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Computing, Power and Communication Technologies (IC2PCT), IEEE International Conference on

作者： S. Ambika V. Balaji R.Thalapathi Rajasekaran P.N. Periyasamy N. Kamal Department of Information Technology E. G. S. Pillay Engineering College Nagapattinam Tamil Nadu India Department of CSE (Cyber Security) Easwari Engineering College Chennai India Dept. of Computer Science and Engineering Saveetha School of Engineering SIMATS Chennai India Department of Computer Science and Engineering Hindusthan Institute of Technology India Dept. of Computer Science and Engineering GRT Institute of Engineering and Technology Tiruttani Tamil Nadu India

The revolutionary effects of quantum computing on security procedures for networks and cryptographic protocols are the focus of this study. Our research shows that conventional cryptographic algorithms are susceptible to quantum assaults; specifically, RSA and ECC encryption are very vulnerable. On the other hand, cryptographic algorithms that are immune to quantum attacks, such as multivariate polynomial cryptography and lattice-based algorithms, show promise in meeting these challenges. Key exchange rates between 200 kbps and 450 kbps and error rates as low as 0.5% are some of the significant achievements shown by Quantum Key Distribution (QKD) implementations. These applications show that QKD is a viable solution for protecting communication channels up to 200 km away. On top of that, there are remarkable outcomes when network security systems incorporate quantum advancements. The detection accuracy of Quantum-Enhanced Intrusion Detection Systems (QIDS) is 98.5% and the false positive rate is minimally 0.2%. The detection accuracy of quantum-secured communication systems is 99.2% and the false positive rate is an extremely low 0.1%. While quantum firewalls keep a detection accuracy of 97.8% and a false positive rate of 0.3%, quantum-safe cryptographic modules show a low latency of 3 ms.

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Research on the Characteristics and security Risks of the Internet of Vehicles Data 7

Research on the Characteristics and Security Risks of the In...

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7th IEEE International Conference on Data Science in cyberspace, DSC 2022

作者： Sun, Jun Liu, Dong Liu, Yang Li, Chuang Ma, Yumeng Institute of Network Security Inspection and Evaluation China Industrial Control System Cyber Emergency Response Team Beijing China University of Electronic Science and Technology of China School of Computer Science and Engineering Szechwan China

ISBN: (数字)9781665474801

ISBN: (纸本)9781665474801

As a new industry integrated by computing, communication, networking, electronics, and automation technology, the Internet of Vehicles (IoV) has been widely concerned and highly valued at home and abroad. With the rapid growth of the number of intelligent connected vehicles, the data security risks of the IoV have become increasingly prominent, and various attacks on data security emerge in an endless stream. This paper firstly introduces the latest progress on the data security policies, regulations, standards, technical routes in major countries and regions, and international standardization organizations. Secondly, the characteristics of the IoV data are comprehensively analyzed in terms of quantity, standard, timeliness, type, and cross-border transmission. Based on the characteristics, this paper elaborates the security risks such as privacy data disclosure, inadequate access control, lack of identity authentication, transmission design defects, cross-border flow security risks, excessive collection and abuse, source identification, and blame determination. And finally, we put forward the measures and suggestions for the security development of IoV data in China. © 2022 IEEE.

关键词： Vehicles

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Unveiling Deception: Different Strategies for Combatting Arabic Fake News 25

Unveiling Deception: Different Strategies for Combatting Ara...

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25th International Arab Conference on Information technology, ACIT 2024

作者： Khattab, Nada Al-Qerem, Ahmad Nashwan, Shadi Jebreen, Issam Rajab, Mohammed Alauthman, Mohammad Jeadi, Mohammad Elrashidi, Ali Zarqa University Faculty of Information Technology Computer Science Department Zarqa13110 Jordan Middle East University Faculty of Information Technology Cybersecurity Department Amman11831 Jordan University Headquarter University of Anbar Ramadi Iraq University of Petra Department of Information Security Amman11196 Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

