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Application of Perceptual Features for User Authentication in distributed Systems 22nd

Application of Perceptual Features for User Authentication i...

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11th international conference on Intelligent networking and Collaborative Systems (INCoS) / 22nd international conference on Network-Based Information Systems (NBiS)

作者： Ogiela, Marek R. Ogiela, Lidia AGH Univ Sci & Technol Cryptog & Cognit Informat Res Grp 30 Mickiewicza Ave PL-30059 Krakow Poland Pedag Univ Krakow Dept Cryptog & Cognit Informat Podchorazych 2 St PL-30084 Krakow Poland

ISBN: (纸本)9783030290290;9783030290283

this paper will present selected approaches based on cognitive solutions for creation security procedures and cryptographic protocols. In particular will be described the ways of using perceptual and cognitive features in creation of secure protocols, oriented on user authentication and data management. the new areas of cognitive cryptography will be also described, which offer a new possibilities in security areas oriented on application of perceptual features and personal characteristics.

关键词： Cognitive authentication Security protocols Cryptographic protocols

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Semantic Maximum Relevance and Modal Alignment for Cross-Modal Retrieval 22

Semantic Maximum Relevance and Modal Alignment for Cross-Mod...

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Proceedings of the 2022 11th international conference on computing and Pattern Recognition

作者： Pingping Sun Baohua Qiang Zhiguang Liu Xianyi Yang Guangyong Xi Weigang Liu Ruidong Chen Shihao Zhang Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology China Hebei Key Laboratory of Intelligent Information Perception and Processing The 54th Research Institute of CETC China

ISBN: (纸本)9781450397056

With the increasing abundance of multimedia data resources, researches on mining the relationship between different modalities to achieve refined cross-modal retrieval are gradually emerging. In this paper, we propose a novel Semantic Maximum Relevance and Modal Alignment (SMR-MA) for Cross-Modal Retrieval, which utilizes the pre-trained model with abundant image text information to extract the features of each image text, and further promotes the modal information interaction between the same semantic categories through the modal alignment module and the multi-layer perceptron with shared weights. In addition, multi-modal embedding is distributed to the normalized hypersphere, and angular edge penalty is applied between feature embedding and weight in angular space to maximize the classification boundary, thus increasing both intra-class similarity and inter-class difference. Comprehensive analysis experiments on three benchmark datasets demonstrate that the proposed method has superior performance in cross-modal retrieval tasks and is significantly superior to the state-of-the-art cross-modal retrieval methods.

关键词： Semantic Relevance CLIP Cross-Modal Retrieval Modal Alignment

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Avoidance of Replay attack in CAN protocol using Authenticated Encryption 11

Avoidance of Replay attack in CAN protocol using Authenticat...

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11th international conference on computing, Communication and networking Technologies, ICCCNT 2020

作者： Chandrasekaran, Selvamani Ramachandran, K.I. Adarsh, S. Puranik, Ashish Kumar Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Electronics and Communication Engineering Coimbatore India Centre for Computational Engineering and Networking Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India Tata Consultancy Services Pune India

ISBN: (纸本)9781728168517

Controller Area Network is the prominent communication protocol in automotive systems. Its salient features of arbitration, message filtering, error detection, data consistency and fault confinement provide robust and reliable architecture. Despite of this, it lacks security features and is vulnerable to many attacks. One of the common attacks over the CAN communication is the replay attack. It can happen even after the implementation of encryption or authentication. this paper proposes a methodology of supressing the replay attacks by implementing authenticated encryption embedded with timestamp and pre-shared initialisation vector as a primary key. the major advantage of this system is its flexibility and configurability nature where in each layer can be chosen with the help of cryptographic algorithms to up to the entire size of the keys. © 2020 IEEE.

