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Enhancing an Availability of Cloud Based on Fault Tolerance Techniques 21

Enhancing an Availability of Cloud Based on Fault Tolerance ...

引用

21st Saudi computer Society National computer Conference, NCC 2018

作者： Safaa, Yousef S. Alraddadi Faisal, Saleem S. Alraddadi Dep. Computer Science Faculty of Computing and Information Technology King Abdul-Aziz University Jeddah Saudi Arabia Dep. Computer Network and Information Security School of Information Technology Jawaharlal Nehru Technology University Hyderabad India

ISBN: (纸本)9781538641095

Recently cloud computing used in a wide range of the applications, to ensure availability of the cloud service many design techniques of fault tolerance have been done. In this paper, proposed approach providing high availability for client cloud request. To achieve this, used load balance, redundancy mechanism and acceptance test to handle fault in service manager as well a checkpoint and load balance used to handle fault in service node also. The proposed approach showed better results in terms of the availability than failover strategies approach, where the comparison was based on the availability equation. © 2018 IEEE.

关键词： Redundancy

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On the Efficiency of Combinatorial Generation for Adaptive Image Steganography

On the Efficiency of Combinatorial Generation for Adaptive I...

引用

2021 International Conference Engineering and Telecommunication, En and T 2021

作者： Melman, Anna Evsutin, Oleg Shablya, Yuriy Higher School of Economics Dep. of Information Security of Cyber-Physical Systems Moscow Russia Tomsk State University of Control Systems and Radioelectronics Dep. of Complex Information Security of Computer Systems Tomsk Russia

ISBN: (纸本)9781728183909

Steganographic embedding is an effective method of protecting information transmitted over an open communication channel. Steganography techniques hide information in digital objects by embedding to make it invisible to an attacker. The most common covers for hiding additional information are multimedia data, in particular digital images. The embedding effectiveness is mainly assessed by the criteria of invisibility and capacity. One of the ways to improve the embedding efficiency is to choose the best location of message bits within the cover object, but it usually takes a long time to iterate through a large number of such embedding options. In this paper, we propose a new approach to finding the best option for steganographic embedding of information into the phase spectrum of the discrete Fourier transform based on the methods of combinatorial generation. The results of the experiments show that the new approach allows us to reduce the best embedding option search time, while the invisibility and capacity indicators remain high. © 2021 IEEE.

关键词： Steganography

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The Hierarchial Data Aggregation Method in Backbone Traffic Streaming Analyzing to Ensure Digital Systems information security 11

The Hierarchial Data Aggregation Method in Backbone Traffic ...

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11th International Conference "Management of Large-Scale System Development", MLSD 2018

作者： Poltavtseva, Maria A. Zegzhda, Petr D. Pankov, Ilya D. Information Security of Computer Systems Dep. Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (纸本)9781538649244

Modern large digital systems security poses the urgent task of detecting network attacks on the backbone highspeed traffic flow. To solve this problem, one need to preprocess, prepare and aggregate data from network packets. The network traffic analysis module aggregates big data from the traffic flow in time series for mathematical analysis. The authors propose a new hierarchical method of data aggregation, which allows to more effectively reducing the data size and speed up the processing of each separate new fragment. The method consists in introducing Parent-Child-Relation links between the analyzed parameters time series and the use of data accumulation and shift based on these relationships. Paper include estimating of proposed method effectiveness. © 2018 IEEE.

关键词： Big data

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Complex network model for software system and complexity measurement

Complex network model for software system and complexity mea...

引用

2009 WRI World Congress on computer Science and information Engineering, CSIE 2009

作者： Song, Gao Chunping, Li Computer Science and Technology Dep. Key Laboratory for Information System Security Tsinghua University China School of Software Key Laboratory for Information System Security Tsinghua University China

ISBN: (纸本)9780769535074

This paper proposes a new method for measuring the complexity of software systems based on complex network theory. We first construct the complex network model for software system. Then, the complexity of a homogeneous system is defined according to the entropy theory. With the experiments on open source software systems, we show that our method can reveal the complexity on different aspects of software systems, such as inheritance and understanding complexity. © 2008 IEEE.

关键词： Complex networks

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Automated Reasoning 1

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丛书名： Lecture Notes in computer Science

1000年

作者： David Basin Michaël Rusinowitch

ISBN: (数字)9783540259848

ISBN: (纸本)9783540223450

This volume constitutes the proceedings of the 2nd International Joint C- ference on Automated Reasoning (IJCAR 2004) held July 4–8, 2004 in Cork, Ireland. IJCAR 2004 continued the tradition established at the ?rst IJCAR in Siena,Italyin2001,whichbroughttogetherdi?erentresearchcommunitieswo- ing in automated reasoning. The current IJCAR is the fusion of the following conferences: CADE: The International Conference on Automated Deduction, CALCULEMUS: Symposium on the Integration of Symbolic Computation and Mechanized Reasoning, FroCoS: Workshop on Frontiers of Combining Systems, FTP: The International Workshop on First-Order Theorem Proving, and TABLEAUX: The International Conference on Automated Reasoning with Analytic Tableaux and Related Methods. There were 74 research papers submitted to IJCAR as well as 12 system descriptions. After extensive reviewing, 26 research papers and 6 system - scriptions were accepted for presentation at the conference and publication in this volume. In addition, this volume also contains papers from the three invited speakers and a description of the CADE ATP system competition. We would like to acknowledge the enormous amount of work put in by the members of the program committee, the various organizing and steering c- mittees, the IJCAR o?cials, the invited speakers, and the additional referees named on the following pages. We would also like to thank Achim Brucker and Barbara Geiser for their help in producing this volume.