the proliferation of fake news has become a widespread problem in the contemporary era of information, posing possible harm to public discussions, political stability, and community confidence. To tackle this difficulty, it is necessary to develop strong and effective detection methods that can accurately recognize misinformation in several languages, including Arabic. The aim of this study is to create and assess different models specifically designed for the identification of fake news in Arabic *** of deep Learning models like Recurrent Neural Networks (RNN), Long short-term memory (LSTM), Bidirectional long short term memory (Bi-LSTM) and convolutional neural network (CNN) are used in this study. On the other hand, some of the traditional machine learning models like k-nearest neighbors (KNN), Random Forests (RF), Extreme Gradient Boosting (XGBoost), decision tree (DT) and multi-layer perceptron (MLP) are also used. Also, transformers, like Generative pre-trained Transformer 3 (Gpt-3) and Bidirectional Encoder Representations from Transformers (BERT), are used as a feature extraction to convert text into numerical representation and assign different number to each token. All of these models were used in evaluation which of them is the best model in the process of fake news detection for the Arabic Language *** findings demonstrate strong performance across deep learning models, with CNN-LSTM, Bi-LSTM and CNN-Bi-LSTM exhibiting the best accuracy rates of 93.2% ,92.6%, 93.6% respectively. The LSTM model achieves a moderate accuracy of 87.4%, whilst the RNN model demonstrates a more modest accuracy of 56.8%. The results emphasize the capability of deep learning methods in reducing the dissemination of fake information in Arabic-language datasets. © 2024 IEEE.

关键词： Long short-term memory

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CDE-Learning: Camera Deviation Elimination Learning for Unsupervised Person Re-identification 39

CDE-Learning: Camera Deviation Elimination Learning for Unsu...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Peng, Jinjia Zhang, Songyu Wang, Huibing School of Cyber Security and Computer Hebei University Hebei China Hebei Machine Vision Engineering Research Center China College of Information Science and Technology Dalian Maritime University China

ISBN: (纸本)157735897X

Unsupervised Person Re-identification (Re-ID) aims to identify the same person shot from non-overlapping cameras without any annotated data. In this task, attributes such as contrast, saturation, and resolution of the camera cause the deviation in the target features. Since the camera label is readily available, they are employed to achieve the constraints across cameras and smooth the deviations during the model training phase. However, features from the same camera are prone to generating false positives due to the identical camera properties, which induce camera deviations on pseudo-label assignment. To address this problem, this paper proposes a novel camera-unbiased method named Camera Deviation Elimination Learning (CDE-Learning). In the method, the Camera Deviation Compensation (CDC) module is designed to align data distributions from disparate cameras. This alignment decouples camera information from identity information during the pseudo-label allocation. Our Camera Deviation Balancing (CDB) module integrates different camera constraints in a united loss and adjusts camera constraints by constructing contrastive pairs between intra-camera and inter-camera. After explicit constraints, the Camera Attribution Auxiliary (CAA) task predicts whether a pair of images originate from the same camera to implicitly enhance the capacity to distinguish the camera deviation. We demonstrated the superior performance of the proposed CDE-Learning on benchmark datasets. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Unsupervised learning

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CAViaR Secretary Bird Optimization Algorithm Enabled Transfer Learning for Melanoma Classification

CAViaR Secretary Bird Optimization Algorithm Enabled Transfe...

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IEEE EMBS Conference on Biomedical engineering and Sciences (IECBES)

作者： P. Vijaya Basant Kumar Joseph Mani Satish Chander Roshan Fernandes Hothefa Jassim Dilip Kumar Singvi Department of Mathematics and Computer Science Modern College of Business and Science Bowshar Sultanate of Oman Department of Computer Science and Engineering Birla Institute of Technology Mesra Ranchi India Department of Cyber Security NMAMIT Karkala Karnataka India Department of Internal medicine Burjeel Hospital Oman

