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30th Annual Network and Distributed System Security Symposium, NDSS 2023

作者： Chen, Tianyang Xu, Peng Picek, Stjepan Luo, Bo Susilo, Willy Jin, Hai Liang, Kaitai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Cluster and Grid Computing Lab School of Computer Science and Technology China Huazhong University of Science and Technology Wuhan430074 China Digital Security Group Radboud University Nijmegen Netherlands Department of EECS Institute of Information Sciences The University of Kansas LawrenceKS United States Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

ISBN: (纸本)1891562835

Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studies a new and practical security risk to DSSE, namely, secret key compromise (e.g., a user’s secret key is leaked or stolen), which threatens all the security guarantees offered by existing DSSE schemes. To address this open problem, we introduce the notion of searchable encryption with key-update (SEKU) that provides users with the option of non-interactive key updates. We further define the notion of post-compromise secure with respect to leakage functions to study whether DSSE schemes can still provide data security after the client’s secret key is compromised. We demonstrate that post-compromise security is achievable with a proposed protocol called "Bamboo". Interestingly, the leakage functions of Bamboo satisfy the requirements for both forward and backward security. We conduct a performance evaluation of Bamboo using a real-world dataset and compare its runtime efficiency with the existing forward-and-backward secure DSSE schemes. The result shows that Bamboo provides strong security with better or comparable performance. © 2023 30th Annual Network and Distributed System Security Symposium, NDSS 2023. All Rights Reserved.

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MF-MOS: A Motion-Focused Model for Moving Object Segmentation

MF-MOS: A Motion-Focused Model for Moving Object Segmentatio...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jintao Cheng Kang Zeng Zhuoxu Huang Xiaoyu Tang Jin Wu Chengxi Zhang Xieyuanli Chen Rui Fan School of Electronic and Information Engineering South China Normal University Foshan China Department of Computer Science Aberystwyth University Aberystwyth U.K. Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong China School of Internet of Things Engineering Jiangnan University Wuxi China College of Intelligence Science and Technology National University of Defense Technology Changsha China College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems the State Key Laboratory of Intelligent Autonomous Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Moving object segmentation (MOS) provides a reliable solution for detecting traffic participants and thus is of great interest in the autonomous driving field. Dynamic capture is always critical in the MOS problem. Previous methods capture motion features from the range images directly. Differently, we argue that the residual maps provide greater potential for motion information, while range images contain rich semantic guidance. Based on this intuition, we propose MF-MOS, a novel motion-focused model with a dual-branch structure for LiDAR moving object segmentation. Novelly, we decouple the spatial-temporal information by capturing the motion from residual maps and generating semantic features from range images, which are used as movable object guidance for the motion branch. Our straightforward yet distinctive solution can make the most use of both range images and residual maps, thus greatly improving the performance of the LiDAR-based MOS task. Remarkably, our MF-MOS achieved a leading IoU of 76.7% on the MOS leaderboard of the SemanticKITTI dataset upon submission, demonstrating the current state-of-the-art performance. The implementation of our MF-MOS has been released at https://***/SCNU-RISLAB/MF-MOS.

关键词： Laser radar Semantics Dynamics Object segmentation Data augmentation Data models Reliability

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Using Deep Reinforcement Learning in Optimal Energy Management for Residential House Aggregators with Uncertain User Behaviors

Using Deep Reinforcement Learning in Optimal Energy Manageme...

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IEEE Student Conference on Electric Machines and systems

作者： Yujun Lin Linfang Yan Hongxun Hui Yin Chen Xia Chen Jinyu Wen State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China State Grid (Suzhou) City & Energy Research Institute Suzhou China Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau Macau China Department of Electronic and Electrical Engineering University of Strathclyde Glasgow U.K.

ISBN: (数字)9798350366945

ISBN: (纸本)9798350366952

In this study, the home energy management problem, which can be regarded as a high-dimensional optimization problem, for numerous residential houses, is addressed. The concept of the aggregator is utilized to reduce the state and action space and to handle the high dimensionality. A two-stage deep reinforcement learning (DRL)-based approach is proposed for the aggregators to track the schedule from a superior grid and guarantee the operation constraints. In the first stage, a DRL control agent is set to learn the optimal scheduling strategy interacting with the environment based on the soft-actor-critic framework and generate the aggregate control actions. In the second stage, the aggregate control actions are disaggregated to individual appliances considering the users' behaviors. The uncertainty of an electric vehicle's charging demand is quantitatively expressed based on the driver's experience. An aggregate anxiety concept is introduced to characterize the driver's anxiety on the electric vehicle's range and uncertain events. Finally, simulations are conducted to verify the effectiveness of the proposed approach under dynamic user behaviors, and comparisons show the superiority of the proposed approach over other benchmark methods.

