Hadoop Based Defense Solution to Handle Distributed Denial of Service (DDoS) Attacks

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Journal of Information Security

ISSN Print: 2153-1234
ISSN Online: 2153-1242
www.scirp.org/journal/jis
E-mail: jis@scirp.org

Google-based Impact Factor: 3.25
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"Hadoop Based Defense Solution to Handle Distributed Denial of Service (DDoS) Attacks"
written by Shweta Tripathi, Brij Gupta, Ammar Almomani, Anupama Mishra, Suresh Veluru,
published by Journal of Information Security, Vol.4 No.3, 2013

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	Ddos attack detection through digital twin technique in metaverse
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[2]	Machine Learning and Artificial Intelligence in Cybersecurity
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[3]	Artificial intelligence model for DDOS-detection
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[4]	Use of Blockchain in Crypto-Currency to secure cloud forensic trails
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[5]	IoT Security using Machine Learning Techniques
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[6]	Cyber Security Traits of a Future-Ready Organization
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[7]	Cloud data assured deletion scheme based on dynamic sliding window
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[8]	DDoSDet: An approach to Detect DDoS attacks using Neural Networks
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[9]	Hadoop Distributed File System Security Challenges and Examination of Unauthorized Access Issue
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[10]	Detection of DDOS Attack Using IDS Mechanism: A Review
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[11]	Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems
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[12]	A Deep and Efficient Analysis of DDOS Attack in Software Defined Network
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[13]	A Comparative Analysis of Machine Learning-Based Website Phishing Detection Using URL Information
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[14]	Decentralized approach for data security of Medical IoT Devices
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[15]	The Presentation of a New Defense Framework Against the Distributed Denial of Service Attacks Using the Software Defined Network
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[16]	Analysis of Machine Learning Based DDoS Attack Detection Techniques in Software Defined Network
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[17]	Defensive Approach using Blockchain Technology against Distributed Denial of Service attacks
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[18]	An Integrated BIM-IoT approach to support energy monitoring
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[19]	A big data and deep learning based approach for ddos detection in cloud computing environment
	2021 IEEE 10th Global …, 2021

