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A Study on Cypher Assignment Based on Secrecy Capacity

International Journal of Network Security 2024年第2期26卷 167-172页

作者： Yang, Cheng-Ying Chen, Jong-Shin Yao, Jenq-Foung J F Hwang, Min-Shiang Department of Computer Science University of Taipei Taipei Taiwan Department of Information and Communication Engineering Chaoyang University of Science and Technology Taiwan Computer Science Georgia College and State University Milledgeville United States Department of Computer Science & Information Engineering Asia University Taiwan Fintech and Blockchain Research Center Asia University Taiwan 500 Lioufeng Rd. Wufeng Taichung41354 Taiwan

Accessing wireless services is convenient but not secure. The issue of privacy and security is highly demanded on the internet. The information is sent with the undesired threats of eavesdroppers. Secure communication enables the desired receiver to correctly and successfully receive the information without interruption. In the meantime, a secure system protects the transmitted information from the eavesdroppers. Traditionally, encryption, authorization, and authentication schemes could be employed to protect from eavesdroppers. However, the unanticipated attacks have been developing. According to Shannon’s perfect communication, the undesired receivers, such as eavesdroppers, could receive an error-free cryptogram. Based on the physical-layer security, it could be expected that secure communication could be implemented without complex computing at the higher level. The physical-layer security coding scheme aims to achieve an extremely low decoding error probability and obtain a critical security level against attackers. The positive secrecy capacity (secrecy rate) could provide secure communication. Hence, a positive secrecy capacity is the primary concern in the system. Besides, physical-layer security coding is not only to help the system achieve a critical level of security but also to obtain an extremely low decoding error probability. However, it decreases the bandwidth efficiency and suffers the system performance. Hence, the tradeoff between the security level and the coding rate is important to lead a secure communication. © (2023), (Femto Technique Co.). All Rights Reserved.

关键词： Bandwidth

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A Novel Blockchain-Based Deepfake Detection Method Using Federated and Deep Learning Models

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Cognitive Computation 2024年第3期16卷 1073-1091页

作者： Heidari, Arash Navimipour, Nima Jafari Dag, Hasan Talebi, Samira Unal, Mehmet Department of Software Engineering Haliç University Istanbul34060 Turkey Department of Computer Engineering Kadir Has University Istanbul Turkey Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan Department of Information Technology Kadir Has University Istanbul Turkey Department of Computer Science University of Texas at San Antonio San AntonioTX United States Department of Computer Engineering Nisantasi University Istanbul Turkey

In recent years, the proliferation of deep learning (DL) techniques has given rise to a significant challenge in the form of deepfake videos, posing a grave threat to the authenticity of media content. With the rapid advancement of DL technology, the creation of convincingly realistic deepfake videos has become increasingly prevalent, raising serious concerns about the potential misuse of such content. Deepfakes have the potential to undermine trust in visual media, with implications for fields as diverse as journalism, entertainment, and security. This study presents an innovative solution by harnessing blockchain-based federated learning (FL) to address this issue, focusing on preserving data source anonymity. The approach combines the strengths of SegCaps and convolutional neural network (CNN) methods for improved image feature extraction, followed by capsule network (CN) training to enhance generalization. A novel data normalization technique is introduced to tackle data heterogeneity stemming from diverse global data sources. Moreover, transfer learning (TL) and preprocessing methods are deployed to elevate DL performance. These efforts culminate in collaborative global model training zfacilitated by blockchain and FL while maintaining the utmost confidentiality of data sources. The effectiveness of our methodology is rigorously tested and validated through extensive experiments. These experiments reveal a substantial improvement in accuracy, with an impressive average increase of 6.6% compared to six benchmark models. Furthermore, our approach demonstrates a 5.1% enhancement in the area under the curve (AUC) metric, underscoring its ability to outperform existing detection methods. These results substantiate the effectiveness of our proposed solution in countering the proliferation of deepfake content. In conclusion, our innovative approach represents a promising avenue for advancing deepfake detection. By leveraging existing data resources and the power of FL

