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Towards Optimal Leakage Assessment of TVLA 7th

Towards Optimal Leakage Assessment of TVLA

引用

8th Asia Pacific Web and Web-Age information Management Joint International Conference on Web and Big Data

作者： Bi, Yuanqiao Li, Weijian Xie, Guiyuan Jianghan Univ Engn Training Ctr Wuhan Peoples R China Guangdong Polytech Normal Univ Sch Comp Sci Guangzhou Peoples R China

ISBN: (纸本)9789819600540;9789819600557

Since side-channel attacks pose a very serious threat to cryptographic products, leakage assessment plays a key role in the evaluation of the physical security of cryptographic products before putting into the market. However, the widely used Common Criteria (CC) method is both costly and difficult to apply, while the Test Vector Leakage Assessment (TVLA) method fails to accurately detect key leakage points. In this paper, a feature selection technique in machine learning is introduced, with which the leakage points detected by TVLA are treated as features for supervised learning. According to their contribution to the classification, irrelevant features are removed, while the optimal features remained, which identify more important leakage points. We further extend the assessment from two groups to multiple groups, which achieves much better performance. Experimental results show that, compared with existing methods such as TVLA,chi(2)-test, TVLA-Bonferroni and ANOVA test, our methods detect leakage points more accurately and stably, and greatly improve the evaluation performance in term of accuracy, leakage hit rate and false positive rate. Besides, our methods require much fewer power traces and shorter time for evaluation than existing methods.

关键词： Side-channel Attacks Leakage Evaluation Feature Selection

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CB-RISE: Improving the RISE Interpretability Method Through Convergence Detection and Blurred Perturbations 12th

CB-RISE: Improving the RISE Interpretability Method Through ...

引用

12th Conference on Cloud Computing, Big Data and Emerging Topics

作者： Stanchi, Oscar Ronchetti, Franco Dal Bianco, Pedro Rios, Gaston Ahon, Santiago Ponte Hasperue, Waldo Quiroga, Facundo Univ Nacl La Plata Inst Invest Informat LIDI La Plata Argentina Comis Invest Cient Pcia Bs CIC PBA La Plata Argentina Univ Nacl La Plata UNLP La Plata Argentina Consejo Nacl Invest Cient & Tecn CONICET La Plata Argentina

ISBN: (纸本)9783031708060;9783031708077

This paper presents significant advancements in the RISE (Randomized Input Sampling for Explanation) algorithm, a popular black-box interpretability method for image data. RISE's main weakness lies on the large number of model evaluations required to produce the importance heatmap. Furthermore, RISE's strategy of occluding image regions with black patches is not advisable, as it may lead to unexpected predictions. Therefore, we introduce two new versions of the algorithm, C-RISE and CB-RISE, each incorporating novel features to address the two major challenges of the original implementation. CRISE introduces a convergence detection based on the Welford algorithm which reduces the computational burden of the algorithm by ceasing computations once the importance map stabilizes. CB-RISE, additionally, introduces the use of blurred masks as perturbations, equivalent to applying Gaussian noise, as opposed to black patches. This allows for a more nuanced representation of the model's decision-making process. Our experimental results demonstrate the effectiveness of these improvements, successfully enhancing the effectiveness of the generated heatmaps while improving their quality, qualitatively, and showing a speedup of approximately 3.

关键词： Black Box Blurred Masks omputer Vision Convergence Detection Deep Learning Interpretability RISE

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A Technique for Authentic Fatigue Driving Detection Using Nighttime Infrared Images 12th

A Technique for Authentic Fatigue Driving Detection Using Ni...

引用

2023 International Conference on Smart Cities and Green ICT Systems and International Conference on Vehicle Technology and Intelligent Transport Systems

作者： Lin, Huei-Yung Tu, Kai-Chun Natl Taipei Univ Technol Dept Comp Sci & Informat Engn 1Sec 3Zhongxiao E Rd Taipei 10608 Taiwan Natl Chung Cheng Univ Dept Elect Engn 168 Univ Rd Chiayi 621 Taiwan

ISBN: (纸本)9783031709654;9783031709661

Traffic accidents are one of the top ten causes of death, with driver fatigue accounting for a significant proportion. Fatigue can lead to reduced attention and slower reaction times. Many professions require frequent nighttime driving, such as truck and taxi drivers, making them particularly a high risk group. Therefore, preventing accidents caused by driver fatigue, especially during nighttime, is a crucial task. Currently, there is limited research and datasets focused on fatigue driving in nighttime scenes. To address this gap we collect nighttime fatigue driving data using an infrared (IR) camera, and propose Unbalanced LocalCNNs for fatigue driving detection in this work. The network architecture can effectively direct the network's attention to different regions based on specific actions caused by fatigue, and result in a 1.6% improvement in accuracy compared to the original models. Furthermore, an adversarial learning mechanism is introduced to enhance the network's robustness, ensuring effective feature extraction in both day and night scenarios. Compared to models without adversarial learning, the overall accuracy is improved by 1.5%. The code is available at https://***/KaiChun-Tu/slow fastDrowsyDriver.