关键词： Authentication

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Event-Driven Data Pipeline for Network Management Systems 11

Event-Driven Data Pipeline for Network Management Systems

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11th international conference on computing, Communication and networking Technologies, ICCCNT 2020

作者： Ponnuswami, Ganesan Kailasam, Sriram DInesh, DIleep Aroor School of Computing and Electrical Engineering Indian Institute of Technology Mandi Himachal Pradesh India

ISBN: (纸本)9781728168517

Developing an event-driven applications for network management systems(NMS) requires data-wrangling operations to be performed in a data pipeline with low latency and high throughput. Data stream processing engines(SPEs) enables the pipeline to feature extract complex data in near real time. We present a low latency and high throughput data pipeline that performs operations such as data cleansing, filtering, aggregations and join of streams on pipeline stages for event-driven machine learning applications. When the data stream has imbalance in arrival of records, a standalone system handle it ineffectively that reduces the performance of data pipeline. In this work, the system powered by SPEs handle the imbalance by scaling out resources and degree of parallelism such that performance is not degraded. © 2020 IEEE.

关键词： Pipelines

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Emergence of Edge computing: An Advancement over Cloud and Fog 11

Emergence of Edge Computing: An Advancement over Cloud and F...

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11th international conference on computing, Communication and networking Technologies, ICCCNT 2020

作者： Mitra, Anuran Biswas, Soumita Adhikari, Tinku Ghosh, Arindam De, Soumalya Karmakar, Raja Techno International New Town Dept. of IT Kolkata700156 India

ISBN: (纸本)9781728168517

In today's world, the Internet of things i.e IoT has possessed a great impact in our life. Almost everything from electrical to electronic gadgets have become a part of IoT due to which the data production and consumption have increased. Cloud computing due to its centralized architecture is not enough to handle this exponential growth of data it suffers from and thus certain limitations. Due to the drawbacks of cloud computing, a decentralized computing paradigm called fog computing was coined where computation of data used to happen near to the network edge. But due to some limitations of fog computing a similar type but an advancement over fog came into existence called edge computing which could resolve all the major drawbacks and challenges of cloud and fog to a large extent. Certain issues regarding high latency, high response time, high bandwidth cost, high energy consumption and high security threat are now resolved by edge computing to a large extent with lots of popular emerging fields and applications running on this concept. So the overall journey of this paper focuses on what exactly edge computing is and the need of edge computing in this growing world of data and how edge computing introduces the technology world with some of the emerging applications being widely used nowadays. © 2020 IEEE.

关键词： Edge computing

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Kawaii in Tweets: What Emotions Does the Word Describe in Social Media? 22nd

Kawaii in Tweets: What Emotions Does the Word Describe in So...

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11th international conference on Intelligent networking and Collaborative Systems (INCoS) / 22nd international conference on Network-Based Information Systems (NBiS)

作者： Iio, Jun Chuo Univ Fac Global Informat Shinjuku Ku 1-18 Ichigaya Tamachi Tokyo 1628478 Japan

ISBN: (纸本)9783030290290;9783030290283

the Japanese word kawaii is a particular word that represents a kind of emotion. It is similar to "pretty" or "cute" in English. However, there is some difference between kawaii and these English words. this study reveals how the word kawaii is used in message exchanges over social networking services (SNS) and in what context it is used. the experiment compared two sets of tweets: one set with the word kawaii and the other without it. Also, it compared several sets of words within five predetermined emotional categories. the experiment revealed that there was a marked difference between the two groups, especially in the context of expressing the emotions of "enjoy," "happy," and "like."

关键词： Social networking (online)

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A Robust Deep Learning Segmentation and Identification Approach of Different Bangladeshi Plant Seeds Using CNN 11

A Robust Deep Learning Segmentation and Identification Appro...

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11th international conference on computing, Communication and networking Technologies, ICCCNT 2020

作者： Keya, Mumenunnessa Majumdar, Bhaskar Islam, Md. Sanzidul Daffodil International University Dept. of CSE Dhaka Bangladesh

ISBN: (纸本)9781728168517

the purpose of this research is to identify the image of the seed. Different types of seeds are leveled into different classes through seed classification process. the demonstration was applied on more than 1000 seed images. It contains five processing modules such as Image acquisition, Pre-processing, Feature extraction, Image recognition and Show results. Seed varieties and qualities of seeds will be able to identify. the seeds species, namely Oryza sativa, Lagenaria siceraria, Cucurbita moschata, Zea mays, Benincasa hispida. Define the seeds age, shape, color, length, width, size, healthy or not, duration of seeds quality. the cost of analyzing the image will be minimal and does not require skilled labor, Seed studies - such as seed germination, can play an important role in seed purity. this research we have used CNN algorithm and the training accuracy was 87%-89% and validation accuracy was 90%-93%. © 2020 IEEE.

