ICUS). IEEE, 2022. http://dx.doi.org/10.1109/icus55513.2022.9986597.

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Makridis, Georgios, Spyros Theodoropoulos, Dimitrios Dardanis, Ioannis Makridis, Maria Margarita Separdani, Georgios Fatouros, Dimosthenis Kyriazis, and Panagiotis Koulouris. "XAI enhancing cyber defence against adversarial attacks in industrial applications." In 2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS). IEEE, 2022. http://dx.doi.org/10.1109/ipas55744.2022.10052858.

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Nakane, Ikuko. "Accusation, defence and morality in Japanese trials: A Hybrid Orientation to Criminal Justice." In GLOCAL Conference on Asian Linguistic Anthropology 2019. The GLOCAL Unit, SOAS University of London, 2019. http://dx.doi.org/10.47298/cala2019.16-5.

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The Japanese criminal justice system has gone through transformations in its modern history, adopting the models of European Continental Law systems in the 19th century as part of Japan’s modernisation process, and then the Anglo-American Common Law orientation after WWII. More recently, citizen judges have been introduced to the criminal justice process, a further move towards an adversarial orientation with increased focus on orality and courtroom discourse strategies. Yet, the actual legal process does not necessarily represent the adversarial orientation found in Common Law jurisdictions. While previous research from cultural and socio-historical perspectives has offered valuable insights into the Japanese criminal court procedures, there is hardly any research examining how adversarial (or non-adversarial) orientation is realised through language in Japanese trials. Drawing on an ethnographic study of communication in Japanese trials, this paper discusses a ‘hybrid’ orientation to the legal process realised through courtroom discourse. Based on courtroom observation notes, interaction data, lawyer interviews and other relevant materials collected in Japan, trial participants’ discourse strategies contributing to both adversarial and inquisitorial orientations are identified. In particular, the paper highlights how accusation, defence and morality are performed and interwoven in the trial as a genre. The overall genre structure scaffolds competing narratives, with prosecution and defence counsel utilising a range of discourse strategies for highlighting culpability and mitigating factors. However, the communicative practice at the micro genre level shows an orientation to finding the ‘truth,’ rehabilitation of offenders and maintaining social order. The analysis of courtroom communication, contextualised in the socio-historical development of the Japanese justice system and in the ideologies about courtroom communicative practice, suggests a gap between the practice and official/public discourses of the justice process in Japan. At the same time, the findings raise some questions regarding the powerful role that language plays in different ways in varying approaches to delivery of justice.

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Han, Yi, David Hubczenko, Paul Montague, Olivier De Vel, Tamas Abraham, Benjamin I. P. Rubinstein, Christopher Leckie, Tansu Alpcan, and Sarah Erfani. "Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence." In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. http://dx.doi.org/10.1109/ijcnn48605.2020.9206634.

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Звіти організацій з теми "Adversarial Defence"

Allan, Duncan, and Ian Bond. A new Russia policy for post-Brexit Britain. Royal Institute of International Affairs, January 2022. http://dx.doi.org/10.55317/9781784132842.

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The UK’s 2021 Integrated Review of security, defence, development and foreign policy describes Russia as ‘the most acute direct threat to [the UK’s] security’ in the 2020s. Relations did not get this bad overnight: the trend has been negative for nearly two decades. The bilateral political relationship is now broken. Russian policymakers regard the UK as hostile, but also as weaker than Russia: a junior partner of the US and less important than Germany within Europe. The consensus among Russian observers is that Brexit has reduced the UK’s international influence, to Russia’s benefit. The history of UK–Russia relations offers four lessons. First, because the two lack shared values and interests, their relationship is fragile and volatile. Second, adversarial relations are the historical norm. Third, each party exaggerates its importance on the world stage. Fourth, external trends beyond the UK’s control regularly buffet the relationship. These wider trends include the weakening of the Western-centric international order; the rise of populism and opposition to economic globalization; and the global spread of authoritarian forms of governance. A coherent Russia strategy should focus on the protection of UK territory, citizens and institutions; security in the Euro-Atlantic space; international issues such as non-proliferation; economic relations; and people-to-people contacts. The UK should pursue its objectives with the tools of state power, through soft power instruments and through its international partnerships. Despite Brexit, the EU remains an essential security partner for the UK. In advancing its Russia-related interests, the UK should have four operational priorities: rebuilding domestic resilience; concentrating resources on the Euro-Atlantic space; being a trusted ally and partner; and augmenting its soft power. UK decision-makers should be guided by four propositions. In the first place, policy must be based on clear, hard-headed thinking about Russia. Secondly, an adversarial relationship is not in itself contrary to UK interests. Next, Brexit makes it harder for the UK and the EU to deal with Russia. And finally, an effective Russia policy demands a realistic assessment of UK power and influence. The UK is not a ‘pocket superpower’. It is an important but middling power in relative decline. After Brexit, it needs to repair its external reputation and maximize its utility to allies and partners, starting with its European neighbours.

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Collazo, Hector III L. Defending Against Opposed Patterns of Resistant: Can Past Cultural Lessons in Armed Conflict Help U.S. Identify, Defend, Adapt, or Exploit Notions of Resistant With New Adversaries Like ISIS. Fort Belvoir, VA: Defense Technical Information Center, May 2015. http://dx.doi.org/10.21236/ad1012800.

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