关键词： Blockchain

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Feasibility of Integrating Bimetallic Au-Ag Non-Alloys Nanoparticles Embedded in Reduced Graphene Oxide Photodetector

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Photonic Sensors 2023年第3期13卷 23-36页

作者： Nurul Syazwani ROHIZAT Muhammad Nur Syafiq MOHAMAD ISMAIL Muhammad Aiman Saufi AHMAD FAHRI Chee Leong TAN Rozalina ZAKARIA Photonics Research Center Faculty of ScienceUniversity of MalayaKuala Lumpur 50603Malaysia Department of Physics Faculty of ScienceUniversity of MalayaKuala Lumpur 50603Malaysia School of Electronic and Optical Engineering and College of Microelectronics Nanjing University of Posts and TelecommunicationsNanjing 210023China

To coordinate the resonant wavelength of the plasmonic nanoparticles(NPs),the emission band of the reduced graphene oxide(rGO)photodetector at the NIR-region is crucial for the optimal plasmon-enhanced luminescence in the *** contrast to monometallic NPs,where limits the dimensions and extended resonant wavelength,we integrated an Au-Ag bimetallic NPs(BMNPs)to enable resonance tuning at the longer wavelength at the excitation source of 785 *** features showed an increase in radiative recombination rates as well as the quantum yield efficiency of the *** BMNPs were produced from the dewetting process of 600℃and 500℃,both at 1 min after the deposition thickness layer of Au(8 nm)and Ag(10 nm)on the Si substrate using the electron-beam evaporation *** BMNPs-rGO photodetector exhibited the responsivity of 2.25 A·W^(–1),Jones of specific detectivity of 2.45×10^(11)Jones,and external quantum efficiency(EQE)of 356%.The rise time and fall time for the photodetector were 32 ns and 186 ns,*** work provided an essential information to enable the versatile plasmon-enhanced application in 2-dimensional(2D)material optoelectronic devices.

关键词： Au-Ag bimetallic nanoparticles rGO photodetector

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Design of a High-Efficiency Temporal Engine for Real-Time Spatial Satellite Image Classification Using Augmented Incremental Transfer Learning for Crop Analysis

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SN computer science 2024年第5期5卷 585页

作者： Dhande, Akshay Pramodrao Malik, Rahul Saini, Dipen Garg, Rachit Jha, Sudan Nazeer, Jabeen Ahmad, Sultan Department of Electronics and Telecommunication Engineering Lovely Professional University Punjab Phagwara India School of Computer Science and Engineering Lovely Professional University Punjab Phagwara India Department of Computer Science and Engineering Kathmandu University Dhulikhel Nepal Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Alkharj 11942 Saudi Arabia University Center for Research and Development (UCRD) Department of Computer Science and Engineering Chandigarh University Gharuan Punjab Mohali 140413 India

Satellite image processing is a multidomain task which involves design of image capturing, denoising, segmentation, feature extraction, feature reduction, classification, and post-processing tasks. A wide variety of satellite image processing models are proposed by researchers, and each of them has different data and process requirements. For instance, the image capturing module might obtain images in layered form, while feature extraction module might require data in 2D or 3D forms. Moreover, performance of these models also varies due to changes in internal process parameters and dataset parameters, which limits their accuracy and scalability when applied to real-time scenarios. To reduce the probability of these limitations, a novel high-efficiency temporal engine for real-time satellite image classification using augmented incremental transfer learning is proposed and discussed in this text. The model initially captures real-time satellite data using Google’s Earth Engine and processes it using a transfer learning-based convolutional neural network (CNN) via backscatter coefficient analysis. These coefficients indicate average intensity value of Precision Image (PRI) when evaluated over a distributed target. Due to extraction of backscattering coefficients, the model is capable of representing crop images in VV (vertical transmit, vertical receive), and HV (horizontal transmit vertical receive) modes. Thereby assisting the CNN model to extract a wide variety of features from input satellite image, which classifies these datasets (original, VV, and VH) into different crop categories. The classified images are further processed via an incremental learning layer, which assists in visual identification of affected regions. Due to use of incremental learning and CNN for classification, the proposed TRSAITL model is capable of achieving an average accuracy of 97.8% for crop type and severity of damage detection, with an average PSNR (Peak Signal-to-Noise Ratio) of 29.

