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Artificial intelligence in physiological characteristics recognition for internet of things authentication

Digital Communications and Networks 2024年第3期10卷 740-755页

作者： Zhimin Zhang Huansheng Ning Fadi Farha Jianguo Ding Kim-Kwang Raymond Choo School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Beijing Engineering Research Center for Cyberspace Data Analysis and Applications Beijing100083China Faculty of Informatics Engineering Aleppo UniversityAleppoSyria Department of Computer Science Blekinge Institute of Technology37179KarlskronaSweden Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249-0631USA

Effective user authentication is key to ensuring equipment security,data privacy,and personalized services in Internet of Things(IoT)***,conventional mode-based authentication methods(e.g.,passwords and smart cards)may be vulnerable to a broad range of attacks(e.g.,eavesdropping and side-channel attacks).Hence,there have been attempts to design biometric-based authentication solutions,which rely on physiological and behavioral *** characteristics need continuous monitoring and specific environmental settings,which can be challenging to implement in ***,we can also leverage Artificial Intelligence(AI)in the extraction and classification of physiological characteristics from IoT devices processing to facilitate ***,we review the literature on the use of AI in physiological characteristics recognition pub-lished after *** use the three-layer architecture of the IoT(i.e.,sensing layer,feature layer,and algorithm layer)to guide the discussion of existing approaches and their *** also identify a number of future research opportunities,which will hopefully guide the design of next generation solutions.

关键词： Physiological characteristics recognition Artificial intelligence Internet of things Biological-driven authentication

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Machine Learning for Threat Detection

Machine Learning for Threat Detection

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Sutanto, Dustin Fransisca, Febri Liem, Steven Chowanda, Andry Muliono, Yohan Izdihar, Zahra Nabila School of Computer Science Cyber Security Program Computer Science Department Bina Nusantara Jakarta Indonesia School of Computer Science Computer Science Program Computer Science Department Bina Nusantara Jakarta Indonesia

ISBN: (纸本)9798350364910

These days almost all people in the world use the Internet as the internet is constantly evolving. cyber attack scale are increased thanks to cybercriminals that have become sophisticated in employing threats. Since the 1980s, Intrusion Detection Systems (IDS) have been developed to defend computer networks against malicious activity and unauthorized access. Companies choose to implement IDS the part of their cyber security strategy to protect their data and network from potential threats. in this case, IDS has played a crucial role in detecting abnormal traffic and protecting digital assets. furthermore, a high-accuracy IDS is needed in concern of having false positive feedback from the IDS machine itself that can cause various problems. to accompany the need for high accuracy and trainable IDS machines, we experimented with a hybrid system using machine learning that is combined with traditional IDS machines resulting in higher accuracy and lower error rate. By adjusting the parameter the accuracy improved and could achieve an accuracy of 99.66% of classifying the traffic. © 2024 IEEE.

关键词： Network intrusion

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Forward Legal Anonymous Group Pairing-Onion Routing for Mobile Opportunistic Networks

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IEEE Transactions on Mobile Computing 2025年第07期24卷 6595-6612页

作者： Zhu, Xiuzhen Lin, Limei Huang, Yanze Wang, Xiaoding Hsieh, Sun-Yuan Wu, Jie Fujian Normal University College of Computer and Cyber Security Fujian Provincial Key Laboratory of Network Security and Cryptology Fujian Fuzhou350117 China Fujian University of Technology School of Computer Science and Mathematics Fujian Fuzhou350118 China National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan Temple University Department of Computer and Information Science 1925 N. 12th St PhiladelphiaPA19122 United States

Mobile Opportunistic Networks (MONs) often experience frequent interruptions in end-to-end connections, which increases the likelihood of message loss during delivery and makes users more susceptible to various cyber attacks. However, most currently proposed anonymous routing protocols are primarily designed for networks with stable connections, making it challenging to protect user identities in MONs. To address these challenges, we propose FLAG-POR (Forward Legal Anonymous Group Pairing-Onion Routing), a novel anonymous routing protocol specifically tailored to enhance message delivery anonymity and security in MONs. Specifically, we abstract the mobile opportunistic network as a contact graph. By introducing the concept of "groups» into the pairing-onion routing protocol, which encrypts messages and relay nodes layer by layer, we develop a novel group-based pairing-onion routing protocol. This protocol ensures message confidentiality and relay node anonymity, while also improving message forwarding rates, as any node within a group can potentially act as a relay. To ensure message authenticity, we employ the efficient SM2 signing algorithm to generate signatures for the message source. Furthermore, by incorporating parameters such as the public key validity period and master key validity period into the group pairing-onion routing protocol, we achieve forward security in message delivery. We conduct a thorough theoretical analysis of the protocol's security and performance. The experimental results demonstrate that our FLAG-POR protocol outperforms baseline anonymous protocols in terms of delivery success rate, traceability rate, path anonymity, and node anonymity. Additionally, the FLAG-POR scheme effectively resists three potential threats to the routing system: collusion attack threat, node identification threat, and path identification threat, in any situation. © 2002-2012 IEEE.

