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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
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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
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IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
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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
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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
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
future internetArticleERMOCTAVE A Risk Management Fra
future internet
Article
ERMOCTAVE: A Risk Management Framework for IT
Systems Which Adopt Cloud Computing
Masky Mackita 1, Soo-Young Shin 2 and Tae-Young Choe 3,*
1 ING Bank, B-1040 Brussels, Belgium; [email protected]
2 Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea;
[email protected]
3 Department of Computer Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea
* Correspondence: [email protected]; Tel.: +82-54-478-7526
Received: 22 June 2019; Accepted: 3 September 2019; Published: 10 September 2019
����������
�������
Abstract: Many companies are adapting cloud computing technology because moving to the cloud
has an array of benefits. During decision-making, having processed for adopting cloud computing,
the importance of risk management is progressively recognized. However, traditional risk management
methods cannot be applied directly to cloud computing when data are transmitted and processed by
external providers. When they are directly applied, risk management processes can fail by ignoring
the distributed nature of cloud computing and leaving numerous risks unidentified. In order to fix
this backdrop, this paper introduces a new risk management method, Enterprise Risk Management
for Operationally Critical Threat, Asset, and Vulnerability Evaluation (ERMOCTAVE), which combines
Enterprise Risk Management and Operationally Critical Threat, Asset, and Vulnerability Evaluation for
mitigating risks that can arise with cloud computing. ERMOCTAVE is composed of two risk management
methods by combining each component with another processes for comprehensive perception of risks.
In order to explain ERMOCTAVE in detail, a case study scenario is presented where an Internet seller
migrates some modules to Microsoft Azure cloud. The functionality comparison with ENISA and
Microsoft cloud risk assessment shows that ERMOCTAVE has additional features, such as key objectives
and strategies, critical assets, and risk measurement criteria.
Keywords: risk management; ERM; OCTAVE; cloud computing; Microsoft Azure
1. Introduction
Cloud computing is a technology that uses virtualized resources to deliver IT services through the
Internet. It can also be defined as a model that allows network access to a pool of computing resources
such as servers, applications, storage, and services, which can be quickly offered by service providers [1].
One of properties of the cloud is its distributed nature [2]. Data in the cloud environments had become
gradually distributed, moving from a centralized model to a distributed model. That distributed nature
causes cloud computing actors to face problems like loss of data control, difficulties to demonstrate
compliance, and additional legal risks as data migration from one legal jurisdiction to another. An example
is Salesforce.com, which suffered a huge outage, locking more than 900,000 subscribers out of important
resources needed for business trans ...
Future internet articleermoctave a risk management fra
This document introduces a new risk management framework called ERMOCTAVE for assessing risks associated with adopting cloud computing. ERMOCTAVE combines two existing risk management methods - Enterprise Risk Management (ERM) and Operationally Critical Threat, Asset, and Vulnerability Evaluation (OCTAVE) - to provide a more comprehensive approach. The framework distributes ERM components across the three phases of the OCTAVE method. A case study is presented to demonstrate how ERMOCTAVE can be applied to assess risks when migrating systems to the Microsoft Azure cloud.
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59
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
57
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
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The document proposes a dynamic trust computation model called "SecuredTrust" for evaluating trust in multi-agent systems. It aims to address issues with existing trust/reputation models, including their inability to properly evaluate trust of agents with unpredictable malicious behavior or provide quick response to behavioral changes. The model also seeks to distribute workload evenly among service-providing agents. The paper analyzes factors for evaluating agent trust, proposes a quantitative trust measurement model, and a novel load-balancing algorithm based on defined factors. Simulation results show the model can effectively handle strategic changes in malicious agents and efficiently distribute workloads compared to other models.
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Manoj Kumar Sadhu is seeking a position where he can contribute his skills and abilities to grow an organization. He has strong skills in SQL, Java, C, Linux, and Microsoft technologies. He has a Master's degree in Computer Science from Northwestern Polytechnic University with a GPA of 3.2/4.0 and a Bachelor's degree in Computer Science from VEMU Institute of Technology with a GPA of 6.5/10.0. His academic projects include developing an advertising agency website, a board game called Navy Beach, and a health and fitness website called Fit Now.