关键词： Artificial Intelligence Mathematical Logic and Foundations Mathematical Logic and Formal Languages Logics and Meanings of Programs Software Engineering

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Personalization in crowd-driven annotation for cultural heritage collections

Personalization in crowd-driven annotation for cultural heri...

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20th Conference on User Modeling, Adaptation, and Personalization, UMAP 2012

作者： Dijkshoorn, Chris Oosterman, Jasper Aroyo, Lora Houben, Geert-Jan Network Institute Dep. of Computer Science VU University Amsterdam Netherlands Web Information Systems Delft University of Technology Netherlands

Many cultural heritage institutions are confronted with a big challenge when it comes to adapting the process of registration, annotation and digitization of their collections to meet the new technological demands for providing their collections online with Web and mobile technologies. With limited funding and limited professional resources, annotation is often lagging behind significantly in terms of quantity and level of detail. Quantity as well as quality of the annotations is the key to finding relevant objects by various groups of users in online collections. As many experiments with cultural heritage data online show, human computation can be useful for collecting large quantities of data. Various of these experimented with a crowd of lay people to help with the annotation of cultural heritage artefacts. However, a common concern relates to the resulting quality. The current trend appears to focus on supporting 'the crowd' to achieve the desired level of quality. In this paper, we discuss the results of the first phase of an evolutionary system design performed in collaboration with the Rijksmuseum Amsterdam, as part of the SEALINCMedia project. By providing personalized support to the individuals and groups in the 'crowd' when annotating museum collection objects, we also support the integration of the annotation result in the RMA content management system. The contribution of this paper is twofold: (1) requirements specification for a crowdsourcing annotation process and (2) design of the personalization functionality in a crowdsourcing annotation system. © Springer-Verlag Berlin Heidelberg 2011.

关键词： Crowdsourcing

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Feature Selection for Robust Spoofing Detection: A Chi-Square-based Machine Learning Approach 2

Feature Selection for Robust Spoofing Detection: A Chi-Squar...

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2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Al-Na'amneh, Qais Aljaidi, Mohammad Gharaibeh, Hasan Nasayreh, Ahmad Emhamed Al Mamlook, Rabia Almatarneh, Sattam Alzu'bi, Dalia Suliman Husien, Abla Applied Science Private University Dep. of Cyber Security Amman Jordan Zarqa University Dep. of Computer Science Zarqa Jordan Yarmouk University Dep. Computer Science Irbid Jordan Trine University Dep. of Business Administration Indiana United States University of Zawia Department of Industrial Engineering Tripoli Libya Zarqa University Dep. of Data Science and Artificial Intelligence Zarqa Jordan Concordia University Dep. Information and Systems Engineering Montreal Canada

ISBN: (纸本)9798350373363

Nowadays, the Internet of Things (IoT) system is vulnerable to spoofing attacks that can easily where attackers can easily pose as a legal entity of the network. A 'spoofing attack' refers to a type of cyber-attack when an attacker purposefully impersonates or masquerades as someone or something else to deceive the target or obtain unauthorized access to systems, information, or resources. In such attacks, the attacker alters their name, IP address, or other attributes to fool the victim into thinking they are engaging with a legitimate entity. Spoofing attacks can take place via a variety of channels, including, ARP and DNS spoofing. Therefore. Spoofing attacks can have serious consequences. We proposed a new approach based on three machine learning models LightGBM, Gradient Boost, and XGBoost to classify attacks on spoofing, we used Chi-square to select the best features to get the highest performance, and we demonstrated that the results using Chi-square achieved higher results than without Chi-square and improved the result with a rate three percent of accuracy. In terms of results, LightGBM outperformed other models by achieving 89%, 91 %, 87 %, and 89 % for accuracy, precision, recall, and f1-score, respectively. This shows the potential and efficiency of Chi-square to achieve the best performance by selecting the best features, thus providing a secure system and identifying cyber-attacks on systems. © 2023 IEEE.

关键词： Internet of things

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Logistic Regression Classification for Assessing the Risk of Kidney Tumor 2

Logistic Regression Classification for Assessing the Risk of...