关键词： Schedules Uncertainty Aggregates Anxiety disorders Optimal scheduling Deep reinforcement learning Electric vehicle charging Temperature control Vehicle dynamics Resistance heating

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Information Security and Privacy in the Digital World: Some Selected Topics

arXiv

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arXiv 2024年

作者： Sen, Jaydip Mayer, Joceli Dasgupta, Subhasis Nandi, Subrata Krishnaswamy, Srinivasan Mitra, Pinaki Singh, Mahendra Pratap Kundeti, Naga Prasanthi Rao, Chandra Sekhara M.V.P. Chekuri, Sudha Sree Pallapothu, Seshu Babu Nanjundan, Preethi George, Jossy P. Allali, Abdelhadi E.I. Morino, Ilham Oussous, Salma A.I.T. Beloualid, Siham Tamtaoui, Ahmed Bajit, Abderrahim Department of Data Science Praxis Business School Kolkata India Department of Computer Science and Engineering IIT Guwahati Assam India Department of Electronics and Electrical Engineering IIT Guwahati Assam India Department of Computer Science and Engineering National Institute of Technology Karnataka Surathkal Mangaluru India Department of CSE Lakireddy Balireddy College of Engineering Affiliated to JNTU Mylavaram Kakinada India Department of CSE RVR & JC college of Engineering Guntur India Department of Mathematics and statistics K.B.N. College Vijayawada India Department of Electrical Engineering Federal University of Santa Catarina Florianópolis Brazil Department of Data Science Christ University Lavasa Pune India National School of Applied Sciences Kenitra Morocco SC Department Mohammed V University Laboratory of Advanced Systems National Institute of Posts and Telecommunications Rabat Morocco

In the era of generative artificial intelligence and the Internet of Things,while there is explosive growth in the volume of data and the associated needfor processing, analysis, and storage, several new challenges are faced inidentifying spurious and fake information and protecting the privacy ofsensitive data. This has led to an increasing demand for more robust andresilient schemes for authentication, integrity protection, encryption,non-repudiation, and privacy-preservation of data. The chapters in this bookpresent some of the state-of-the-art research works in the field ofcryptography and security in computing and communications. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital storage

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FetalDiffusion: Pose-Controllable 3D Fetal MRI Synthesis with Conditional Diffusion Model

arXiv

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arXiv 2024年

作者： Zhang, Molin Golland, Polina Grant, P. Ellen Adalsteinsson, Elfar Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Computer Science and Artificial Intelligence Laboratory MIT CambridgeMA United States Fetal-Neonatal Neuroimaging and Developmental Science Center Boston Children’s Hospital BostonMA United States Harvard Medical School BostonMA United States Institute for Medical Engineering and Science MIT CambridgeMA United States

The quality of fetal MRI is significantly affected by unpredictable and substantial fetal motion, leading to the introduction of artifacts even when fast acquisition sequences are employed. The development of 3D real-time fetal pose estimation approaches on volumetric EPI fetal MRI opens up a promising avenue for fetal motion monitoring and prediction. Challenges arise in fetal pose estimation due to limited number of real scanned fetal MR training images, hindering model generalization when the acquired fetal MRI lacks adequate pose. In this study, we introduce FetalDiffusion, a novel approach utilizing a conditional diffusion model to generate 3D synthetic fetal MRI with controllable pose. Additionally, an auxiliary pose-level loss is adopted to enhance model performance. Our work demonstrates the success of this proposed model by producing high-quality synthetic fetal MRI images with accurate and recognizable fetal poses, comparing favorably with in-vivo real fetal MRI. Furthermore, we show that the integration of synthetic fetal MR images enhances the fetal pose estimation model’s performance, particularly when the number of available real scanned data is limited resulting in 15.4% increase in PCK and 50.2% reduced in mean error. All experiments are done on a single 32GB V100 GPU. Our method holds promise for improving real-time tracking models, thereby addressing fetal motion issues more effectively. Copyright © 2024, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Dispersion compensating fiber with Brillouin fiber laser generation

Dispersion compensating fiber with Brillouin fiber laser gen...

