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For further details contact: N.RAJASEKARAN B.E M.S 9841091117,9840103301. IMPULSE TECHNOLOGIES, Old No 251, New No 304, 2nd Floor, Arcot road , Vadapalani , Chennai-26.
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For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
PhD Projects in Fog Computing Research Ideas
Innovative Topics in Fog Computing Projects
Eminent Concepts in Fog Computing Projects
Primary Tools in Fog Computing Projects
D pcode privacy preserving frequent visual patterns publication on cloud
D pcode privacy preserving frequent visual patterns publication on cloud
+91-9994232214,7806844441, ieeeprojectchennai@gmail.com,
www.projectsieee.com, www.ieee-projects-chennai.com
IEEE PROJECTS 2016-2017
-----------------------------------
Contact:+91-9994232214,+91-7806844441
Email: ieeeprojectchennai@gmail.com
Fog computing
Fog computing is the next stage of cloud computing. The presentation provides a comparison between cloud and fog computing and discusses how live migration is useful in the field of fog computing.
Introduction to Fog Computing
This document presents a seminar on fog computing given by Ajay Dhanraj Sirsat. It discusses the existing cloud computing system and its problems, proposes fog computing as an alternative system, and describes fog computing architecture and its advantages over cloud. Fog computing extends cloud services to the edge of the network to provide low latency and location awareness. It is well-suited for applications such as the Internet of Things, connected cars, smart grids, and smart buildings.
Fog computing 000
The seminar presentation introduced fog computing, which extends cloud computing and services to the edge of the network. Fog computing provides data, compute, and application services to end-users. It was developed to address limitations of cloud computing like high latency and lack of location awareness. Fog computing improves efficiency, latency, security, and supports real-time interactions through geographical distribution of resources at the edge of the network. The presentation covered fog computing characteristics, architecture, applications in areas like smart grids and vehicle networks, and concluded that fog computing will grow in helping network paradigms requiring fast processing.
Dynamic module deployment in a fog computing platform
Several applications, such as smart cities, smart homes and smart hospitals adopt Internet of Things (IoT) networks to collect data from IoT devices. The incredible growing speed of the number of IoT devices congests the networks and the large amount of data, which are streamed to data centers for further analysis, overload the data centers. In this paper, we implement a fog computing platform that leverages end devices, edge networks, and data centers to serve the IoT applications. In this paper, we focus on implementing a fog computing platform, which dynamically pushes programs to the devices. The programs pushed to the devices pre-process the data before transmitting them over the Internet, which reduces the network traffic and the load of data centers. We survey the existing platforms and virtualization technologies, and leverage them to implement the fog computing platform. Moreover, we formulate a deployment problem of the programs. We propose an efficient heuristic deployment algorithm to solve the problem. We also implement an optimal algorithm for comparisons. We conduct experiments with a real testbed to evaluate our algorithms and fog computing platform. The proposed algorithm shows near-optimal performance, which only deviates from optimal algorithm by at most 2% in terms of satisfied requests. Moreover, the proposed algorithm runs in real-time, and is scalable. More precisely, it computes 1000 requests with 500 devices in <; 2 seconds. Last, the implemented fog computing platform results in real-time deployment speed: it deploys 20 requests <; 10 seconds.
Fog Computing and the Internet of Things
The document discusses the integration of fog computing with Internet of Things (IoT) applications. It introduces fog computing and how it extends cloud computing by providing data processing and storage locally at IoT devices to address challenges of latency and mobility. Benefits of fog computing include low latency, scalability, and flexibility to support various IoT applications like smart homes, healthcare, traffic lights, and connected cars. Challenges of integrating fog computing with IoT include security, privacy, resource estimation, and ensuring communication between fog servers and the cloud. The document reviews open issues and concludes by discussing future research directions for fog computing and IoT integration.
Recommended
32
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
PhD Projects in Fog Computing Research Ideas
Innovative Topics in Fog Computing Projects
Eminent Concepts in Fog Computing Projects
Primary Tools in Fog Computing Projects
D pcode privacy preserving frequent visual patterns publication on cloud
D pcode privacy preserving frequent visual patterns publication on cloud
+91-9994232214,7806844441, ieeeprojectchennai@gmail.com,
www.projectsieee.com, www.ieee-projects-chennai.com
IEEE PROJECTS 2016-2017
-----------------------------------
Contact:+91-9994232214,+91-7806844441
Email: ieeeprojectchennai@gmail.com
Fog computing
Fog computing is the next stage of cloud computing. The presentation provides a comparison between cloud and fog computing and discusses how live migration is useful in the field of fog computing.
Introduction to Fog Computing
This document presents a seminar on fog computing given by Ajay Dhanraj Sirsat. It discusses the existing cloud computing system and its problems, proposes fog computing as an alternative system, and describes fog computing architecture and its advantages over cloud. Fog computing extends cloud services to the edge of the network to provide low latency and location awareness. It is well-suited for applications such as the Internet of Things, connected cars, smart grids, and smart buildings.