关键词： Accuracy Classification Crop Damage Deep learning Earth Incremental Precision Recall Satellite Transfer Type

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Knowledge Extraction from Technical Reports Based on Large Language Models: An Exploratory Study 15

Knowledge Extraction from Technical Reports Based on Large L...

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15th International Conference on Information and Knowledge Technology, IKT 2024

作者： Bakhtiari, Parsa Bashiri, Hassan Khalilipour, Alireza Nasiripour, Masoud Challenger, Moharram Department of Computer Engineering Hamedan University of Technology Hamedan Iran Department of Computer Science University of Antwerp Flanders Make Strategic Research Center Antwerp Belgium

ISBN: (纸本)9798331522254

Organizations and companies possess a vast amount of documents generated over the years. These documents contain valuable information and knowledge that can be instrumental in resolving ambiguities and challenges experts face. Information retrieval and knowledge management systems are tools for extracting documents relevant to users’ informational needs, addressing part of the knowledge extraction challenge from these document collections. With the emergence of generative artificial intelligence and large language models that exhibit strong capabilities in understanding textual documents, knowledge extraction solutions have shifted towards utilizing these models. Large language models possess general knowledge obtained from pre-training methods, and there are various approaches to infuse domain-specific knowledge into the general understanding of the language model. This research first examines the possible techniques for fine-tuning a large language model in a specific domain. We then train the model using fine-tuning methods on a collection of documents and technical reports from the industry. Finally, we measure the improvement in the large language model’s capability to extract domain-specific knowledge. © 2024 IEEE.

关键词： Information management

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A 16 nm 140 TOPS/W 5 μj/Inference Keyword Spotting Engine Based on 1D-BCNN

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IEEE Transactions on Circuits and Systems II: Express Briefs 2023年第12期70卷 4564-4568页

作者： Lin, Tay-Jyi Ting, Yi-Hsuan Hsu, Meng-Ze Lin, Kuan-Han Huang, Chung-Ming Tsai, Fu-Cheng Sheu, Shyh-Shyuan Chang, Shih-Chieh Yeh, Chingwei Wang, Jinn-Shyan SoC Research Center AIM-HI Department of Computer Science and Information Engineering Chiayi621 Taiwan SoC Research Center AIM-HI Department of Electrical Engineering Chiayi621 Taiwan Hsinchu300 Taiwan Hsinchu310 Taiwan

This brief presents an event-driven keyword spotting (KWS) system for reducing the significant but usually ignored energy dissipations on the 'always-on' A/D converter and microphone. 'Low energy per inference' and 'fast responsiveness' are new design goals of such KWS engine. A 7-layer 1-dimensional binarized convolutional neural network (1D-BCNN) was designed to achieve 95% inference accuracy for detecting 10 keywords, plus silence and unknown, from raw speech, and 64 32-element signed binary inner product units were allocated in the engine to deliver the 4,096 operations/cycle maximum throughput. The 16nm implementation consumes only 0.1mm2 silicon area and 5μJ /inference energy (including memory accesses), while achieving 1.72ms response time. The performance is comparable to state-of-the-art KWS designs without sacrificing number of detectable keywords or inference accuracy. © 2004-2012 IEEE.

关键词： Energy efficiency

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AdaPIP: Adaptive picture-in-picture guidance for 360° film watching

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Computational Visual Media 2024年第3期10卷 487-503页

作者： Yi-Xiao Li Guan Luo Yi-Ke Xu Yu He Fang-Lue Zhang Song-Hai Zhang Department of Computer Science and Technology Tsinghua UniversityBeijingChinaand Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijingChina Key Laboratory of Space Utilization Technology and Engineering Center for Space UtilizationChinese Academy of SciencesBeijingChina Victoria University of Wellington WellingtonNew Zealand