ISBN: (数字)9798350383409

ISBN: (纸本)9798350383416

Melanoma is one amongst aggressive diseases with some ordinary treatment choices. The fatality rates and their occurrence vary expansively around the world relying upon access to earlier identification and basic medical care. The significant demerits of the existing classification models are a lack of predictive significance and a small relationship with treatment results. Here, CAViaR Secretary Bird Optimization Algorithm enabled Transfer Learning (CSBOA_TL) is introduced for melanoma classification. Firstly, an Adaptive Kalman Filter (AKF) is utilized to pre-process input skin images. After pre-processing, skin lesion segmentation is conducted employing Deep Fuzzy Clustering (DFC). Thereafter, statistical features, Oriented FAST Rotated and BRIEF (ORB) and Haralick features are extracted. Lastly, melanoma classification is conducted by Convolutional Neural Network (CNN) based TL, where CNN is utilized with fetched hyperparameters from EfficientNet. The CNN-based TL is trained utilizing the CAViaR Secretary Bird Optimization Algorithm (CSBOA), which is presented by incorporating Conditional Autoregressive Value at Risk (CAViaR) with Secretary Bird Optimization Algorithm (SBOA). Additionally, CSBOA_TL achieved a maximal accuracy of 91.852%, a True Negative Rate (TNR) of 92.788% and a True Positive Rate (TPR) of 90.715%.

关键词： Accuracy Clustering algorithms Melanoma Feature extraction Birds Skin Classification algorithms Convolutional neural networks Lesions Optimization

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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Yajun Li, Ru Li, Aimin Fei, Rong Guo, Xie Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China University of Saskatchewan Division of Biomedical Engineering Department of Computer Science Department of Mechanical Engineering Saskatoon Canada

ISBN: (纸本)9798350337488

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions. © 2023 IEEE.

关键词： interactive inference network noncoding RNA piRNA-mRNA interactions positive-unlabeled learning

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Backdoor-Resistant Public Data Integrity Verification Scheme Based on Smart Contracts

Backdoor-Resistant Public Data Integrity Verification Scheme...

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作者： Li, Shanshan Xu, Chunxiang Zhang, Yuan Du, Yicong Yang, Anjia Wen, Xinsheng Chen, Kefei Zhongnan University of Economics and Law School of Information and Safety Engineering Wuhan430073 China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China University of Electronic Science and Technology of China Yangtze Delta Region Institute Huzhou313001 China Jinan University College of Cyber Security Guangzhou510632 China Hangzhou Normal University Department of Mathematics Hangzhou310030 China

This article analyzes existing smart contract-based public data integrity verification schemes and identifies certain weaknesses. First, the fair arbitration mechanism deployed in these schemes fails to meet the users' requirements as it may not promptly notify users of data corruption or loss. Second, to ensure outsourced data confidentiality, existing data integrity schemes use a conventional encrypted method, where each user randomly selects a key to encrypt the outsourced data. Such a method results in varying ciphertexts for the same data by different users, leading to additional storage costs for the cloud server. Third, users' devices, if poorly designed or even intentionally backdoored, can potentially exfiltrate secrets and compromise the security of schemes. To address these issues, we propose the first backdoor-resistant public data integrity verification scheme based on smart contracts (ASSIST). The key idea is to introduce a new entity (a whistleblower) to periodically monitor the state of verification results recorded in the blockchain. This allows for timely notification of data corruption to users. ASSIST requires users to encrypt their data with a cryptographic primitive called message-locked encryption (MLE), which motivates different users to produce the same ciphertext for the same data and reduces storage costs for cloud servers. We also deploy a cryptographic reverse firewall between users' devices and the external to rerandomize interactive messages, making the exfiltration impossible. We provide rigorous security proofs to demonstrate the security of ASSIST. The performance evaluation shows that ASSIST is efficient regarding computation and communication costs. © 2014 IEEE.

关键词： Smart contract

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Enumeration and Post-Enumeration Attack on Active Directory and Their Detection Using log Correlation Method

Enumeration and Post-Enumeration Attack on Active Directory ...