Fog computing 000
The seminar presentation introduced fog computing, which extends cloud computing and services to the edge of the network. Fog computing provides data, compute, and application services to end-users. It was developed to address limitations of cloud computing like high latency and lack of location awareness. Fog computing improves efficiency, latency, security, and supports real-time interactions through geographical distribution of resources at the edge of the network. The presentation covered fog computing characteristics, architecture, applications in areas like smart grids and vehicle networks, and concluded that fog computing will grow in helping network paradigms requiring fast processing.
Dynamic module deployment in a fog computing platform
Several applications, such as smart cities, smart homes and smart hospitals adopt Internet of Things (IoT) networks to collect data from IoT devices. The incredible growing speed of the number of IoT devices congests the networks and the large amount of data, which are streamed to data centers for further analysis, overload the data centers. In this paper, we implement a fog computing platform that leverages end devices, edge networks, and data centers to serve the IoT applications. In this paper, we focus on implementing a fog computing platform, which dynamically pushes programs to the devices. The programs pushed to the devices pre-process the data before transmitting them over the Internet, which reduces the network traffic and the load of data centers. We survey the existing platforms and virtualization technologies, and leverage them to implement the fog computing platform. Moreover, we formulate a deployment problem of the programs. We propose an efficient heuristic deployment algorithm to solve the problem. We also implement an optimal algorithm for comparisons. We conduct experiments with a real testbed to evaluate our algorithms and fog computing platform. The proposed algorithm shows near-optimal performance, which only deviates from optimal algorithm by at most 2% in terms of satisfied requests. Moreover, the proposed algorithm runs in real-time, and is scalable. More precisely, it computes 1000 requests with 500 devices in <; 2 seconds. Last, the implemented fog computing platform results in real-time deployment speed: it deploys 20 requests <; 10 seconds.
Fog Computing and the Internet of Things
The document discusses the integration of fog computing with Internet of Things (IoT) applications. It introduces fog computing and how it extends cloud computing by providing data processing and storage locally at IoT devices to address challenges of latency and mobility. Benefits of fog computing include low latency, scalability, and flexibility to support various IoT applications like smart homes, healthcare, traffic lights, and connected cars. Challenges of integrating fog computing with IoT include security, privacy, resource estimation, and ensuring communication between fog servers and the cloud. The document reviews open issues and concludes by discussing future research directions for fog computing and IoT integration.
FOG COMPUTING- Presentation
Fog computing is a paradigm that extends cloud computing and services to the edge of the network, similar to cloud but providing data computation, storage, and application services closer to users. This helps address issues with cloud like limited bandwidth, latency, and security vulnerabilities. Fog computing uses techniques like user behavior profiling and decoy systems to detect unauthorized access and secure data in the cloud from attackers. It has a decentralized architecture with fog devices acting as intermediaries between user devices and the cloud. Potential applications and scenarios of fog computing include smart grids, smart traffic lights, software defined networks, and the Internet of Things.
Evolving a Cyber Space Doctrine
When presented in 2010, this presentation provided a novel concept for moving from passive security to active defense. Leveraging lessons learned from BearingPoint and Deloitte's R&D on Collaborative Situational Awareness for Decision Making, this presentation put forward a framework for integrating cyber security system to enhance collaboration and more effectively integrate information from desperate sources.
Fog Computing
Fog computing is a model that processes and stores data closer to end users, at the edge of the network, rather than keeping all data in the cloud. It aims to extend cloud computing by providing greater security and faster analytics by keeping data closer to its source. Fog computing monitors data access in the cloud and can detect abnormal patterns to help minimize insider attacks. While it provides some advantages over cloud, fog computing also introduces more complexity in detecting attacks and affected users or files.
Fog computing document
Cloud computing involves clusters of servers connected over a network that allow users to access computational resources and pay only for what they use. While cloud computing provides advantages like flexibility and cost savings, security is a main concern as user data is stored remotely. Fog computing is a new technique that extends cloud computing by providing additional security measures and isolating user data at the network edge to enhance privacy. It aims to place data closer to end users to improve security in cloud environments.
Fog ppt
This document discusses fog computing. Fog computing extends cloud computing by providing data, compute, storage, and application services closer to the edge of the network. It was introduced by Cisco to efficiently share and store data between distributed devices in the Internet of Things. Fog computing helps address issues with cloud computing like high latency by processing data locally at edge devices instead of sending all data to a centralized cloud. It provides advantages like improved security, reduced data transfers across networks, and better support for real-time applications. The document compares fog and cloud computing and concludes that fog computing will grow in helping network paradigms that require fast processing.