360°videos enable viewers to watch freely from different directions but inevitably prevent them from perceiving all the helpful *** mitigate this problem,picture-in-picture(PIP)guidance was proposed using preview windows to show regions of interest(ROIs)outside the current view *** identify several drawbacks of this representation and propose a new method for 360° film watching called *** enhances traditional PIP by adaptively arranging preview windows with changeable view ranges and *** addition,AdaPIP incorporates the advantage of arrow-based guidance by presenting circular windows with arrows attached to them to help users locate the corresponding ROIs more *** also adapted AdaPIP and Outside-In to HMD-based immersive virtual reality environments to demonstrate the usability of PIP-guided approaches beyond 2D *** user experiments on 2D screens,as well as in VR environments,indicate that AdaPIP is superior to alternative methods in terms of visual experiences while maintaining a comparable degree of immersion.

关键词： 360°videos picture-in-picture(PIP) virtual reality(VR) visual guidance

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A Survey of Cyber Attacks on Cyber Physical Systems:Recent Advances and Challenges

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 784-800页

作者： Wenli Duo MengChu Zhou Abdullah Abusorrah Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China IEEE Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center and Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz University

A cyber physical system(CPS)is a complex system that integrates sensing,computation,control and networking into physical processes and objects over *** plays a key role in modern industry since it connects physical and cyber *** order to meet ever-changing industrial requirements,its structures and functions are constantly ***,new security issues have arisen.A ubiquitous problem is the fact that cyber attacks can cause significant damage to industrial systems,and thus has gained increasing attention from researchers and *** paper presents a survey of state-of-the-art results of cyber attacks on cyber physical ***,as typical system models are employed to study these systems,time-driven and event-driven systems are ***,recent advances on three types of attacks,i.e.,those on availability,integrity,and confidentiality are *** particular,the detailed studies on availability and integrity attacks are introduced from the perspective of attackers and ***,both attack and defense strategies are discussed based on different system *** challenges and open issues are indicated to guide future research and inspire the further exploration of this increasingly important area.

关键词： Attack detection attack strategy cyber attack cyber physical system(CPS) secure control

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Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun Zhang MengChu Zhou ChenXi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain *** transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each *** one party refuses to do so,the channel is unstable.A stable channel is thus *** nodes may show uncooperative behavior,they may have a negative impact on the stability of such *** order to address this issue,this work proposes a dynamic evolutionary game model based on node *** model considers various defense strategies'cost and attack success ratio under *** can dynamically adjust their strategies according to the behavior of attackers to achieve their effective *** equilibrium stability of the proposed model can be *** proposed model can be applied to general channel *** is compared with two state-of-the-art blockchain channels:Lightning network and Spirit *** experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable *** its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

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Leveraging OpenStack-based Private Cloud for Intrusion Detection Using Deep Learning Techniques 1

Leveraging OpenStack-based Private Cloud for Intrusion Detec...

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1st International Conference for Women in Computing, InCoWoCo 2024

作者： Roshan, Rahul G. Salanke, Vishal S Nagasundari, S. Research Center for Information Security Forensics and Cyber Resilience PES University Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331518943

OpenStack is a cloud platform that offers infrastructure services, providing access to computing, storage, and network resources. However, due to its open-source nature, the cloud environment can be vulnerable to security threats. OpenStack security measures are generally applied to specific services, rather than being integrated comprehensively across the entire cloud environment. Despite offering flexibility and scalability, the widespread use of OpenStack calls for robust security solutions. Current intrusion detection systems often struggle to adapt to constantly evolving traffic patterns and attack vectors in the OpenStack environment. This study introduces a two-stage deep learning framework to create a robust Intrusion Detection System (IDS) for OpenStack-based private clouds. The proposed framework efficiently analyzes network traffic data in these clouds by implementing dimensionality reduction and anomaly detection techniques. It utilizes a network-based IDS, trained on two publicly available datasets, which enables a broader detection range of known attack patterns. The results indicate that the OpenStack IDS significantly enhances OpenStack's security, addressing the limitations of generic IDS solutions. © 2024 IEEE.

关键词： Network intrusion

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