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Communication and Information Technology (AICCIT), Al-Sadiq International Conference on

作者： Hasanain Naser Abd Ali Sulaiman Wadi Harun Norhana Arsad Taj-Aldeen Naser Abdali Ahmed Salih Al-Khaleefa Mustafa H Hassan Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Malaysia Department of Electrical Engineering Photonics Engineering Laboratory Faculty of Engineering University of Malaya Kuala Lumpur Malaysia Department of Electronic Computer Center University of Misan Misan Iraq Department of Physics Faculty of Education University of Misan Misan Iraq Department of Computer Technical Engineering College of Information Technology Imam Ja’afar Al-Sadiq University Al-Muthanna Iraq

Short linewidth light lasers are essential for a wide range of applications, including quantum computing, spectroscopy, and sensing. Stimulated Brillouin scattering is an intriguing method for achieving extremely coherent light laser output. The demonstration of an unstable pulsed Brillouin erbium fiber laser (BFL) operating at kHz is shown here. The BFL works at 1550.1 nm, which is 0.09 nm higher than the Brillouin pump wavelength since the dispersion compensating fiber was pumped over the 24.77 mW threshold. It has an extreme power of 0.7 dBm, a side-mode suppression ratio of 29 dB, and a pump power of 59.12 mW at 980 nm. Due to the intrinsic instability in relaxation oscillation, which generates the nonlinear self-pulsing mechanism in the BEFL cavity, the BEFL produced a pulse train running at 200.9 kHz with a 24.77 mW pump. The pulse frequency was raised to 3.02 MHz. The pump power has been increased to 59.12 mW. Yet, as the pump power was raised further, more than one pulse was produced. This is the first example of generating kHz pulses in a BFL cavity. The laser system is straightforward, small, and all-fiber. These are the attempts of experimental work to realize the BFL with Q-switched multi-wavelength output using a specific length of DCF to generate the pulses.

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Current-induced Néel order switching facilitated by magnetic phase transition

Current-induced Néel order switching facilitated by magneti...

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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Hao Wu Hantao Zhang Baomin Wang Yaqin Guo Ran Cheng Kang L. Wang Songshan Lake Materials Laboratory Dongguan China Department of Electrical and Computer Engineering University of California Los Angeles CA USA Department of Electrical and Computer Engineering University of California Riverside CA USA School of Physical Science and Technology Ningbo University Ningbo China CAS Key Laboratory of Magnetic Materials and Devices Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China

Antiferromagnetic materials (AFMs), which have zero-stray field and the THz-range magnetic resonance frequency, are promising candidates for the next-generation magnetic memory technology. Here, we report an electrical writing of antiferromagnetic orders through a record-low current density on the order of 10 6 A cm -2 facilitated by the unique AFM-ferromagnetic (FM) phase transition in FeRh. The spin-orbit torque can switch the AFM order parameter by 90° with a reduced writing current density by introducing a transient FM state via current-induced Joule heating. This work demonstrates the exciting possibility of writing operations in AFM-based devices with a lower current density, opening a new pathway toward pure AFM memory applications.

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Operando FTIR study on water additive in lithium-sulfur batteries to mitigate shuttle effect

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Journal of Energy Chemistry 2024年第11期98卷 702-713页

作者： Érick A.Santos Martim C.Policano Manuel J.Pinzón Isabela Galantini Vanessa A.Goncalves Francisco C.B.Maia Lucyano J.A.Macedo Gustavo Doubek Renato G.Freitas Hudson Zanin Advanced Energy Storage Division Center for Innovation on New EnergiesSchool of Electrical and Computer EngineeringUniversity of CampinasAv Albert Einstein 400CampinasSP 13083-852Brazil Catalytic Processes and Materials Group Department of Chemical EngineeringFaculty of Science and TechnologyMESA+Institute for NanotechnologyUniversity of TwentePO Box 2177500 AE EnschedeThe Netherlands Centre for Cooperative Research on Alternative Energies(CIC EnergiGUNE) Basque Research and Technology Alliance(BRTA)Vitoria-Gasteiz 01510Spain Institute of Physics&Institute of Chemistry Laboratory of Computational MaterialsFederal University of Mato GrossoCuiabá78060-900MTBrazil Brazilian Synchrotron Light Laboratory Brazilian Center for Research in Energy and MaterialsCampinas 13083-970SPBrazil Advanced Energy Storage Division LABCenter for Innovation on New EnergiesSchool of Chemical EngineeringUniversity of CampinasAv Albert Einstein 500Campinas 13083-852SPBrazil