关键词： Anonymity

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security Challenges and Issues in Cloud Computing

Security Challenges and Issues in Cloud Computing

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Zakiyyah, Rika Permana, Daniel Valenecio, Devan Chowanda, Andry Muliono, Yohan Izdihar, Zahra Nabila Cyber Security Program Computer Science Department School of Computer Science Bina Nusantara Jakarta Indonesia Computer Science Program Computer Science Department School of Computer Science Bina Nusantara Jakarta Indonesia

ISBN: (纸本)9798350364910

Managing data has changed significantly because of cloud computing, which offers scalabe, flexible and reasonably priced solutions to enterprises and to people as well such as Amazon, Google, and Microsoft expanding their infrastructure to meet the demand from the customer. With such advantages there will also be disadvantages such as security problems. This paper will discuss about security problems such as encryption, access control, multi-factor authentication, regular audits, secure configurations, incident response planning. This paper will also talk about security measures to deal with threats such as malicious insiders, data abuse, unsecured interfaces and APIs, shared technology complications, data loss or leakage, hijacking, and enigmatic risk profiles. This study examines and evaluates a range of cloud computing security concerns and issues through a systematic analysis of the literature. The goal of the research is to raise public awareness of the need for cloud computing security and to offer possible remedies. Identify and classify network security threats and vulnerabilities in cloud computing by doing an extensive examination of the body of research and empirical investigations is one of the answer to the questions from the paper. In the end, this take a look at unearths vulnerabilities and their practical implications through very well reading network safety in cloud computing. © 2024 IEEE.

关键词： Cloud security

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Probabilistic Reliability via Subsystem Structures of Arrangement Graph Networks

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IEEE Transactions on Reliability 2024年第1期73卷 279-289页

作者： Huang, Yanze Lin, Limei Xu, Li Hsieh, Sun-Yuan Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications School of Computer Science and Mathematics Fuzhou350118 China Fujian Normal University College of Computer and Cyber Security Key Laboratory of Network Security and Cryptology Fuzhou350117 China National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan

With the rapid growth of the number of processors in a multiprocessor system, faulty processors occur in it with a probability that rises quickly. The probability of a subsystem with an appropriate size being fault-free in a definite time interval is a significant and practical measure of the reliability for a multiprocessor system, which characterizes the functionality of a multiprocessor system well. Motivated by the study of subgraph reliability, as well as the attractive structure and fault tolerance properties of (n, k)-arrangement graph A n, k, we focus on the subgraph reliability for A n, k under the probabilistic fault model in this article. First, we investigate intersections of no more than four subgraphs in A n, k, and classify all the intersecting modes. Second, we focus on the probability P(q, A n, k n-1, k-1) with which at least one (n-1, k-1)-subarrangement graph is fault-free in A n, k, when given a uniform probability q with which a single vertex is fault-free, and we establish the P(q, A n, kn-1, k-1) by adopting the principle of inclusion-exclusion under the probabilistic fault model. Finally, we study the probabilistic fault model involving a nonuniform probability with which a single vertex is fault-free, and we prove that the P(q, A n, kn-1, k-1) under both models is very close to the asymptotic value by both theoretical arguments and experimental results. © 1963-2012 IEEE.

关键词： Fault tolerance

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Strategies for Building and Maintaining Secure Web Applications 5

Strategies for Building and Maintaining Secure Web Applicati...

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5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024

作者： Sathiyapriyan, C. Manikandan, B. Gokul, S. Satheesh, Rewin Nivetha, S. Leelavathy, S. Aarupadai Veedu Institute of Technology Cyber Security Department of Computer Science and Engineering Chennai603104 India Aarupadai Veedu Institute of Technology Department of Computer Science and Engineering Chennai603104 India Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai600119 India

ISBN: (纸本)9798350395235

Ensuring the security of web applications is paramount in safeguarding sensitive data and maintaining user trust. This study presents a comprehensive overview of strategies for building and maintaining secure web applications, acknowledging their inherent limitations and outlining potential areas for future work. The strategies discussed encompass fundamental aspects of web application security, including input validation and sanitization, robust authentication and authorization mechanisms, secure communication through HTTPS, timely security patching, implementation of security headers, monitoring and logging, client-side security measures, and vigilance in handling third-party components.. This research employed algorithms include Routing Algorithms, Middleware Execution Order Algorithms, Eloquent ORM Algorithms, Encryption and Hashing Algorithms, Session Handling Algorithms, Queue Management Algorithms, and Dependency Injection Algorithms. © 2024 IEEE.

关键词： Sensitive data

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Advancing Stance Detection of Political Fan Pages: A Multimodal Approach 24

Advancing Stance Detection of Political Fan Pages: A Multimo...