关键词： Seed

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Neural Network Based Bengali News Headline Multi Classification System: Selection of Features describes Comparative Performance 11

Neural Network Based Bengali News Headline Multi Classificat...

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11th international conference on computing, Communication and networking Technologies, ICCCNT 2020

作者： Khushbu, Sharun Akter Masum, Abu Kaisar Mohammad Abujar, Sheikh Hossain, Syed Akhter Daffodil International University Dept.of CSE Dhaka Bangladesh

ISBN: (纸本)9781728168517

the modern era is gradually developing in all sectors. Moreover, development is necessary to research. Accordingly natural language processing is the expanding area of process text. At present year, memorizing the data is very tough due to the rapidly growing volume of data. Newspapers are a great habit to the whole world of all ages. To acquire a variety of knowledge from different segments is entertaining by themselves. According to this work using bengali news headline may be more specific to others by defining its news type. therefore the machine can smartly review the sequence of sentences within reach output to find newstype. With experiment, we connect our approach by Neural Network of adoption with 90% accuracy performance. Coming with a momentous outcome we've done Multi Classification reached at SVM, NB, Logistic Regression, Neural Network, Random forest applying bengali dataset. © 2020 IEEE.

关键词： Decision trees

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Real-Time Vehicle Classification Using CNN 11

Real-Time Vehicle Classification Using CNN

引用

11th international conference on computing, Communication and networking Technologies, ICCCNT 2020

作者： Jahan, Nusrat Islam, Saiful Foysal, Md. Ferdouse Ahmed CSE Daffodil International University Dhaka Bangladesh

ISBN: (纸本)9781728168517

Convolutional Neural Network (CNN) is a model of artificial neural networks that has grown to be most well known in computer vision assignment. In this paper work, we presented convolutional neural network for classifying four types of common vehicle in our country. Vehicle classification plays a vital role of various application such as surveillance security system, traffic control system. We addressed these issues and fixed an aim to find a solution to reduce road accident due to traffic related cases. the greatest challenge of computer vision is to achieve effective results to implement a system due to variation in shapes and colors of data. To classify the vehicle we used two methods feature extraction and classification. these two methods can straightforwardly performed by convolutional neural network. the method shows quite good performance on real-time standard dataset. Our mentioned method able to reach 97% accuracy in case of vehicle classification. © 2020 IEEE.

关键词： Convolutional neural networks

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Time-Aware Missing Traffic Flow Prediction for Sensors with Privacy-Preservation 11th

Time-Aware Missing Traffic Flow Prediction for Sensors with ...

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11th international conference on Computer Engineering and Networks, CENet2021

作者： Qi, Lianyong Wang, Fan Xu, Xiaolong Dou, Wanchun Zhang, Xuyun Khosravi, Mohammad R. Zhou, Xiaokang School of Computer Science Qufu Normal University Qufu China School of Computer and Software Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China Department of Computing Macquarie University SydneyNSW2109 Australia Department of Computer Engineering Persian Gulf University Bushehr Iran Department of Electrical and Electronic Engineering Shiraz University of Technology Shiraz Iran Faculty of Data Science Shiga University Hikone Japan

ISBN: (纸本)9789811665530

With the continuous development of IoT, a number of sensors establish on the roadside to monitor traffic conditions in real time. the continuously traffic data generated by these sensors makes traffic management feasible. However, loss of data may occur due to inevitable sensor failure, impeding traffic managers to understand traffic dynamics clearly. In this situation, it is becoming a necessity to predict missing traffic flow accurately for effective traffic management. Furthermore, the traffic sensor data are often distributed and stored by different agencies, which inhibits the multi-party sensor data sharing significantly due to privacy concerns. therefore, it has become a major obstacle to balance the tradeoff between data sharing and vehicle privacy. In light of these challenges, we propose a privacy-aware and accurate missing traffic flow prediction approach based on time-aware Locality-Sensitive Hashing technique. At last, we deploy a set of experiments based on a real traffic dataset. Experimental reports demonstrate the feasibility of our proposal in terms of traffic flow prediction accuracy and efficiency while guaranteeing sensor data privacy. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data privacy

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