Seminar ppt fog comp
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network .This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
Fog computing and internet of things
This document discusses fog computing and its role in supporting Internet of Things applications. It defines fog computing as extending cloud computing to the edge of the network to enable applications requiring low latency, mobility support, and location awareness. Key characteristics of fog include its geographical distribution, support for real-time interactions, and role in streaming and sensor applications. The document argues fog is well-suited as a platform for connected vehicles, smart grids, smart cities, and wireless sensor networks due to its ability to meet latency and mobility requirements. It also describes the interplay between fog and cloud for data analytics, with fog handling real-time analytics near data sources and cloud providing long-term global analytics.
Fog computing : The new age Technology
This document provides an overview of fog computing, including its origins at Cisco, its advantages over cloud computing for applications with low latency requirements like IoT, and examples of applications that could benefit like smart cities and healthcare. Fog computing processes data locally at the edge of the network rather than sending all data to the cloud, helping address issues of bandwidth constraints, network congestion, and latency for real-time applications. Security challenges also exist with protecting data and devices at the edge of the network in fog computing environments.
Fog Computing
This document provides an introduction to fog computing. Fog computing is a model where data processing and applications occur at the edge of networks rather than solely in the cloud. This helps address limitations of cloud computing like high latency and bandwidth usage. Key characteristics of fog computing include low latency, geographical distribution, mobility support, and real-time interactions. Potential applications discussed are connected cars, smart grids, and smart traffic lights, which can benefit from fog computing's low latency and location awareness.
Fog Computing Reality Check: Real World Applications and Architectures
Is Fog Computing just a buzz or a real business?
The IoT is flooded with a variety of platforms and solutions. Fog Computing has been notably appearing as an evolving term in the context of IoT software. There is skepticism that Fog Computing is just another buzzword destined to disappear in the dust of time. Get insight from concrete business cases in a variety of IoT verticals – Agriculture, Industrial Manufacturing, Transportation, Smart & Connected Communities etc. and learn how Fog Computing can play a substantial role in each one of these verticals. Develop a judicious point of view with respect to the future of Fog Computing through market research, technology disruption vectors and ROI use cases presented in this session.
Fog computing
This presentation include some of limitations of cloud computing that motivate cisco to come up with new fog computing .Fog is nothing but cloud or we can say it is an extension of the cloud.
Cloud computing ppts
The document provides an overview of cloud computing, including its history, key features, deployment models, layers, engineering, storage, interconnection of clouds, and issues. It discusses how cloud computing evolved from earlier concepts and allows users to access computing resources over the internet on an as-needed basis. Some challenges include privacy, legal concerns, use of open standards and security issues.
Io t technologies_ppt-2
This document provides an overview of machine learning for IoT analytics. It discusses what IoT is and how it has evolved from standalone computers to include cloud and physical objects. It describes common IoT applications and architectures including multi-layer architectures with device, fog, and cloud layers. It then discusses how machine learning can be used at each layer for tasks like data analytics, classification, and prediction. It provides examples of using techniques like PCA, SVM, LDA, and decision trees for water and fruit quality analysis applications. Finally, it discusses IoT security challenges and proposes models for device authentication, end-to-end encryption, and data integrity.
ISACA GRC-CYBER CALL FOR PAPERS ABSTRACT v.3.0
- The document discusses the need for a layered and holistic approach to cyber security including security management, risk containment, threat response, and crisis management given the changing landscape with IoT and cloud.
- It emphasizes applying confidentiality, integrity and availability principles to information and considering information as the key element and most valuable asset rather than physical products.
- Achieving situational awareness across edge, core, logical and physical layers through a combination of perimeter defenses, deep inspection, data analytics and monitoring is key to proper information protection.
cloud security using Fog Computing
This document summarizes a research paper presentation on cloud and fog computing. The presentation discusses:
1) The security issues in cloud computing and how fog computing can address them through techniques like user profiling and decoy documents.
2) The characteristics, architecture, applications and advantages of fog computing, which extends cloud services to the edge of the network.
3) How fog computing helps improve cloud computing security by processing and analyzing data locally, reducing traffic to the cloud and misleading attackers through decoy documents.
A Study on Cloud and Fog Computing Security Issues and Solutions
Cloud computing is the significant part of the data world. The security level in cloud is undefined. Fog computing is the new buzz word added to the technical world. And the term Fog was coined by CISCO. The need for Fog computing is security and gets the data more closely to the end-user. Fog Computing is not going to replace the Cloud computing, it will be acting as the intermediate layer for securing the data which is stored inside the cloud. The principal idea of this paper is to provide data safety measures to the Cloud storage through Fog Computing. Fog Computing will be playing the vital role for the future technology. The Internet of Things (IoT) will be using the Fog computing to implement the smart World concept. So, in the future we have to handle huge amount of data and we need to provide the security for the Data. This study gives the security solutions available for the different issues.
Fog computing
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider.
For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
CONCLUSION
This proposal of monitoring data access patterns by profiling user behavior to determine if and when a malicious insider illegitimately accesses someone’s documents in a Cloud service. Decoy documents stored in the Cloud alongside the user’s real data also serve as sensors to detect illegitimate access. Once unauthorized data access or exposure is suspected, and later verified, with challenge questions for instance, this inundate the malicious insider with bogus information in order to dilute the user’s real data. Such preventive attacks that rely on disinformation technology could provide unprecedented levels of security in the Cloud and in social networks.
