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Facial Emotion Detection and Recommendation using Deep learning

Facial Emotion Detection and Recommendation using Deep learn...

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Blockchain and distributed systems security (ICBDS), IEEE international conference on

作者： Ansari Abu Affan Mustafa Kamal Ah. Dhananjay Dinkar Deore Mubashshera Mirza Gufran Beg Sufiyan M Ahsan Ansari Afeefa Rafeeque Md. Salman Baig Computer Department MMANTC (SPPU Pune) Malegaon (Nashik) Maharashtra

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354355

Facial emotion detection has emerged as a key focus in psychology, leveraging computer vision and machine learning to decode human emotions through facial expressions. By analyzing behaviors, actions, poses, and speech, it offers insights into individuals' emotional states. Deep learning models, particularly Convolutional Neural networks (CNNs), have significantly improved accuracy in identifying emotions like anger, happiness, and sadness from facial expressions. This technology facilitates personalized content recommendations based on detected emotional states, enhancing human-machine *** emotions serve as a vital window into one's internal feelings and mental state, playing a crucial role in non-verbal communication. Despite various channels of expression, facial emotion detection stands out as the most utilized method for its ability to accurately reflect a person's emotional spectrum. Specialized computer programs, trained on annotated datasets, employ advanced mathematical techniques to decipher emotions, contributing to our understanding of human emotions and enhancing the reliability of emotion recognition systems. Through the integration of CNNs, these programs have become more precise and dependable, paving the way for more nuanced interpretations of emotional cues in human-machine interactions.

关键词： Deep learning Human computer interaction Emotion recognition Shape Mood Human-machine systems User experience Convolutional neural networks security Reliability

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Efficiency-enhanced Blockchain-based Client Selection in Heterogeneous Federated Learning 6

Efficiency-enhanced Blockchain-based Client Selection in Het...

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6th IEEE international conference on Blockchain, Blockchain 2023

作者： Lei, Zhiqi Gai, Keke Yu, Jing Wang, Shuo Zhu, Liehuang Raymond Choo, Kim-Kwang Beijing Institute of Technology School of Computer Science and Technology Beijing100081 China Yangtze Delta Region Academy of Beijing Institute of Technology Zhejiang Jiaxing314000 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Institute of Information Engineering Chinese Academy of Sciences Beijing China University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

ISBN: (纸本)9798350319293

In Federated Learning (FL), blockchain has been extensively used to achieve distributed and tamper-resistant data processing. However, typical Blockchain-based Federated Learning (BFL) rarely considers clients' resource and computing limits. High-capacity clients may be sacrificed when all clients train on the same neural network. This paper proposes a Blockchain-based Heterogeneous Federated Learning (BlocFL) model to address the challenges above. BlocFL replaces the central server with a consortium blockchain, and several neural networks are employed for local training. Considering the challenges in resource allocation in BFL, especially in heterogeneous networks, we propose a consortium blockchain-based heterogeneous federated learning client selection method. The proposed method optimizes the choice of client nodes under the limits of computational resources. Experiment results demonstrate that our method can allocate appropriate neural network models to each client and effectively improve the efficiency of local training in HFL. It also can achieve a comparable level of accuracy to the baseline approach with similar training parameters. © 2023 IEEE.

关键词： Blockchain

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Denial of Service (DoS) Attacks in SDN-Based VANETs: A Study

Denial of Service (DoS) Attacks in SDN-Based VANETs: A Study

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international conference on Parallel distributed and Grid Computing (PDGC)

作者： Jyotsana Sardana Sunil Kumar Dharminder Kumar Kamlesh Dutta Dept. of Computer Science & Engg Guru Jambeshwar University of Science and Technology Hisar Haryana India Dept. of AI & Data Science Guru Jambeshwar University of Science and Technology Hisar Haryana India Dept. of Computer Science & Engg Gurugram University Gurugram Haryana India Dept. of Computer Science & Engg National Institute of Technology Hamirpur H.P India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

Vehicular ad hoc networks (VANETs) play a vital role in ensuring the success of Intelligent transport systems (ITS), but the architecture of VANETs is vulnerable to several security attacks. There are also some challenges associated with VANETs such as the management of large-scale dynamic heterogeneous networks and secure communication over the network. The research community stressed on the integration of Software-defined Networking (SDN) with traditional VANETs to address these challenges. The SDN enhances the functionality of traditional VANETs by adding a centralised control mechanism, programmability, and flexibility *** SDN also mitigates some security issues in VANETs to a limited degree. However, SDN's inherent features introduce new security vulnerabilities mainly in the control plane. This paper first examines the characteristics of SDN when integrated with VANETs. Then, this paper discusses the new security vulnerabilitiesthat arise as a result of the integration of SDN into VANET architecture. The mostcritical security attack in SDN-based VANETs is Denial of Service (DoS) attack. This paper also examines different types of DoS attacks in SDN-based VANETs along with their potentialdefence mechanisms. Finally, this paper highlights the future research directions in the domain of securing the network operations of SDN-based VANETs.