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International Conference on Computation System and Information technology for Sustainable Solutions (CSITSS)

作者： K Meghana Shankaramma M.N. Thippeswamy A M Anu M Chaithra N Nagamani Computer Science and Engineering (Cyber Security) M S Ramaiah Institute of Technology (Affiliated to VTU) Bangalore India Dr. Ambedkar Institute of Technology (Dr. AIT) Bangalore India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

Microsoft Active Directory Domain Services (AD DS) is a cornerstone of IT infrastructure in many organizations due to its widespread use and comprehensive feature set. AD DS centralizes network management, streamlines user authentication, and simplifies access control, thereby enhancing the efficiency of IT operations. However, its ubiquity and critical role also make it a prime target for attackers. This study delves into the Kerberos authentication protocol, which is often exploited in various attacks on AD DS. It investigates techniques used for enumeration and post-enumeration activities in AD environments and proposes strategies for detecting and mitigating these security threats. Furthermore, an experimental setup has been developed to demonstrate examples of these attacks. Addressing the challenge of detecting and thwarting enumeration and post-enumeration attacks is crucial, as it is vital to intercept attackers during the early stages of their attempts. This resource aims to be a comprehensive guide for IT security professionals managing Microsoft AD environments, providing essential insights into securing their systems against such threats.

关键词： Access control Protocols Correlation Authentication Organizations Machine learning Real-time systems Information technology Monitoring

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cyberbullying Detection and Recognition with Type Determination Based on Machine Learning

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computers, Materials & Continua 2023年第6期75卷 5307-5319页

作者： Khalid M.O.Nahar Mohammad Alauthman Saud Yonbawi Ammar Almomani Computer Science Department Yarmouk UniversityIrbidJordan Department of Information Security Faculty of Information TechnologyUniversity of PetraAmmanJordan Software Engineering Department University of JeddahJeddahKSA Research and Innovation Department Skyline University CollegeP.O.Box 1797SharjahUAE IT Department-Al-Huson University College Al-Balqa Applied UniversityP.O.Box 50IrbidJordan

Social media networks are becoming essential to our daily activities,and many issues are due to this great involvement in our *** is a social media network issue,a global crisis affecting the victims and society as a *** results from a misunderstanding regarding freedom of *** this work,we proposed a methodology for detecting such behaviors(bullying,harassment,and hate-related texts)using supervised machine learning algo-rithms(SVM,Naïve Bayes,Logistic regression,and random forest)and for predicting a topic associated with these text data using unsupervised natural language processing,such as latent Dirichlet *** addition,we used accuracy,precision,recall,and F1 score to assess prior *** show that the use of logistic regression,support vector machine,random forest model,and Naïve Bayes has 95%,94.97%,94.66%,and 93.1%accuracy,respectively.

关键词： cyberbullying social media naïve bayes support vector machine natural language processing LDA

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Quantum Remote State Preparation Based on Quantum Network Coding

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computers, Materials & Continua 2022年第10期73卷 119-132页

作者： Zhen-Zhen Li Zi-Chen Li Yi-Ru Sun Haseeb Ahmad Gang Xu Xiu-Bo Chen School of Information Engineering Beijing Institute of Graphic CommunicationBeijing102600China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Information Security Center State key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Department of Computer Science National Textile UniversityFaisalabad37610Pakistan School of Information Science and Technology North China University of TechnologyBeijing100144China Advanced Cryptography and System Security Key Laboratory of Sichuan Province China

As an innovative theory and technology,quantum network coding has become the research hotspot in quantum network *** this paper,a quantum remote state preparation scheme based on quantum network coding is *** with the general quantum remote state preparation schemes,our proposed scheme brings an arbitrary unknown quantum state finally prepared remotely through the quantum network,by designing the appropriate encoding and decoding steps for quantum network *** is worth mentioning,from the network model,this scheme is built on the quantum k-pair network which is the expansion of the typical bottleneck network—butterfly ***,it can be treated as an efficient quantum network preparation scheme due to the characteristics of network coding,and it also makes the proposed scheme more applicable to the large-scale quantum *** addition,the fact of an arbitrary unknown quantum state remotely prepared means that the senders do not need to know the desired quantum ***,the security of the proposed scheme is ***,this scheme can always achieve the success probability of 1 and 1-max flow of value ***,the communication efficiency of the proposed scheme is ***,the proposed scheme turns out to be practicable,secure and efficient,which helps to effectively enrich the theory of quantum remote state preparation.

关键词： Quantum remote state preparation quantum network coding quantum k-pair network

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