TACO-DTN
This document presents a time-aware publish/subscribe model for content dissemination in delay-tolerant networks (DTNs). It proposes TACO-DTN, a prototype that uses temporal descriptions of topics to match publications and subscriptions based on time. Simulations show it effectively routes events in a mixed DTN topology. Future work includes real mobility traces and applications to validate the approach.
Fog Computing
All the major details of Fog Computing is discussed in this PPT, its better use for you to easily get the knowledge about Fog Computing
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BioTechnique is a full service sterile injectable contract manufacturing organization located in Madison, WI that provides aseptic manufacturing services including aseptic fill and finish, aseptic lyophilization, drug compounding and formulation, and manufacturing of cytotoxic and high potency drugs. They aim to be a partner to clients from clinical trials through commercialization by providing high quality sterile manufacturing and regulatory support to help get products to market.
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FOG COMPUTING- Presentation
Fog computing is a paradigm that extends cloud computing and services to the edge of the network, similar to cloud but providing data computation, storage, and application services closer to users. This helps address issues with cloud like limited bandwidth, latency, and security vulnerabilities. Fog computing uses techniques like user behavior profiling and decoy systems to detect unauthorized access and secure data in the cloud from attackers. It has a decentralized architecture with fog devices acting as intermediaries between user devices and the cloud. Potential applications and scenarios of fog computing include smart grids, smart traffic lights, software defined networks, and the Internet of Things.
Evolving a Cyber Space Doctrine
When presented in 2010, this presentation provided a novel concept for moving from passive security to active defense. Leveraging lessons learned from BearingPoint and Deloitte's R&D on Collaborative Situational Awareness for Decision Making, this presentation put forward a framework for integrating cyber security system to enhance collaboration and more effectively integrate information from desperate sources.
Fog Computing
Fog computing is a model that processes and stores data closer to end users, at the edge of the network, rather than keeping all data in the cloud. It aims to extend cloud computing by providing greater security and faster analytics by keeping data closer to its source. Fog computing monitors data access in the cloud and can detect abnormal patterns to help minimize insider attacks. While it provides some advantages over cloud, fog computing also introduces more complexity in detecting attacks and affected users or files.
Fog computing document
Cloud computing involves clusters of servers connected over a network that allow users to access computational resources and pay only for what they use. While cloud computing provides advantages like flexibility and cost savings, security is a main concern as user data is stored remotely. Fog computing is a new technique that extends cloud computing by providing additional security measures and isolating user data at the network edge to enhance privacy. It aims to place data closer to end users to improve security in cloud environments.
Fog ppt
This document discusses fog computing. Fog computing extends cloud computing by providing data, compute, storage, and application services closer to the edge of the network. It was introduced by Cisco to efficiently share and store data between distributed devices in the Internet of Things. Fog computing helps address issues with cloud computing like high latency by processing data locally at edge devices instead of sending all data to a centralized cloud. It provides advantages like improved security, reduced data transfers across networks, and better support for real-time applications. The document compares fog and cloud computing and concludes that fog computing will grow in helping network paradigms that require fast processing.
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ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network .This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
Fog computing and internet of things
This document discusses fog computing and its role in supporting Internet of Things applications. It defines fog computing as extending cloud computing to the edge of the network to enable applications requiring low latency, mobility support, and location awareness. Key characteristics of fog include its geographical distribution, support for real-time interactions, and role in streaming and sensor applications. The document argues fog is well-suited as a platform for connected vehicles, smart grids, smart cities, and wireless sensor networks due to its ability to meet latency and mobility requirements. It also describes the interplay between fog and cloud for data analytics, with fog handling real-time analytics near data sources and cloud providing long-term global analytics.
Fog computing : The new age Technology
This document provides an overview of fog computing, including its origins at Cisco, its advantages over cloud computing for applications with low latency requirements like IoT, and examples of applications that could benefit like smart cities and healthcare. Fog computing processes data locally at the edge of the network rather than sending all data to the cloud, helping address issues of bandwidth constraints, network congestion, and latency for real-time applications. Security challenges also exist with protecting data and devices at the edge of the network in fog computing environments.
Fog Computing
This document provides an introduction to fog computing. Fog computing is a model where data processing and applications occur at the edge of networks rather than solely in the cloud. This helps address limitations of cloud computing like high latency and bandwidth usage. Key characteristics of fog computing include low latency, geographical distribution, mobility support, and real-time interactions. Potential applications discussed are connected cars, smart grids, and smart traffic lights, which can benefit from fog computing's low latency and location awareness.
Fog Computing Reality Check: Real World Applications and Architectures
Is Fog Computing just a buzz or a real business?