关键词： Prevention and mitigation Vehicular ad hoc networks Grid computing Real-time systems Heterogeneous networks security Reliability Vehicle dynamics Software defined networking Resilience

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Navigating IoT security Assessment: Current Methods, Challenges and Future Directions

Navigating IoT Security Assessment: Current Methods, Challen...

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international conference on Advanced computer Information Technologies (ACIT)

作者： Alhassan Abdulhamid Sohag Kabir Ibrahim Ghafir Ci Lei Faculty of Engineering and Digital Technologies University of Bradford Bradford United Kingdom

ISBN: (数字)9798350350043

ISBN: (纸本)9798350350050

Rapid growth of Internet of Things (IoT) applications h as significantly transformed h uman interaction with technology, providing unprecedented convenience and connectivity in our daily lives. Securing a complex network of interconnected IoT devices poses significant c hallenges. T his r equires a continuous proactive security assessments of the systems, considering their interconnected nature, distributed networks, and their crucial role in our health, safety, and the environment. It is essential to comprehensively evaluate IoT systems’ security features to comprehend and successfully address security risks. This arti-cle offers an in-depth exploration of quantifying IoT security, examining some of the existing assessment models, associated challenges in security quantification, a nd p otential a venues for advancement. The principal contribution of this article lies in providing an overview of the current state of IoT security quantification a nalysis, d elineating p rominent c hallenges, and proposing prospects for addressing them.

关键词： Technological innovation Navigation Computational modeling Data integration Complex networks Data models Safety Internet of Things computer security Information technology

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Towards Privacy-First security Enablers for 6G networks: The PRIVATEER Approach 23rd

Towards Privacy-First Security Enablers for 6G Networks: The...

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23rd international conference on Embedded computer systems: Architectures, Modeling, and Simulation, SAMOS 2023

作者： Masouros, Dimosthenis Soudris, Dimitrios Gardikis, Georgios Katsarou, Victoria Christopoulou, Maria Xilouris, George Ramón, Hugo Pastor, Antonio Scaglione, Fabrizio Petrollini, Cristian Pinto, António Vilela, João P. Karamatskou, Antonia Papadakis, Nikolaos Angelogianni, Anna Giannetsos, Thanassis Villalba, Luis Javier García Alonso-López, Jesús A. Strand, Martin Grov, Gudmund Bikos, Anastasios N. Ramantas, Kostas Santos, Ricardo Silva, Fábio Tsampieris, Nikolaos National Technical University of Athens Athens Greece R&D Department Space Hellas S.A Athens Greece NCSR "Demokritos" Institute of Informatics and Telecommunications Agia Paraskevi Greece Telefonica I+D Madrid Spain RHEA Group Wavre Belgium INESC TEC Porto Portugal Infili Technologies S.A Zografou Greece Ubitech Ltd Digital Security & Trusted Computing Group Chalandri Greece Universidad Complutense de Madrid Madrid Spain Kjeller Norway Iquadrat Informatica S.L Barcelona Spain Polytechnic of Porto Porto Portugal ERTICO-ITS Europe Brussels Belgium

ISBN: (纸本)9783031460760

The advent of 6G networks is anticipated to introduce a myriad of new technology enablers, including heterogeneous radio, RAN softwarization, multi-vendor deployments, and AI-driven network management, which is expected to broaden the existing threat landscape, demanding for more sophisticated security controls. At the same time, privacy forms a fundamental pillar in the EU development activities for 6G. This decentralized and globally connected environment necessitates robust privacy provisions that encompass all layers of the network stack. In this paper, we present PRIVATEER’s approach for enabling "privacy-first" security enablers for 6G networks. PRIVATEER aims to tackle four major privacy challenges associated with 6G security enablers, i.e., i) processing of infrastructure and network usage data, ii) security-aware orchestration, iii) infrastructure and service attestation and iv) cyber threat intelligence sharing. PRIVATEER addresses the above by introducing several innovations, including decentralised robust security analytics, privacy-aware techniques for network slicing and service orchestration and distributed infrastructure and service attestation mechanisms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Queueing networks