[20]	How IoT is Making DDoS Attacks More Dangerous
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[21]	Machine Learning Approaches for Combating Distributed Denial of Service Attacks in Modern Networking Environments
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[22]	Analysis of Machine learning based XSS attack Detection Techniques
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[23]	Advancement of Cloud Computing and Big Data Analytics in Healthcare Sector Security
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[24]	Challenges of the System and Network Administration
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[25]	A lightweight Anomaly based DDoS flood attack detection for Internet of vehicles
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[26]	Denial of Service Attacks: Difference in Rates, Duration, and Financial Damages and the Relationship Between Company Assets and Revenues
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[27]	A Detailed Analysis on Intrusion Identification Mechanism in Cloud Computing and Datasets
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[28]	Uma Metodologia para análise de incidentes de segurança da informação
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[29]	Cross-site Scripting Attacks: Classification, Attack, and Countermeasures
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[30]	An Economic Incentive-Based Risk Transfer Approach for Defending Against DDoS Attacks
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[31]	The detection method of low-rate DoS attack based on multi-feature fusion
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[32]	A Comprehensive Survey on DDoS Attacks and Recent Defense Mechanisms
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[33]	Ways to eliminate DDos attacks
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[34]	Методы обнаружения и предотвращения DDOS-атак
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[35]	Applying Multi-Level Theory to an Information Security Incident Domain Ontology.
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[36]	Systematic review of aspects of DDoS attacks detection
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[37]	Applying Multi-Level Theory to an Information Security Incident Domain Ontology
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[38]	A Review on Detection of DDOS Attack Using Machine Learning and Deep Learning Techniques
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[39]	Développement d'un protocole SCADA temps réel sécurisé à base de l'IEC 60870-5-101
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[40]	Smart Card Security: Applications, Attacks, and Countermeasures
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[41]	DDoS Attacks—Analysis and Prevention
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[42]	An improved agent-based adaptive protection model for distributed denial of service flooding attack and flash crowd flooding traffic
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[43]	The Impact of Crypto-Currency Risks on the Use of Blockchain for Cloud Security and Privacy
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[44]	An efficient index structure for distributed k-nearest neighbours query processing
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[45]	Fixing the Cloud Forensic Problem with Blockchain
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[46]	Multi-agent-based DDoS detection on big data systems
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[47]	Security Analytics Tools and Implementation Success Factors: Instrument Development Using Delphi Approach and Exploratory Factor Analysis
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[48]	Could Block Chain Technology Help Resolve the Cloud Forensic Problem?
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[49]	Cashing in on Cyberpower: How Interdependent Actors Seek Economic Outcomes in a Digital World
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[50]	Researching Cyber Weapons: An Enumerative Bibliography
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[51]	Network Anomaly Detection and Prevention using Statistical and Machine Learning Approaches
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[52]	Forecasting problems in cybersecurity: applying econometric techniques to measure IT risk
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[53]	A Game Theory Model for Detection and Mitigation of Ddos Attacks on Web Servers
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[54]	Performance Improvement of MapReduce for Heterogeneous Clusters Based on Efficient Locality and Replica Aware Scheduling (ELRAS) Strategy.
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[55]	Collaborative detection and filtering techniques against denial of service attacks in cloud computing
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[56]	DDoS Attacks: Tools, Mitigation Approaches, and Probable Impact on Private Cloud Environment
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[57]	COLLABORATIVE DETECTION AND FILTERING TECHNIQUES AGAINST DENIAL OF SERVICE ATTACKS IN CLOUD COMPUTING.
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[58]	Towards Large-Scale, Heterogeneous Anomaly Detection Systems in Industrial Networks: A Survey of Current Trends
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[59]	Using SDN Approach to Secure Cloud Servers against Flooding Based DDoS Attacks
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[60]	Foreword
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[61]	Data-Driven Anomaly Detection in Industrial Networks
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[62]	An Empirical Study of The Impact of DoS, DDoS Attacks on Various Web Servers and Application Servers
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[63]	Denial of service attacks detection using synchronization packets analysis
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[64]	Designing a Robust Closed-Loop Intrusion Detection Predictive Model Using Signal Processing Techniques in Cloud Computing Environment
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[65]	Performance Improvement of MapReduce for Heterogeneous Clusters Based on Efficient Locality and Replica Aware Scheduling (ELRAS) Strategy
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[66]	HADM: detection of HTTP GET flooding attacks by using Analytical hierarchical process and Dempster–Shafer theory with MapReduce
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[67]	Recent Developments on Security and Reliability in Large-Scale Data Processing with MapReduce
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[68]	Graphics processing unit based next generation DDoS prevention system
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[69]	Comparative analysis of features based machine learning approaches for phishing detection
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[70]	A survey of cloud-based network intrusion detection analysis
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[71]	BENEFITS AND CHALLENGES OF THE ADOPTION OF CLOUD COMPUTING IN BUSINESS
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[72]	Recent survey of various defense mechanisms against phishing attacks
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[73]	Bigdata platform based approach for defending against DDoS
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[74]	Securing cloud computing.
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[75]	Distributed Denial of Service Prevention Techniques
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[76]	A Novel approach for Detection of Distributed Denial of Service attack in VANET
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[77]	Intrusion Detection and Countermeasure of Virtual Cloud Systems-State of the Art and Current Challenges
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[78]	Safety of data warehouse for remote laboratories in Laboratory Management System and network of road junctions
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[79]	Distributed Denial of Service (DDOS) Attack, Networks, Tools and DEFENSE.
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[80]	Defending Against DDOS Flooding Attacks-A Data Streaming Approach
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[81]	Analysis of Denial of Services (DOS) Attacks and Prevention Techniques
	International Journal of Engineering Research and Technology, 2015