The IoT is flooded with a variety of platforms and solutions. Fog Computing has been notably appearing as an evolving term in the context of IoT software. There is skepticism that Fog Computing is just another buzzword destined to disappear in the dust of time. Get insight from concrete business cases in a variety of IoT verticals – Agriculture, Industrial Manufacturing, Transportation, Smart & Connected Communities etc. and learn how Fog Computing can play a substantial role in each one of these verticals. Develop a judicious point of view with respect to the future of Fog Computing through market research, technology disruption vectors and ROI use cases presented in this session.
Fog computing
This presentation include some of limitations of cloud computing that motivate cisco to come up with new fog computing .Fog is nothing but cloud or we can say it is an extension of the cloud.
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The document provides an overview of cloud computing, including its history, key features, deployment models, layers, engineering, storage, interconnection of clouds, and issues. It discusses how cloud computing evolved from earlier concepts and allows users to access computing resources over the internet on an as-needed basis. Some challenges include privacy, legal concerns, use of open standards and security issues.
Io t technologies_ppt-2
This document provides an overview of machine learning for IoT analytics. It discusses what IoT is and how it has evolved from standalone computers to include cloud and physical objects. It describes common IoT applications and architectures including multi-layer architectures with device, fog, and cloud layers. It then discusses how machine learning can be used at each layer for tasks like data analytics, classification, and prediction. It provides examples of using techniques like PCA, SVM, LDA, and decision trees for water and fruit quality analysis applications. Finally, it discusses IoT security challenges and proposes models for device authentication, end-to-end encryption, and data integrity.
ISACA GRC-CYBER CALL FOR PAPERS ABSTRACT v.3.0
- The document discusses the need for a layered and holistic approach to cyber security including security management, risk containment, threat response, and crisis management given the changing landscape with IoT and cloud.
- It emphasizes applying confidentiality, integrity and availability principles to information and considering information as the key element and most valuable asset rather than physical products.
- Achieving situational awareness across edge, core, logical and physical layers through a combination of perimeter defenses, deep inspection, data analytics and monitoring is key to proper information protection.
cloud security using Fog Computing
This document summarizes a research paper presentation on cloud and fog computing. The presentation discusses:
1) The security issues in cloud computing and how fog computing can address them through techniques like user profiling and decoy documents.
2) The characteristics, architecture, applications and advantages of fog computing, which extends cloud services to the edge of the network.
3) How fog computing helps improve cloud computing security by processing and analyzing data locally, reducing traffic to the cloud and misleading attackers through decoy documents.
A Study on Cloud and Fog Computing Security Issues and Solutions
Cloud computing is the significant part of the data world. The security level in cloud is undefined. Fog computing is the new buzz word added to the technical world. And the term Fog was coined by CISCO. The need for Fog computing is security and gets the data more closely to the end-user. Fog Computing is not going to replace the Cloud computing, it will be acting as the intermediate layer for securing the data which is stored inside the cloud. The principal idea of this paper is to provide data safety measures to the Cloud storage through Fog Computing. Fog Computing will be playing the vital role for the future technology. The Internet of Things (IoT) will be using the Fog computing to implement the smart World concept. So, in the future we have to handle huge amount of data and we need to provide the security for the Data. This study gives the security solutions available for the different issues.
Fog computing
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider.
For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
CONCLUSION
This proposal of monitoring data access patterns by profiling user behavior to determine if and when a malicious insider illegitimately accesses someone’s documents in a Cloud service. Decoy documents stored in the Cloud alongside the user’s real data also serve as sensors to detect illegitimate access. Once unauthorized data access or exposure is suspected, and later verified, with challenge questions for instance, this inundate the malicious insider with bogus information in order to dilute the user’s real data. Such preventive attacks that rely on disinformation technology could provide unprecedented levels of security in the Cloud and in social networks.
TACO-DTN
This document presents a time-aware publish/subscribe model for content dissemination in delay-tolerant networks (DTNs). It proposes TACO-DTN, a prototype that uses temporal descriptions of topics to match publications and subscriptions based on time. Simulations show it effectively routes events in a mixed DTN topology. Future work includes real mobility traces and applications to validate the approach.
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FIRECOL: A COLLABORATIVE PROTECTION NETWORK FOR THE DETECTION OF FLOODING DDO...
The document describes FireCol, a system for detecting distributed denial-of-service (DDoS) flooding attacks. The core of FireCol is composed of intrusion prevention systems (IPSs) located at internet service providers that form virtual protection rings around hosts. The IPSs collaborate by exchanging selected traffic information to detect DDoS attacks early. FireCol was evaluated using simulations and real data, showing its effectiveness with low overhead and support for incremental deployment.
Presentation1 shweta
This document proposes a system called FireCol, which stands for a collaborative protection network for detecting flooding DDoS attacks. FireCol uses a distributed network of intrusion prevention systems located at internet service providers that form virtual protection rings around hosts. These systems collaborate by exchanging selected traffic information to detect DDoS attacks close to the source. The document outlines the architecture of FireCol and experimental results showing its effectiveness at detecting attacks with low overhead. Future work is mentioned to extend FireCol's capabilities.