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Next-Gen SDN security: Quantum Keying Meets AI Analytics

Next-Gen SDN Security: Quantum Keying Meets AI Analytics

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distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： S. Virushabadoss Anithaashri T. P M. Nivedha S. Hari Krishnan Anand Karuppannan Dept. of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Electronics and Communication and Engineering Arasu Engineering College Kumbakonam India Department of Electronics and Communication and Engineering Sanskrithi School of Engineering Puttaparthi India Department of Electronics and Communication and Engineering Gnanamani College of Technology Namakkal India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

This paper suggests a complete security architecture that blends quantum key distribution (QKD) with cutting-edge machine learning methods to improve the Software-Defined Networking (SDN) control plane. By creating secure channels of communication through QKD, the framework ensures integrity and secrecy of control messages between the SDN controller and network devices. Furthermore, network traffic is continuously monitored and analyzed using machine learning techniques, enabling the detection of unusual behaviors that might be warning signs of upcoming security problems. Tests utilizing Mininet as the network interface and Open Daylight as the SDN controller proved the efficacy of the suggested method. The outcomes revealed a minimal computational overhead, exceptional detection accuracy up to 98.1%, and low false positive rates, substantiating the system's ability to effectively manage varied network conditions and traffic volumes. These results underscore the potential of integrating QKD with robust machine learning strategies to secure the SDN control plane against sophisticated threats.

关键词： Quantum computing Machine learning Telecommunication traffic computer architecture Quantum key distribution Network interfaces Cryptography Software defined networking computer security Monitoring

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Face Mask Detection under the Threat of Covid-19 Virus 1

Face Mask Detection under the Threat of Covid-19 Virus

引用

1st IEEE international conference on Blockchain and distributed systems security, ICBDS 2022

作者： Dange, B.J. Khalate, S.S. Kshirsagar, D.B. Gunjal, S.N. Khodke, H.E. Bhaskar, T. Sanjivani College of Engineering Kopargaon Savitribai Phule Pune University Dept. of Computer Engineering Pune India

ISBN: (数字)9781665428323

ISBN: (纸本)9781665428323

For wearing a mask, Covid19 has a new identity. Detecting masked faces with accuracy and efficiency is becoming increasingly important. Face mask recognition is a tough task because of the high occlusions that cause the loss of face in-formation. Furthermore, There aren't many large-scale, masked face with a well-label datasets out there, which makes face mask recognition more difficult. CNN-based deep learning algorithms have achieved significant advances in a variety, one aspect of computer vision is face detection disciplines. We introduce a new cascade structure based on CNN for recognising face masks in this paper, This is made up of three convolutional neural networks that have been successfully built. To finetune our CNN models, we propose a new dataset named 'facial mask dataset.' due to a paucity of face masked training instances. Face masks were tested on a set of faces, we assess our suggested face mask recognition algorithm, and it performs admirably. A new cascade framework based on CNN is proposed for detecting face masks and their types, which comprises of three properly built convolutional neural networks. © 2022 IEEE.

关键词： Feature extraction

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CPADP: Novel Processor for Efficient Threat Detection in CPS using RISC and DC-GCNN

CPADP: Novel Processor for Efficient Threat Detection in CPS...

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distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： K. Sravan Kumar G. Suresh Usthulamuri Penchalaiah Sundeep Kumar K E. Prasanthi Department of ECE Geethanjali Institute of Science and Technology India Dept. of ECE Geethanjali Institute of Science and Technology India Dept. of CSE Geethanjali Institute of Science and Technology India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

In the realm of cybersecurity for cyber-physical systems (CPS), the need for robust and efficient intrusion detection mechanisms has become increasingly critical. The existing CPS had limited processing capabilities of traditional detection systems in CPS, and incompatibility of existing IT- centric security solutions with CPS environments. The challenges in real-time threat detection and response due to high data volumes. Vulnerabilities arising from interconnected nature of cyber-physical systems. This paper proposes a novel Cyber-Physical Attack Detection Processor (CPADP) based on Reduced Instruction Set Computing (RISC) architecture. The CPADP integrates advanced techniques for real-time threat detection in CPS environments, leveraging a comprehensive approach spanning data collection, preprocessing, Independent Component Analysis (ICA)-based feature extraction, and a Dual Channel Graph Convolutional Neural Network (DC-GCNN) for attack classification. The architecture aims to address the challenges posed by CPS environments, where traditional IT- centric security measures often fall short. By harnessing the capabilities of RISC architecture, the CPADP promises enhanced processing efficiency and scalability, crucial for real-time threat mitigation in diverse CPS applications.