[82]	Similarity Detection via Random Subsets for Cyber War Protection in Big Data using Hadoop Framework
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[83]	Defence for Distributed Denial of Service Attacks in Cloud Computing
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[84]	DDoS detection and filtering technique in cloud environment using GARCH model
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[85]	A Proactive Approach to Intrusion Detection in Cloud Software as a Service
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[86]	Botnet-originated DDoS attacks: Overview and Mitigation
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[87]	Detection of DDoS attack in VANET using LPN (Local Protection Node)
	2015

[88]	THRESHOLD BASED APPROACH TO DETECT DDOS ATTACKS IN CLOUD
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[89]	Defense against DoS attack: PSO approach in virtualization
	2014

[90]	Presenting a pattern for detection of denial of service attacks with web mining technique and fuzzy logic approach
	2014

[91]	An Efficient Attack Resistance Model Using Application Based Polynomial Distribution
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[92]	Autonomous Agent for DDoS Attack Detection and Defense in an Experimental Testbed
	International Journal of Fuzzy Systems, 2014

[93]	Cyber Conflict Bibliography
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[94]	Digital compensation for timing mismatches in interleaved ADCs
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[95]	MINISTÉRIO DA DEFESA EXÉRCITO BRASILEIRO DEPARTAMENTO DE CIÊNCIA E TECNOLOGIA INSTITUTO MILITAR DE ENGENHARIA PROGRAMA DE …


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[97]	Evolving Conversational AI: Analyzing the Development and Advancements in ChatGPT


[98]	Analysis of Rumour and Fake News Detection Techniques


[99]	A MODEL OF PREVENTING DDOS ATTACK USING IN-HYPERVISOR HOST-BASED IDPS


[100]	Ethical Considerations in the Deployment of AI Chatbots: Lessons from ChatGPT


[101]	Building Resilience Trust and Security in the Evolution to 6G Networks


[102]	The Crucial Role of Change Request Analysis in Enhancing 3GPP Security


[103]	Data Privacy with Elliptic Curve Cryptography


[104]	Advanced Techniques for Detecting Phishing URLs


[105]	Cyber Security in Healthcare


[106]	Analysing Ransomware Attacks and Strategies for Defence


[107]	Enhancing Cyber Security in the Banking Sector with Chatbot Assistance


[108]	Cybersecurity in Healthcare: Safeguarding the Integrity of Medical Imaging Data


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[111]	Exploring the Synergy of Blockchain and Federated Learning in Online Voting Systems


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[115]	A Meta-Learning Chatbot Assistance against Evolving Cyber-Attacks


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[117]	The Future of Federated Learning: Collaborative Intelligence in a Decentralized World


[118]	Enhancing Player Experience and Data Privacy: Federated Learning in Online Gaming Platforms


[119]	Mechanism, Tools and Techniques to Mitigate Distributed Denial of Service Attacks

[1]	DDoS Attack Detection Through Digital Twin Technique in Metaverse 2023 IEEE International Conference on Consumer Electronics (ICCE), 2023 DOI:10.1109/ICCE56470.2023.10043433

[2]	Cyber Security, Privacy and Networking Lecture Notes in Networks and Systems, 2022 DOI:10.1007/978-981-16-8664-1_16

[3]	Detection of DDOS Attack Using IDS Mechanism: A Review 2022 1st International Conference on Informatics (ICI), 2022 DOI:10.1109/ICI53355.2022.9786899

[4]	A Comparative Analysis of Machine Learning-Based Website Phishing Detection Using URL Information 2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI), 2022 DOI:10.1109/PRAI55851.2022.9904055

[5]	Big Data Analytics for Internet of Things 2021 DOI:10.1002/9781119740780.ch13