Fire col a collaborative protection
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This paper proposes a system called FireCol for detecting and preventing distributed denial-of-service (DDoS) attacks. FireCol uses a distributed architecture of multiple intrusion prevention systems (IPS) forming protective rings around subscribed users. The IPS devices collaborate by exchanging traffic information to calculate scores for potential attacks. If a high score indicates a potential DDoS attack, the protective rings use parallel communication to verify the attack near the source before it reaches the victim. Simulation results show FireCol can effectively detect DDoS attacks while imposing low overhead and supporting scalability.
Project titles abstract_2012
This document contains titles and descriptions of 12 networking projects. It includes projects on topics like efficient full-text retrieval in peer-to-peer networks, density estimation in wireless ad hoc networks, detection of flooding DDoS attacks, game-theoretic pricing for video streaming, throughput and energy efficiency in wireless networks, and more. Each project description provides details on the research problem addressed, proposed solution, and relevant references. The document serves as a reference for potential final year project titles in networking.
An Efficient Hybrid-DNN for DDoS Detection and Classification in Software-Def...
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DDoS Defense for the Hosting Provider - Protection for you and your customers
Distributed Denial of Service (DDoS) attacks are major threats to hosting providers as well as datacenter operators, and traditional game plans for protecting shared infrastructure should be revisited to better protect availability and allow hosting providers to potentially create incremental revenue streams. DDoS attacks can have a devastating impact on not only the customer under attack, but also on the hosting provider and other customers within the same shared network infrastructure.
ddo-s attacks in cloud computing issued taxonomy and future direction
This document summarizes research on DDoS attacks in cloud computing. It begins with an introduction to the issues of DDoS attacks in cloud environments and the need for cloud-specific solutions. The document then presents a survey of contributions related to characterization, prevention, detection and mitigation of DDoS attacks in clouds. It develops a taxonomy to classify different solution approaches and identifies weaknesses that need to be addressed. It concludes by outlining design aspects for effective cloud-based DDoS attack solutions and provides evaluation metrics for comparing solutions.
Incapsula Enterprise is the best mitigation service provider with th.pdf
Incapsula Enterprise is the best mitigation service provider with the gold award winner and the
other two with silver and bronze award are F5 Silverline DDOS Protection and Arbor Cloud
respectively
With DDoS attacks growing in complexity and size daily, you need a DDoS protection service
with a robust network and variety of mitigation techniques to thwart any attacks directed at your
site. We found that Incapsula Enterprise, F5 Silverline DDoS Protection and Arbor Cloud
offered the best protection.
Incapsula’s growing global network and scrubbing capacities equip it with the size needed to
prevent large-scale volumetric attacks,27 data centers are connected which are located all over
the world, the service is prepared for even the most advanced DDoS attacks. In addition to
enormous network capacity and a high number of data centers, Incapsula hosts a variety of
mitigation techniques that intercept application layer, volumetric and protocol attacks.
With the recent acquisition of Defense.net, F5 has adjusted its service to offer cloud-based
mitigation technique, on-site and hybrid deployment methods,both hardware and the cloud is
used, F5 Silverline Protection is equipped for sophisticated DDoS attacks. This service surpasses
Incapsula in scrubbing capacity, it provides 2TB of bandwidth to filter, clean and remove
infected traffic. While the service does not offer unlimited mitigation, this protection service can
be used on-demand or always on, customizing it to fit the needs of any company.
Third one comes Arbor Cloud which offers a large network and scrubbing capacity and have
1.14TB of bandwidth, this server prepare the system for specialised volumetric attacks.variety of
protection techniques are provided by this service including IP blocking, rate limiting, automatic
bot discernment and more. While the cloud-based mitigation techniques are impressive, Arbor is
known for its hardware. The service is in a unique position, it\'s hardware is the challenge for it\'s
competitors
similar mitigation techniques is provided by all DDOS mitigation service providers to keep an
eye on any attacks and constant monitoring, they differ in price, deployment methods and
network size.It is not necessary that bigger mean better, the services that offer larger networks
and more mitigation technologies allow for more customization that you employ the best
protection service for your IT infrastructure.
Solution
Incapsula Enterprise is the best mitigation service provider with the gold award winner and the
other two with silver and bronze award are F5 Silverline DDOS Protection and Arbor Cloud
respectively
With DDoS attacks growing in complexity and size daily, you need a DDoS protection service
with a robust network and variety of mitigation techniques to thwart any attacks directed at your
site. We found that Incapsula Enterprise, F5 Silverline DDoS Protection and Arbor Cloud
offered the best protection.
Incapsula’s growing global network and scrubbing capacit.