关键词： Reduced instruction set computing Scalability Intrusion detection computer architecture Independent component analysis Cyber-physical systems Feature extraction Real-time systems Threat assessment computer security

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Image Cryptography using AES-256 Algorithm

Image Cryptography using AES-256 Algorithm

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distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： Taniska Chandel Ninad Gangodkar Abhiraj Gautam Yogesh Lohumi Mohd Rehan Ghazi Ashtha Goyal Department of Computer Science and Engineering Graphic Era (Deemed to be) University Dehradun India School of Computing Graphic Era Hill University Dehradun India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Due to the advancement of technology, information security and user privacy have become a critical issue resulting in the use of various encryption techniques. Especially with the increasing use of social networking, it has become necessary to secure multimedia messages and prevent data threats and data manipulation. Image Cryptography focuses on the encryption of images and securing them from unauthorized access and protect their confidentiality and integrity. In order to encrypt and decode pictures, this paper focuses on the Advanced Encryption Standard Algorithm (AES) which is a symmetric encryption algorithm. Furthermore, it reflects on the efficiency of the algorithm by determining the security of the algorithm using various parameters like entropy, NPCR, MSE and Histogram analysis. For better comparison all five of AES modes are presented in this paper; Electronic Codebook (ECB), Cipher Block Chaining (CBC), Cipher Feedback (CFB), Output Feedback (OFB), and Counter (CTR). Overall, it can be concluded that AES is a secure algorithm that can be used for safe data transfer. Furthermore, through the result of the parameters used to determine the security of each mode of the AES algorithm, it can further be concluded that CTR mode of the algorithm is the most secure.

关键词： Ciphers Steganography Privacy Social networking (online) Entropy Encryption security Cryptography Standards Output feedback

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Quantum Cryptography Techniques for Enhancing security in IoT Communications

Quantum Cryptography Techniques for Enhancing Security in Io...

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distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： Suresh Bysani Venkata Naga Arnav Kotiyal R.S.S. Raju Battula Harshal Patil Yogesh Dharangutti Natrayan L Eightfold.ai Ex - Cohesity California USA Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Applications Aditya University Surampalem India School of Computer Science & Engineering IILM University Greater Noida India Department of Law Symbiosis Law School Symbiosis International (Deemed University) Pune India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Kuthambakkam India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

A system of wirelessly communicative sensors embedded in a person's clothing. In order to remotely monitor and treat a patient's health, sensor devices are embedded in clothing, skin, and the human body itself. Healthcare, the military, sports, and remote treatment are just a few of the modern WBSN applications. It improves people's quality of life by allowing for more precise and quicker disease diagnosis as well as more timely care and more effective treatment. Even if a patient is far away from medical care, WBSN can still save their life. Despite the numerous benefits that WBSN technology brings to healthcare systems, there are legitimate concerns about security and privacy when it comes to collecting and transmitting physiological data about humans in an open setting. Ensuring the security of physiological data during transmission in a wireless environment is a challenging but crucial task. Key distribution, authentication, data integrity, and data confidentiality are just a few of the many security issues plaguing the WBSN. In tackling the WBSN security issues, this research contributes significantly. Secure transmission in wireless networks and high attack resistance are both provided by the cryptographic computational process. Nevertheless, the unsecure transmission of keys across networks is the sole vulnerability of public and private key cryptography methods. Attackers can easily crack traditional key sharing protocols used by communicating parties. Intruders can compromise the system's security in its entirety if they obtain the secret key. In WBSN, a secure way to generate and distribute secret keys is required. The EBB84QCP is a method for creating and sharing secret keys between communicating parties. Rather than using two prime numbers, the Enhanced and Modified RSA Cryptosystem (EMRSACS) suggests using four prime numbers for key generation, encryption, and decryption. Data transmission in wireless networks still involves a secret quantum key that is

关键词： Data privacy Wireless networks Qubit Receivers Sensors Encryption security Communication system security Biomedical monitoring Quantum cryptography

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