[6]	Machine Learning Approaches for Combating Distributed Denial of Service Attacks in Modern Networking Environments IEEE Access, 2021 DOI:10.1109/ACCESS.2021.3062909

[7]	Big Data Analytics for Internet of Things 2021 DOI:10.1002/9781119740780.ch13

[8]	A Big Data and Deep Learning based Approach for DDoS Detection in Cloud Computing Environment 2021 IEEE 10th Global Conference on Consumer Electronics (GCCE), 2021 DOI:10.1109/GCCE53005.2021.9622091

[9]	An Economic Incentive-Based Risk Transfer Approach for Defending Against DDoS Attacks International Journal of E-Services and Mobile Applications, 2020 DOI:10.4018/IJESMA.2020070104

[10]	Handbook of Research on Intrusion Detection Systems Advances in Information Security, Privacy, and Ethics, 2020 DOI:10.4018/978-1-7998-2242-4.ch010

[11]	Cloud Security 2019 DOI:10.4018/978-1-5225-8176-5.ch031

[12]	Innovations in Computer Science and Engineering Lecture Notes in Networks and Systems, 2019 DOI:10.1007/978-981-10-8201-6_1

[13]	The Impact of Crypto-Currency Risks on the Use of Blockchain for Cloud Security and Privacy 2018 International Conference on High Performance Computing & Simulation (HPCS), 2018 DOI:10.1109/HPCS.2018.00111

[14]	Performance Improvement of MapReduce for Heterogeneous Clusters Based on Efficient Locality and Replica Aware Scheduling (ELRAS) Strategy Wireless Personal Communications, 2017 DOI:10.1007/s11277-017-3953-5

[15]	Using SDN Approach to Secure Cloud Servers against Flooding Based DDoS Attacks 2017 25th International Conference on Systems Engineering (ICSEng), 2017 DOI:10.1109/ICSEng.2017.31

[16]	Towards Large-Scale, Heterogeneous Anomaly Detection Systems in Industrial Networks: A Survey of Current Trends Security and Communication Networks, 2017 DOI:10.1155/2017/9150965

[17]	Graphics processing unit based next generation DDoS prevention system 2016 4th International Symposium on Digital Forensic and Security (ISDFS), 2016 DOI:10.1109/ISDFS.2016.7473518

[18]	A survey of cloud-based network intrusion detection analysis Human-centric Computing and Information Sciences, 2016 DOI:10.1186/s13673-016-0076-z

[19]	HADM: detection of HTTP GET flooding attacks by using Analytical hierarchical process and Dempster-Shafer theory with MapReduce Security and Communication Networks, 2016 DOI:10.1002/sec.1611

[20]	Recent survey of various defense mechanisms against phishing attacks Journal of Information Privacy and Security, 2016 DOI:10.1080/15536548.2016.1139423

[21]	HADM: detection of HTTP GET flooding attacks by using Analytical hierarchical process and Dempster–Shafer theory with MapReduce Security and Communication Networks, 2016 DOI:10.1002/sec.1611

[22]	DDoS detection and filtering technique in cloud environment using GARCH model 2015 IEEE 4th Global Conference on Consumer Electronics (GCCE), 2015 DOI:10.1109/GCCE.2015.7398603

[23]	Achieving Enterprise Agility through Innovative Software Development Advances in Systems Analysis, Software Engineering, and High Performance Computing, 2015 DOI:10.4018/978-1-4666-8510-9.ch013

[24]	Defence for Distributed Denial of Service Attacks in Cloud Computing Procedia Computer Science, 2015 DOI:10.1016/j.procs.2015.12.037

[25]	Presenting a pattern for detection of denial of service attacks with web mining technique and fuzzy logic approach 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014 DOI:10.1109/ICCICCT.2014.6992947

[26]	Defense against DoS attack: PSO approach in virtualization 2014 Sixth International Conference on Advanced Computing (ICoAC), 2014 DOI:10.1109/ICoAC.2014.7229709

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