Final report
This document describes a proposed SDN-based scheme for detecting and mitigating distributed denial-of-service (DDoS) attacks mounted by botnets. The scheme involves a DDoS blocking application running on an SDN controller that monitors network traffic flows and detects attacks. When an attack is detected, the application installs rules on SDN switches to block traffic from botnet sources while still allowing legitimate traffic. The target server implements CAPTCHA to differentiate legitimate and bot traffic during attacks. The scheme is implemented using the POX SDN controller and OpenFlow standards and tested on the Mininet emulator.
Encountering distributed denial of service attack utilizing federated softwar...
This research defines the distributed denial of service (DDoS) problem in software-defined-networks (SDN) environments. The proposes solution uses Software defined networks capabilities to reduce risk, introduces a collaborative, distributed defense mechanism rather than server-side filtration. Our proposed network detection and prevention agent (NDPA) algorithm negotiates the maximum amount of traffic allowed to be passed to server by reconfiguring network switches and routers to reduce the ports' throughput of the network devices by the specified limit ratio. When the passed traffic is back to normal, NDPA starts network recovery to normal throughput levels, increasing ports' throughput by adding back the limit ratio gradually each time cycle. The simulation results showed that the proposed algorithms successfully detected and prevented a DDoS attack from overwhelming the targeted server. The server was able to coordinate its operations with the SDN controllers through a communication mechanism created specifically for this purpose. The system was also able to determine when the attack was over and utilize traffic engineering to improve the quality of service (QoS). The solution was designed with a sophisticated way and high level of separation of duties between components so it would not be affected by the design aspect of the network architecture.
DISTRIBUTED DENIAL OF SERVICE ATTACK DETECTION AND PREVENTION MODEL FOR IOTBA...
Defending against Distributed Denial of Service (DDoS) in the Internet of Things (IoT) computing environment is a challenging task. DDoS attacks are type of collective attack in which attackers work together to compromise internet security and services. The resource-constrained devices used in IoT deployments have made it even easier for an attacker to break, because of the vast number of vulnerable IoT devices with significant compute power. This paper proposed an ensemble machine learning (ML) model using the bagging technique to detect and prevent DDoS attacks in the IoT computing environment. We carried out an Machine Learning experiment and evaluated our proposed model with the most recent DDoS attacks (CICDoS2019) dataset. We use seven validation metrics (classification accuracy, precision rate, recall rate, f1-score, Matthews Correlation Coefficient, false negative rate and false positive rate) to evaluate the performance of the proposed model. The results obtained in our experiment shows an improved performance with an overall maximum classification accuracy of 99.75%, precision rate of 99.99%, recall rate of 99.76%, f1-score of 99.87%, Matthews Correlation Coefficient of 0.000000214, false negative rate of 0.24% and 4.42% false positive rate.
Protecting the movable Endeavor with Network-Based validation and Virtual Com...
Abstract: A new security architecture for the mobile enterprise which uses network-based security and cloud
computing has been proposed in these paper. This newly proposed architecture is mainly for both simplifying
and enhancing the security of enterprises, and reinstates the currently disappearing security perimeter.
Keywords-cloud computing; cloud-based security; enterprise security architecture; mobile enterprise; networkbased
security; security.
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IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
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* Video Tutorials
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=======================
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* Voice Conference
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ITSecurity_DDOS_Mitigation
This document examines a proposed alternative solution to mitigate distributed denial of service (DDoS) attacks using crowd-sourced bandwidth. It discusses how DDoS attacks work and their impacts on organizations. The proposal aimed to leverage unused bandwidth from multiple clients to filter out malicious traffic and redirect valid traffic. However, the document concludes the concept is not currently feasible due to security, performance, and reliability issues from placing too much trust in clients and relying on slow public DNS propagation. Existing centralized DDoS mitigation solutions from companies are still recommended.
Hybrid cloud based firewalling
This architecture proposes a hybrid cloud-based firewalling approach to improve performance and reliability. The architecture has both a physical firewall and virtual firewalls in the cloud. Traffic is redirected from the physical firewall to the virtual firewalls in the cloud when the physical firewall becomes overloaded. This improves computational power by leveraging the resources of the cloud. Experimental results showed the hybrid approach improved latency, memory usage, and CPU performance compared to only using a physical firewall.
A Data Hiding Techniques Based on Length of English Text using DES and Attack...
The comparing recent proposal for multimedia applications network security remains an important topic for researchers. The security deals with both wired and wireless communication. Network is defined as it is a large system consisting of many similar parts that are connected together to allow the movement or communication between or along the parts or between the parts and a control center. There are the main components of the network information system such as end systems (terminals, servers) and intermediate systems (hubs, switches, gateways). Every node has its own set of vulnerabilities that can be related to hardware, software, protocol stack etc. Nodes are interconnected by physical supports in a network for example connected with cables in wired Local Area Network (LAN) or radio waves (Wi-Fi) in Wireless Local Area Network (WLAN). Some nodes are able to provide services (FTP, HTTP browsing, database access). If two nodes want to communicate together, they must be interconnected physically and logically. Network security deals with also information hiding technique. Now day’s security deals with heterogeneous networks. The use of different wireless and wired network which are working on different platform is heterogeneous. So design of network security for such type of heterogeneous network is difficult task.