关键词： Fatigue driving detection Infrared images Action recognition Convolutional neural network

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FS-IGA: Feature Selection Method Based on Improved Genetic Algorithm 7th

FS-IGA: Feature Selection Method Based on Improved Genetic A...

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8th Asia Pacific Web and Web-Age information Management Joint International Conference on Web and Big Data

作者： Li, Dong Du, Shumei Wei, Yong Qin, Lei Du, Yuefeng Liaoning Univ Shenyang 110036 Peoples R China

ISBN: (纸本)9789819600540;9789819600557

Feature selection is one of the important techniques of machine learning and data mining. However, with the continuous growth of data scale and application scenarios, the traditional feature selection methods have some defects. In this paper, a Feature Selection method based on Improved Genetic Algorithm (FS-IGA) is proposed. Firstly, the fitness function is improved by introducing the separability criterion based on the distance between classes. Secondly, the decision tree is introduced as the classifier in the genetic algorithm to optimize the performance of the algorithm. Finally, experimental results show that our proposed method can effectively improve the accuracy and adaptability of feature selection. The method presented in this paper boasts of a unique advantage in that it transcends reliance on any specific model framework, thereby ensuring broader applicability. As such, this paper provides a more profound reference value for the research on feature selection in the field of machine learning and data mining.

关键词： Genetic Algorithm Feature Selection Decision Tree Machine Learning Data Mining

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Negotiating with LLMs: Prompt Hacks, Skill Gaps, and Reasoning Deficits 8th

Negotiating with LLMs: Prompt Hacks, Skill Gaps, and Reasoni...

引用

8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Schneider, Johannes Haag, Steffi Kruse, Leona Chandra Univ Liechtenstein Inst Informat Syst Vaduz Liechtenstein Univ Duesseldorf Dusseldorf Germany

ISBN: (纸本)9783031838446;9783031838453

Large language models (LLMs) like ChatGPT have reached the 100 million users' barrier in record time and might increasingly enter all areas of our life leading to a diverse set of interactions between those Artificial Intelligence models and humans. While many studies have discussed governance and regulations deductively from first order principles, few studies provide an inductive, data-driven lens based on observing dialogues between humans and LLMs - especially, when it comes to non-collaborative, competitive situations that have the potential to pose a serious threat for people. In this work, we conduct a user study engaging 41 individuals across all age groups in price negotiations with an LLM. We explore how people interact with an LLM, investigating differences in negotiation outcomes and strategies. Furthermore, we highlight shortcomings of LLMs with respect to their reasoning capabilities and, in turn, susceptiveness to prompt hacking, which intends to manipulate the LLM to make agreements that are against its instructions or beyond any rationality. We also show that the negotiated prices humans manage to achieve span a broad range, which points to a literacy gap in effectively interacting with LLMs.

关键词： Large language model Negotiation Reasoning Prompt Hacking

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Application of the Simulated Annealing Algorithm for Finding the Optimal Trajectory in the Sense of Construction Cost 2nd

Application of the Simulated Annealing Algorithm for Finding...

引用

2nd International Conference on information Technologies and Their Applications

作者： Rychkov, Andrey Abbasov, Majid St Petersburg State Univ SPbSU7-9 Univ Nab St Petersburg 199034 Russia

ISBN: (纸本)9783031734168;9783031734175

We consider variational problem of finding the cost-optimal path on the surface of the terrain. In our model the path is represented as a curve on a plain, while the actual terrain is taken into consideration by the cost function. Our main goal is to obtain an approximate solution as a piecewise linear function via simulated annealing algorithm. For this purpose, we introduce a uniform grid and solve a problem of finding least-cost path with transition prices obtained as the values of the integral cost functional. We adapt the simulated annealing algorithm for this problem and compare its performance with a set of other solutions, namely modified A* and ant colony optimization algorithm. To obtain a better solution we use modifications of the algorithm, such as quantum annealing and stochastic tunneling, which help us improve the performance and avoid getting stuck in the local optima. We also compare the used approaches and provide numerical examples of application of the introduced methods.

关键词： Calculus of Variations Mathematical Modelling Simulated Annealing Optimal Trajectory Quantum Annealing

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Quality Assessment of Fundus Images for Further Classification: Lesson from Thesis 5th

Quality Assessment of Fundus Images for Further Classificati...

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5th International Symposium on Intelligent Computing Systems

作者： Menares, Patricia Castaneda, Victor Univ Santo Tomas Ejercito Libertador 146 Santiago Chile Univ Andres Bello Sazie 2325 Santiago Chile Univ Chile Dept Med Technol Fac Med Av. Independencia 1027 Santiago Chile

ISBN: (纸本)9783031829307;9783031829314

Diabetic retinopathy (DR) is the third leading cause of irreversible blindness worldwide and the leading cause among adults of working age, underscoring the critical need for adequate screening. The quality of the information is a key aspect in any image analysis process and is essential for the correct analysis by automatic processes in pathologies of great importance such as DR. This study aimed to generate a low-cost computational tool that preprocesses fundus images to optimize time in the timely referral of patients. Using two public databases, HDR and DRIMDB, which include both good and poor-quality images, we performed Retinal Image Quality Assessment (RIQA) by analyzing entropy and Peak Signal-to-Noise Ratio (PSNR) under Salt & Pepper and Gaussian Blur noise conditions. Additionally, a vector based on vessel segmentation was created using the Galdran et al. algorithm. The data were evaluated on the WEKA machine learning platform, revealing that neither entropy nor PSNR with Salt & Pepper noise were effective in classifying medically useful images. However, PSNR with Gaussian Blur, especially when combined with vessel segmentation, proved to be a reliable indicator of image quality. These findings suggest that images should be classified as gradable or non-gradable to enhance the efficiency and accuracy of DR screening systems.