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2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Alzubi, Dalia Al Mamlook, Rabia Emhamed Nasayreh, Ahmad Aljaidi, Mohammad Alazab, Rami Gharaibeh, Hasan Al-Naamneh, Qais Concordia University Dep. Information and Systems Engineering Montreal Canada Trine University Dep. of Business Administration IN United States University Zawia Department of Industrial Engineering Tripoli Libya Yarmouk University Dep. Computer Science Irbid Jordan Zarqa University Dep. of Computer Science Zarqa Jordan Jordan University of Science and Technology Dep. Surgery and Urology Irbid Jordan Applied Science Private University Dep. of Cyber Security Amman Jordan

ISBN: (纸本)9798350373363

The kidneys have the important function of filtering waste products and toxins from the blood in the human body. Any problems affecting the kidneys can potentially impact their efficiency and overall function. Kidney Tumor (KT) is a disease that specifically affects kidney cells and causes the abnormal growth of tissue in one or both kidneys. Assessing the risk of developing a kidney tumor and identifying the key factors that contribute to this risk are crucial for ensuring patient well-being. Additionally, this information assists doctors and specialists in making faster and more accurate diagnoses, determining appropriate treatment methods, and potentially influencing the course of the disease to minimize its severity and impact. Machine learning algorithms have recently been introduced to evaluate disease risks, and in this study, we specifically focus on examining the risk of kidney tumor development and investigating the influencing factors. We employed a logistic regression model to predict if a patient is at risk of developing a kidney tumor or not, and further categorized the samples into high-risk and low-risk groups. Our model was trained and tested using a unique dataset obtained from the (KAUH) hospital in Jordan, consisting of well-balanced metadata from 120 patients with kidney issues. Our work demonstrated accuracy results ranging from 90% to 98%. Ultimately, specialists can utilize our model as an additional tool to enhance the speed and accuracy of patient diagnoses © 2023 IEEE.

关键词： Tumors

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Theorem Proving in Higher Order Logics 1

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丛书名： Lecture Notes in computer Science

1000年

作者： David Basin Burkhart Wolff

ISBN: (数字)9783540451303

ISBN: (纸本)9783540406648

This volume constitutes the proceedings of the16th International Conference on Theorem Proving in Higher Order Logics (TPHOLs 2003) held September 8–12, 2003 in Rome, Italy. TPHOLs covers all aspects of theorem proving in higher order logics as well as related topics in theorem proving and veri?cation. TPHOLs 2003 was co-located with TABLEAUX, the International Con- rence on Automated Reasoning with Analytic Tableaux and Related Methods, and with Calculemus, the Symposium on the Integration of Symbolic Compu- tion and Mechanized Reasoning. There were 50 papers submitted to TPHOLs in the full research category, each of which was refereed by at least 3 reviewers, selected by the program c- ***,21wereacceptedforpresentationattheconference and publication in this volume. In keeping with tradition, TPHOLs 2003 also o?ered a venue for the presentation of work in progress, where researchers - vite discussion by means of a brief preliminary talk and then discuss their work at a poster session. A supplementary proceedings containing associated papers for work in progress was published by the computer science dep.rtment at the Universit¨ at Freiburg. The organizers are grateful to Jean-Raymond Abrial, Patrick Lincoln, and Dale Miller for agreeing to give invited talks at TPHOLs 2003. The TPHOLs conference traditionally changes continent each year in order to maximize the chances that researchers from around the world can attend.

关键词： Philosophy, general Mathematical Logic and Formal Languages Logic Design Software Engineering Logics and Meanings of Programs Artificial Intelligence

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Secure Password Using EEG-based BrainPrint System: Unlock Smartphone Password Using Brain-computer Interface Technology

Secure Password Using EEG-based BrainPrint System: Unlock Sm...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Alkhyeli, Zuwaina Alshehhi, Ayesha Alhemeiri, Mazna Aldhanhani, Salma Albalushi, Khalil Alnuaimi, Fatima Ali Belkacem, Abdelkader Nasreddine UAE University CIT Dep. Computer Science and Software Engineering Al Ain United Arab Emirates UAE University CIT Dep. Information Systems and Security Al Ain United Arab Emirates United Arab Emirates University CIT Dep. Computer & Network Engineering Al Ain United Arab Emirates Autonomous Robotics Research Center TII Abu Dhabi United Arab Emirates

ISBN: (纸本)9781665468190

As security becomes a strong factor in daily activities, finding secure ways to unlock machines and smartphones is a challenge due to hardware limitations and the high risk of hacking. Considering the level of security and privacy in the digital world, attackers tend to be one step ahead. Therefore, this technical paper introduces a brain-computer interface (BCI) for increasing subject-based security using unique biometric features as a solution to build complex passwords. The BCI measures brain changes and extracts relevant bio-features from each subject using non-invasive electroencephalogram (EEG) tests. The proposed system allows users to gain access to their devices using brain waves (bypass) instead of inserting their password manually (normal path), which saves the user time and upgrades the level of privacy as no physical actions are required during this process. This system is also well suited for individuals with mobility impairments. We used the P300-based BCI controlling paradigm which dep.nds on reading the electrical brain activity of the user when observing a particular object. The other feature of the system is that it can extract unique features of each individual brain to produce a network that uniquely identifies them, which is used as a security layer. Users need to enter their unique network to access their device with failed attempts requiring an EEG test to identify the user. The system plays an active role in facilitating user processes for authentication while accessing devices. The system establishes an urgent call whenever the user's brain currents command it to. The project outcomes were assessed by simulating the BCI before real-time implementation to determine errors and resolve the validity of the project scope. © 2022 IEEE.

关键词： Brain computer interface

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