Additives in the electrolytes of Li-S batteries aim to increase overall capacity,improve Li ion conductivity,enhance cyclability,and mitigate the shuttle effect,which is one of the major issues of this ***,the use of water as an additive in the commonly used electrolyte,1.0 M LiTFSI/1.0%(w/w) LiNO_(3) and a 1:1 mixture of 1,3-dioxolane(DOL) and 1,2-dimethoxyethane(DME) was *** used Co_(2)Mn_(0.5)Al_(0.5)O_(4)(CMA) as an electrocatalyst anchored on an activated carbon(AC) electrode with added sulfur via a melt-diffusion *** structural analysis of CMA via Rietveld refinement showed interatomic spaces that can promote ionic conductivity,facilitating Li^(+) ion *** tests determined 1600 ppm as the optimal water concentration,significantly reducing the shuttle ***-mortem XPS analysis focused on the lithium metal anode revealed the formation of Li_(2)O layers in dry samples and LiOH in wet *** capacity was observed in wet samples,which can be attributed to the superior ionic conductivity of LiOH at the electrode/electrolyte interface,surpassing that of Li_(2)O by 12 ***,Operando FTIR experiments provided real-time insights into electrolyte degradation and SEI formation,elucidating the activity mechanisms of water and Li_(2)CO_(3) over the *** work presents results that could aid future advancements in Li-S battery technology,offering possibilities to mitigate its challenges with inexpensive and scalable additives.

关键词： Diffusion Li-S Ionic conductivity Operando FTIR

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Reinforcement of Medical Image Security Through Steganography and Encryption Techniques

Reinforcement of Medical Image Security Through Steganograph...

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Electronic engineering (ICEEM), International Conference on

作者： Fatma Khallaf Walid El-Shafai El-Sayed M. El-Rabaie Fathi E. Abd El-Samie Department of Electronics and Communication Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Electrical Engineering Faculty of Engineering Ahram Canadian University Giza Egypt Department of Computer Science Security Engineering Laboratory Prince Sultan University Riyadh Saudi Arabia

Patients' data is stored in Electronic Health Records (EHRs) for confidentiality purposes. However, the insecure networks of hospitals and clinics puts patient information at risk. To address this ethical issue, secure communication is crucial. The Digital Imaging and Communications in Medicine (DICOM) standard governs the transmission of EHRs to maintain data integrity and confidentiality. This paper combines cryptography and steganography techniques to transmit medical information and images across hospital networks, securely. The introduced framework comprises encryption of patients' data using DNA-based Advanced Encryption Standard (AES), hiding the information within images using Least Significant Bit (LSB) embedding, compressing the stego images using Discrete Wavelet Transform (DWT), and reversal of the process at the receiver end. Simulation experiments demonstrate that this framework comprising both encryption and steganography outperforms existing methods in securing the medical data.

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Triple Point Masking

arXiv

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arXiv 2024年

作者： Liu, Jiaming Kong, Linghe Wu, Yue Gong, Maoguo Li, Hao Miao, Qiguang Ma, Wenping Qin, Can School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China School of Computer Science and Technology Key Laboratory of Collaborative Intelligence Systems Ministry of Education Xidian University Xi’an710071 China School of Electronic Engineering Key Laboratory of Collaborative Intelligence Systems Ministry of Education Xidian University Xi’an710071 China College of Mathematics Science Inner Mongolia Normal University Hohhot010022 China School of Artificial Intelligence Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi’an710071 China Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States

Existing 3D mask learning methods encounter performance bottlenecks under limited data, and our objective is to overcome this limitation. In this paper, we introduce a triple point masking scheme, named TPM, which serves as a scalable plug- and-play framework for MAE pre-training to achieve multi-mask learning for 3D point clouds. Specifically, we augment the baseline methods with two additional mask choices (i.e., medium mask and low mask) as our core insight is that the recovery process of an object can manifest in diverse ways. Previous high-masking schemes focus on capturing the global representation information but lack fine-grained recovery capabilities, so that the generated pre-training weights tend to play a limited role in the fine-tuning process. With the support of the proposed TPM, current methods can exhibit more flexible and accurate completion capabilities, enabling the potential autoencoder in the pre-training stage to consider multiple representations of a single 3D point cloud object. In addition, during the fine-tuning stage, an SVM-guided weight selection module is proposed to fill the encoder parameters for downstream networks with the optimal weight, maximizing linear accuracy and facilitating the acquisition of intricate representations for new objects. Extensive experimental results and theoretical analysis show that five baselines equipped with the proposed TPM achieve comprehensive performance improvements on various downstream tasks. Our code and models are available at https://***/liujia99/TPM. © 2024, CC BY.

关键词： Signal encoding

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