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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
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The document proposes a dynamic trust computation model called "SecuredTrust" for evaluating trust in multi-agent systems. It aims to address issues with existing models, including their inability to properly evaluate trust of agents with unpredictable malicious behavior or provide quick response to behavioral changes. The model also considers workload distribution among service providing agents. The paper first analyzes factors for evaluating agent trust, then proposes a quantitative trust measurement model and load balancing algorithm based on the defined factors. Simulation results show the model can effectively handle strategic changes in malicious agents' behavior while efficiently distributing workload under stable conditions.
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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
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the intrusion detection processes. We must note that the design of NICE does not intend to improve any of the existing intrusion
detection algorithms; indeed, NICE employs a reconfigurable virtual networking approach to detect and counter the attempts to
compromise VMs, thus preventing zombie VMs. NICE includes two main phases: deploy a lightweight mirroring-based network
intrusion detection agent (NICE-A) on each cloud server to capture and analyze cloud traffic. A NICE-A periodically scans the virtual
system vulnerabilities within a cloud server to establish Scenario Attack Graph (SAGs), and then based on the severity of identified
vulnerability toward the collaborative attack goals, NICE will decide whether or not to put a VM in network inspection state. Once a
VM enters inspection state, Deep Packet Inspection (DPI) is applied, and/or virtual network reconfigurations can be deployed to the
inspecting VM to make the potential attack behaviors prominent.
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This document introduces a new risk management framework called ERMOCTAVE for assessing risks associated with adopting cloud computing. ERMOCTAVE combines two existing risk management methods - Enterprise Risk Management (ERM) and Operationally Critical Threat, Asset, and Vulnerability Evaluation (OCTAVE). It structures the processes of OCTAVE into three phases and maps the components of ERM to each phase to provide a more comprehensive approach. The document then describes ERMOCTAVE in detail and provides a case study example of how it can be applied by a company migrating parts of its system to Microsoft Azure cloud.
Survey on cloud computing security techniques
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
future internetArticleERMOCTAVE A Risk Management Fra
future internet
Article
ERMOCTAVE: A Risk Management Framework for IT
Systems Which Adopt Cloud Computing
Masky Mackita 1, Soo-Young Shin 2 and Tae-Young Choe 3,*
1 ING Bank, B-1040 Brussels, Belgium; [email protected]
2 Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea;
[email protected]
3 Department of Computer Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea
* Correspondence: [email protected]; Tel.: +82-54-478-7526
Received: 22 June 2019; Accepted: 3 September 2019; Published: 10 September 2019
����������
�������
Abstract: Many companies are adapting cloud computing technology because moving to the cloud
has an array of benefits. During decision-making, having processed for adopting cloud computing,
the importance of risk management is progressively recognized. However, traditional risk management
methods cannot be applied directly to cloud computing when data are transmitted and processed by
external providers. When they are directly applied, risk management processes can fail by ignoring
the distributed nature of cloud computing and leaving numerous risks unidentified. In order to fix
this backdrop, this paper introduces a new risk management method, Enterprise Risk Management
for Operationally Critical Threat, Asset, and Vulnerability Evaluation (ERMOCTAVE), which combines
Enterprise Risk Management and Operationally Critical Threat, Asset, and Vulnerability Evaluation for
mitigating risks that can arise with cloud computing. ERMOCTAVE is composed of two risk management
methods by combining each component with another processes for comprehensive perception of risks.
In order to explain ERMOCTAVE in detail, a case study scenario is presented where an Internet seller
migrates some modules to Microsoft Azure cloud. The functionality comparison with ENISA and
Microsoft cloud risk assessment shows that ERMOCTAVE has additional features, such as key objectives
and strategies, critical assets, and risk measurement criteria.
Keywords: risk management; ERM; OCTAVE; cloud computing; Microsoft Azure
1. Introduction
Cloud computing is a technology that uses virtualized resources to deliver IT services through the
Internet. It can also be defined as a model that allows network access to a pool of computing resources
such as servers, applications, storage, and services, which can be quickly offered by service providers [1].
One of properties of the cloud is its distributed nature [2]. Data in the cloud environments had become
gradually distributed, moving from a centralized model to a distributed model. That distributed nature
causes cloud computing actors to face problems like loss of data control, difficulties to demonstrate
compliance, and additional legal risks as data migration from one legal jurisdiction to another. An example
is Salesforce.com, which suffered a huge outage, locking more than 900,000 subscribers out of important
resources needed for business trans ...