Ijirsm poornima-km-a-survey-on-security-circumstances-for-mobile-cloud-computing
Ijirsm poornima-km-a-survey-on-security-circumstances-for-mobile-cloud-computingIJIR JOURNALS IJIRUSA
Establishing applications on on-demand infrastructures rather of building applica-tions on fixed and rigid infrastructures was provided by cloud computing provides. By merely exploiting into the cloud, initiatives can gain fast access to business applications or infrastructure resources with decreased Capital Expenditure (CAPEX). The more and more information is placed into the cloud by someone and initiatives, security issues begins to develop and raised. This paper discusses the different security issues that rise up about how secure the mo-bile cloud computing environment.Bn4301364368
This document discusses security issues related to data management in wireless communication and sensor networks over cloud environments. It begins by describing wireless sensor networks and cloud computing individually, noting key characteristics like location independence and on-demand access. It then discusses how wireless sensor networks and cloud computing can be integrated using technologies like PHP and MySQL. The main body of the document focuses on security challenges in cloud computing environments, including issues related to virtualization, networking, and browser-based attacks that can carry over risks from traditional systems. It concludes that secure data transmission to and from the cloud is an important issue that requires mitigation techniques like encryption algorithms.
What Is Openstack And Its Importance
OpenStack is open-source software for building private and public clouds. It provides services for compute, storage, and networking (networking projects allow resources to be shared across clouds). Using OpenStack can help enterprises reduce costs compared to vendor lock-in agreements and manage large server clusters, storage, and networks more efficiently.
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17
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IMPULSE TECHNOLOGIES,
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16
This document discusses energy-efficient strategies for cooperative multichannel MAC protocols. It introduces Distributed Information SHaring (DISH), which helps nodes make decisions by sharing information with neighboring nodes. This approach was shown to significantly increase throughput but had not addressed energy efficiency. The paper proposes two strategies: in-situ energy conscious DISH which uses existing nodes, and altruistic DISH which uses additional nodes called altruists. Evaluation shows altruistic DISH conserves 40-80% of energy, maintains throughput advantages, and more than doubles cost efficiency compared to protocols without this strategy. In-situ energy conscious DISH is only suitable in limited scenarios.
15
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25
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
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Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
24
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
23
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
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Chennai-26.
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Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
22
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
21
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N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
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Vadapalani ,
Chennai-26.
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Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
20
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N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
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19
CTVS is a novel data extraction and alignment method that combines tag and value similarity to extract data from query result pages. It first identifies and segments query result records in the pages and aligns them into a table with data values from the same attribute in the same column. CTVS handles cases where records are not contiguous due to auxiliary information and any nested structures within records. It also designs a new record alignment algorithm that aligns attributes pairwise and holistically using tag and value similarity. Experimental results show CTVS achieves high precision and outperforms existing methods.
18
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16
The document discusses a new algorithm for topic mining over asynchronous text sequences. The algorithm aims to explore correlations between multiple related text sequences that may have different time stamps. It consists of two alternating steps: 1) extracting common topics from sequences based on adjusted time stamps, and 2) adjusting time stamps according to the discovered topic time distributions. The approach is evaluated on research papers and news articles, demonstrating effectiveness in identifying topics across asynchronously published documents.
15
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IMPULSE TECHNOLOGIES,
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14
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N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
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Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
13
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N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
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12
The document presents a new approach called TSCAN for temporally summarizing topics from a collection of documents. TSCAN first derives the major themes of a topic from the eigenvectors of a temporal block association matrix. It then extracts significant events and their summaries for each theme by examining the eigenvectors. Finally, it associates the extracted events based on their temporal closeness and context similarity to form an evolution graph of the topic. Experiments on the TDT4 corpus show that temporal summaries generated by TSCAN present topics in a comprehensible form and are superior to existing summarization methods based on human references.
11
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N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
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www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
10
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
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Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
9
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IMPULSE TECHNOLOGIES,
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Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
8
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IMPULSE TECHNOLOGIES,
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www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
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Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
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Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
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Fire col a collaborative protection network
- 1. FireCol: A Collaborative Protection Network for the Detection of Flooding DDoS Attacks Abstract—Distributed denial-of-service (DDoS) attacks remain a major security problem, the mitigation of which is very hard especially when it comes to highly distributed botnet-based attacks. The early discovery of these attacks, although challenging, is necessary to protect end-users as well as the expensive network infrastructure resources. In this paper, we address the problem of DDoS attacks and present the theoretical foundation, architecture, and algorithms of FireCol. The core of FireCol is composed of intrusion prevention systems (IPSs) located at the Internet service providers (ISPs) level. The IPSs form virtual protection rings around the hosts to defend and collaborate by exchanging selected traffic information. The evaluation of FireCol using extensive simulations and a real dataset is presented, showing FireCol effectiveness and low overhead, as well as its support for incremental deployment in real networks.