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33rd Companion of the ACM World Wide Web Conference, WWW 2023

作者： Kuo, Kuan-Hung Wang, Ming-Hung Kao, Hung-Yu Dai, Yu-Chen National Chung Cheng University Department of Computer Science and Information Engineering Chiayi Taiwan National Institute of Cyber Security Taipei Taiwan

ISBN: (纸本)9798400701726

The evolution of political campaigns is evident with the ascent of social media. Ideological beliefs are increasingly disseminated through political-affiliated fan pages. The interaction between politicians and the general public on these platforms plays a pivotal role in election outcomes. In this study, we utilize a multimodal approach to explore and quantify similarities of ideologies among political fan pages. we employed visualization techniques to demonstrate the political stance of each fan page. To validate our proposal, we concentrated on an analysis of the 2021 national referendums in Taiwan, encompassing a collection of fan pages and their corresponding posts that were related to these referendums. Through a qualitative analysis of the content of these fan pages, the efficacy of our multimodal framework in clustering fan pages according to their respective political ideologies was evaluated. The findings of this study underscore the significant enhancement in the accuracy of stance detection when integrating multiple modalities of data, namely textual content, visual imagery, and user interactions. © 2024 Copyright held by the owner/author(s).

关键词： Image enhancement

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Omni Contextual Aggregation Networks for High-Fidelity Image Inpainting

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IEEE Transactions on Circuits and Systems for Video Technology 2025年第6期35卷 6129-6144页

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

Image inpainting aims to restore a realistic image from a damaged or incomplete version. Although Transformer-based methods have achieved impressive results by modeling long-range dependencies, the inherent quadratic complexity of canonical self-attention has typically led to these approaches adopting uni-dimensional modeling, which limits the model's ability to capture complex relationships from both spatial and channel dimensions. To this end, this paper exploits a novel attention paradigm termed Dynamic Omni-Attention Mechanism (DOAM) for simultaneously modeling pixel-interaction from both spatial and channel dimensions, and implements the information interaction across the omni-axis (i.e., spatial and channel) with linear computational complexity. In addition, to handle large-scale degradation, this paper proposes a Multi-band Feature Enhancement (MFE) module to enhance feature representation in downsampling, thus unlocking the potential of subsequent attentional interactions. Moreover, motivated by recent advances in image restoration, this paper incorporates a domain-related prior representation from CNN-based Network to modulate the features during proposed attention mechanism and feed-forward networks. Integrating the above designs into an encoder-decoder architecture, the proposed Omni Contextual Aggregation Networks (OCANet) achieve superior performance at lower parameters and time costs than the competitive baselines. Extensive experiments on CelebA-HQ, Paris Street View, FFHQ and Dunhuang datasets validate the efficacy of the proposed method. © 2025 IEEE.

关键词： Image reconstruction

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A MULTIMODAL FRAMEWORK FOR SATIRE VS. SARCASM DETECTION 15

A MULTIMODAL FRAMEWORK FOR SATIRE VS. SARCASM DETECTION

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Goyal, Devansh Mishra, Santosh Kumar Rai, Vikash Kumar Department of Computer Science and Engineering RGIPT Jais Amethi India School of Cyber Security and Digital Forensics NFSU Goa Goa India

ISBN: (纸本)9798350370249

Sarcasm and satire are common ways to communicate complicated ideas with humor and irony, both expressing criticism or mockery. Detecting sarcasm vs. satire in real life can foster better communication by understanding intent, preventing misunderstandings, and promoting critical thinking and empathy. We introduce an innovative dataset for detecting Multi-modal Satire vs. Sarcasm, leveraging the MUStARD dataset for its construction. This dataset includes visual utterances annotated with sarcasm and satire labels, enriching its potential for studying multimodal satire and sarcasm detection. This enriched dataset serves as a robust foundation for training and evaluating machine learning and deep learning architectures that combine textual and visual cues to identify satire and sarcasm in multimedia content. By incorporating this enhanced dataset, the research aims to advance the field of multimodal satire and sarcasm detection and contribute to a deeper understanding of humor and irony in online communication. We carry out experimentation with various architectures like LSTM, GPT2, BERT, SVM, and Logistic Regression. The proposed architecture achieves an F1 score of 0.956, outperforming other baselines. © 2024 IEEE.

关键词： Contrastive Learning

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Cowrie SSH Honeypot: Architecture, Improvements and Data Visualization 23

Cowrie SSH Honeypot: Architecture, Improvements and Data Vis...

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23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

作者： Nastase, Vlad-Iulius Mihailescu, Maria-Elena Weisz, Sergiu Dagilis, Lukas Vytautas Mihai, Darius Carabas, Mihai University POLITEHNICA Bucharest Bucharest Department of Computer Science Romania NRD Cyber Security Vilnius Lithuania

ISBN: (纸本)9798331540388

As the competition between threat actors and defenders in the security landscape continues, honeypot deployments become more common as a source of threat intelligence. Yet, documentation for these systems is usually scarce, and their development halts or slows down in time. A better understanding of such systems can lead to deployments of higher deceitfulness, yielding higher quality threat intelligence. This paper aims to improve knowledge about the SSH honeypot Cowrie, presenting both knowledge that aids in understanding its architecture and improvements added to its source code to better suit our deployment or fix encountered issues. © 2024 IEEE.

关键词： honeypot network security SSH threat intelligence

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