Future internet articleermoctave a risk management fra
This document introduces a new risk management framework called ERMOCTAVE for assessing risks associated with adopting cloud computing. ERMOCTAVE combines two existing risk management methods - Enterprise Risk Management (ERM) and Operationally Critical Threat, Asset, and Vulnerability Evaluation (OCTAVE) - to provide a more comprehensive approach. The framework distributes ERM components across the three phases of the OCTAVE method. A case study is presented to demonstrate how ERMOCTAVE can be applied to assess risks when migrating systems to the Microsoft Azure cloud.
Automated Feature Selection and Churn Prediction using Deep Learning Models
This document discusses using deep learning models for churn prediction in the telecommunications industry. It begins with an introduction to churn prediction and feature selection challenges. It then provides an overview of deep learning techniques, including artificial neural networks, convolutional neural networks, and their applications. The document proposes three deep learning architectures for churn prediction and experiments with them on two telecom datasets. The results show deep learning models can achieve performance comparable to traditional models without manual feature engineering.
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Automated Feature Selection and Churn Prediction using Deep Learning Models
Automated Feature Selection and Churn Prediction using Deep Learning Models
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59
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
57
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
56
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
55
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
54
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
53
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
52
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
51
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
49
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
48
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
47
This document presents a spam zombie detection system called SPOT that monitors outgoing messages from a network. SPOT uses a statistical tool called Sequential Probability Ratio Test to detect compromised machines involved in spamming. When evaluated on a two-month email trace from a large campus network, SPOT identified 132 of 440 internal IP addresses as compromised, with 126 being confirmed and 16 likely compromised. SPOT missed only 7 compromised machines and outperformed detection algorithms based on spam message counts.
46
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
45
This document discusses a new mechanism for improving the trustworthiness of a host system and its data by ensuring the correct origin or provenance of critical system information. It defines data provenance integrity as preventing the source of data from being spoofed or tampered with. It then describes a cryptographic provenance verification approach for enforcing this at the kernel level, with two applications - keystroke integrity verification using a Trusted Computing Platform to prevent forged key events, and a lightweight framework for restricting outbound malware traffic to help identify network activities of stealthy malware.
44
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
43
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
42
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
39
This document discusses extending and aggregating attack graph-based security metrics to more accurately assess network security. It proposes a new suite of complimentary metrics to overcome the shortcomings of existing metrics like shortest path, number of paths, and mean path length. Specifically, it suggests an algorithm to combine these metrics to better determine which of two attack graphs corresponds to the most secure network configuration in many cases.
38
The document discusses a solution called Assured Digital Signing (ADS) that aims to enhance the trustworthiness of digital signatures. ADS takes advantage of trusted computing and virtualization technologies to examine not only a signature's cryptographic validity, but also its system security validity by ensuring the private signing key and signing function are secure, even if the signing application and operating system kernel are compromised. The modular design of ADS makes it application-transparent and hypervisor-independent. The document reports on an implementation of ADS using the Xen hypervisor to demonstrate feasibility.
37
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
36
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
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- 1. Impulse Technologies Beacons U to World of technology 044-42133143, 98401 03301,9841091117 ieeeprojects@yahoo.com www.impulse.net.in M-Score: A Misuseability Weight Measure Abstract— Detecting and preventing data leakage and data misuse poses a serious challenge for organizations, especially when dealing with insiders with legitimate permissions to access the organization's systems and its critical data. In this paper, we present a new concept, Misuseability Weight, for estimating the risk emanating from data exposed to insiders. This concept focuses on assigning a score that represents the sensitivity level of the data exposed to the user and by that predicts the ability of the user to maliciously exploit this data. Then, we propose a new measure, the M-score, which assigns a misuseability weight to tabular data, discuss some of its properties, and demonstrate its usefulness in several leakage scenarios. One of the main challenges in applying the M-score measure is in acquiring the required knowledge from a domain expert. Therefore, we present and evaluate two approaches toward eliciting misuseability conceptions from the domain expert. Your Own Ideas or Any project from any company can be Implemented at Better price (All Projects can be done in Java or DotNet whichever the student wants) 1