关键词： Quality Assessment RIQA Retinography Diabetic retinopathy

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Understanding Human Responses to Robot Errors to Enhance Human-Robot Interaction Design in a Non-industrial Context 8th

Understanding Human Responses to Robot Errors to Enhance Hum...

引用

8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： D'Attanasio, Simona Studzinska, Anna Icam Sch Engn Toulouse Campus75 Ave Grande BretagneCS 97615 F-31076 Toulouse 3 France

ISBN: (纸本)9783031838446;9783031838453

Collaborative robots (cobots) are designed to work alongside humans, offering flexibility and cost-effective solutions with quick and easy programming. Despite their potential, many cobot applications lack true collaboration and are confined to industrial environments. This study investigates human error recovery strategies with cobots in a non-industrial context, using a real-world task from an administrative department. Ten participants interacted with a cobot simulating errors, and their responses were observed. The study employed a Wizard of Oz setup to simulate interaction modalities, including voice control and visual and auditory feedback, and collected data through questionnaires assessing usefulness, user experience, and quality satisfaction. The results indicated high user satisfaction and appreciation for the cobot. Findings reveal that intuitive user-centered interaction is crucial for improving user experience and the adoption of collaborative robots in various professional fields.

关键词： Human-robot interaction Error recovery User-centric design Collaborative robot

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AI Driven Carbon Emission Estimation and Forecasting with Recommended Solution 5th

AI Driven Carbon Emission Estimation and Forecasting with Re...

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5th International Symposium on Intelligent Computing Systems

作者： Tesfai, Micheale H. Tsegai, Milkias Kiflay, Rahel Misghina, Ruta Higher Coll Technol Fujairah U Arab Emirates

ISBN: (纸本)9783031829307;9783031829314

A lot of efforts have been made to prevent potential hazards that could damage our natural resources and spoil our healthy environment. Some of them are preventive actions and policies to reduce carbon emissions. This study will compare different types of forecasting models and discuss the most appropriate ways to forecast carbon emissions in the UAE so that sustainable remedies can be recommended as part of the ongoing endeavor. Currently, artificial intelligence is providing sustainable solutions in almost all areas. Similarly, this tool will be implemented to predict accurate emissions in the next years to take serious actions, which will make the United Arab Emirates an environmentally aware country while providing useful information and implementing preventive policies. Although there are many sources of carbon emissions, this study will use and discuss the total carbon emissions from the transportation sector, but it will also examine methods as well as tools for measuring vehicle emissions. Therefore, the proposed solution will focus on reducing carbon emissions from the transportation sector as well.

关键词： carbon emission forecasting reward

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Closing the Gap: Leveraging Recorded Video Lessons for Digital Inclusion in Rural South Africa 4th

Closing the Gap: Leveraging Recorded Video Lessons for Digit...

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4th International Conference on Society 5.0

作者： Fouche, Rouxan Colin Nel, Wynand Univ Free State Dept Comp Sci & Informat Bloemfontein South Africa

ISBN: (纸本)9783031714115;9783031714122

Access to digital technology and computer literacy skills is crucial in bridging the digital divide, particularly in rural areas where resources are often scarce. This study investigates the feasibility of implementing university service-learning projects in distant rural areas by delivering computer literacy training through recorded video lessons. The project aims to address the South African digital divide by providing essential skills training to community members who lack access to traditional face-to-face educational opportunities. Due to logistical constraints preventing direct student involvement in remote areas, the study explores the effectiveness of utilising recorded video lessons as an alternative delivery method. The findings reveal that face-to-face and recorded video implementations of computer literacy training led to significant improvements for participating community members. Analysis of the data showed that there was no significant difference in the level of improvement between the two methods. These results underscore the potential of recorded video lessons to effectively deliver educational content to remote communities, thereby extending the reach and impact of university service-learning initiatives. The study contributes to efforts to bridge the digital divide in South Africa and offers insights into scalable and sustainable solutions for empowering underserved populations with essential digital skills. This research highlights the importance of innovative approaches to address the challenges of delivering education to remote areas where traditional methods may be impractical or inaccessible. By leveraging technology to disseminate educational content, universities can promote digital inclusion and empower communities to thrive in an increasingly digitised world.

关键词： Access to Education Content Delivery Strategies Community Empowerment computer Literacy Digital Divide Rural Communities Service-Learning

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