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Towards Effective Trust-based
Packet Filtering in Collaborative
Network Analysis
SUMMARY / CONTENT
Motivation
01
Limitation
02
Solution
03
Methodology
04
Advantages
05
Disadvantages
06
Abstract
07
ABSTRACT
 The smart terminal and grid protection devices play a very important role in the
safe operation of the smart grid.
 Traditional maintenance and renewal of the center node wastes a lot of manpower
and material resources and have huge safety implications.
 This system proposes a safety equipment diagnosis mechanism based on
consortium technology to realize more efficient, convenient and secure device
maintenance.
 This scheme designs a decentralized safety equipment diagnosis smart contract,
combining response node bid price and credit, and applies a multi-dimensional
reverse auction mechanism to determine bid node and transaction price.
INTRODUCTION
 This scheme designs a decentralized safety equipment diagnosis smart contract,
combining response node bid price and credit, and applies a multi-dimensional
reverse auction mechanism to determine bid node and transaction price.
 After a smart device diagnosed, the relevant message will be packaged and sent to a
smartphone, which can use the client to set up the smart contract of equipment
operation policy.
 Paillier encryption arithmetic can be used to ensure device diagnosis mechanism
safety.
 The proposed scheme is guaranteed not to reveal sensitive information in the process
of device interaction.
PROBLEM DEFINIONAT
 Here we are using an open source database forensic technique for multiple
databases thereby showing the scalability of techniques.
 Along with recovery of data and generating exact copy of metadata. Database
forensics helps in identifying and preventing cybercrimes, equipment diagnosis on
internet.
 In case of live analysis, fraud monetary transactions can be detected and blocked.
 In case, the database data is deleted by the criminal, it can be recovered with the
help of metadata.
MOTIVATION
 Nowadays user is comfortable for shopping online so he/she choose to shop
from ecommerce websites , but sometimes after purchasing the product due to
some system failures or device failures user will get different prices of
product on their bill.
 User is totally unknown of it so to aware the user about it we going
implement the system which will beneficial for user to use.
LIMITATION
 System Requirements.
 Internet Connection Required.
APPLICATION
 Log Mining
 Database Trace Identification through Logs.
 Third Party Data security.
 Forensic Analysis (who ,when, what)
 Restoring intruded data with original.
PROPOSED SYSTEM
 To implement a system for automatic identification & detection of theft as well as
malicious activity of the users data.
 To implement an open source database forensic technique for multiple databases
thereby showing the scalability of tools. Along with recovery of data and generating
exact copy of metadata.
 Database forensics helps in identifying and preventing cybercrimes on internet.
 In case of live analysis, fraud monetary transactions can be detected and blocked.
 In case, the database data is deleted by the criminal, it can be recovered with the
help of metadata.
SYSTEM ARCHITECTURE
Literature Survey
Sr.
No.
Paper name Author /Publication Description
01 A survey of
communication/networking in
Smart Grids
Jingcheng Gaoa, Yang Xiao(2012) Current situation is that most of the blackouts and
voltage sags could be prevented if we have better
and faster communication devices and technologies
for the electrical
grid.
02 Blockchains and Smart
Contracts for
the Internet of Things
K. Christidis
(2016)
Blockchains allow us to have a distributedpeer-to-
peer network where non-trusting members can
interact with each other without a trusted
intermediary, in a veriable manner.
03 Pattern Recognition Letters
journal homepage:
www.elsevier.com
Guojun Gana,, Michael Kwok-Po
Ngb(2016)
As an unsupervised learning process, data clustering
is often used as a preliminary step for data analytics.
For example, data clustering is used to identify
REFRANCES
[1] J.-J. Gao et al., “A survey of communication/networking in smart grids,” Future Comp Sy.,
vol. 28, no. 2, pp. 391–404, Feb. 2012.
[2] G. W. Arnold, “Challenges and opportunities in smart grid: A position article,” P IEEE., vol.
99, no. 6, pp. 922–927, Jun. 2011.
[3] W.-X. Meng, R.-F. Ma, and H.-H. Chen, “Smart grid neighborhood area networks: a survey,”
IEEE Network., vol. 28, no. 1, pp. 24–32, Jan. 2014.
[4] A. Jamshidi et al., “A comprehensive fuzzy risk-based maintenance framework for
prioritization of medical devices,” Appl Soft Comput., vol. 32, PP. 322–334, Jul. 2015.
[5] G.-Q. Ji et al., “A time-varying component outage model for power system condition-based
maintenance,” Proc CSEE., vol. 33, no. 25, PP. 139–146, Sep. 2013.
v
THANK YOU

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Trust Based Packet Filtering.pptx

  • 1. Towards Effective Trust-based Packet Filtering in Collaborative Network Analysis
  • 3. ABSTRACT  The smart terminal and grid protection devices play a very important role in the safe operation of the smart grid.  Traditional maintenance and renewal of the center node wastes a lot of manpower and material resources and have huge safety implications.  This system proposes a safety equipment diagnosis mechanism based on consortium technology to realize more efficient, convenient and secure device maintenance.  This scheme designs a decentralized safety equipment diagnosis smart contract, combining response node bid price and credit, and applies a multi-dimensional reverse auction mechanism to determine bid node and transaction price.
  • 4. INTRODUCTION  This scheme designs a decentralized safety equipment diagnosis smart contract, combining response node bid price and credit, and applies a multi-dimensional reverse auction mechanism to determine bid node and transaction price.  After a smart device diagnosed, the relevant message will be packaged and sent to a smartphone, which can use the client to set up the smart contract of equipment operation policy.  Paillier encryption arithmetic can be used to ensure device diagnosis mechanism safety.  The proposed scheme is guaranteed not to reveal sensitive information in the process of device interaction.
  • 5. PROBLEM DEFINIONAT  Here we are using an open source database forensic technique for multiple databases thereby showing the scalability of techniques.  Along with recovery of data and generating exact copy of metadata. Database forensics helps in identifying and preventing cybercrimes, equipment diagnosis on internet.  In case of live analysis, fraud monetary transactions can be detected and blocked.  In case, the database data is deleted by the criminal, it can be recovered with the help of metadata.
  • 6. MOTIVATION  Nowadays user is comfortable for shopping online so he/she choose to shop from ecommerce websites , but sometimes after purchasing the product due to some system failures or device failures user will get different prices of product on their bill.  User is totally unknown of it so to aware the user about it we going implement the system which will beneficial for user to use.
  • 7. LIMITATION  System Requirements.  Internet Connection Required.
  • 8. APPLICATION  Log Mining  Database Trace Identification through Logs.  Third Party Data security.  Forensic Analysis (who ,when, what)  Restoring intruded data with original.
  • 9. PROPOSED SYSTEM  To implement a system for automatic identification & detection of theft as well as malicious activity of the users data.  To implement an open source database forensic technique for multiple databases thereby showing the scalability of tools. Along with recovery of data and generating exact copy of metadata.  Database forensics helps in identifying and preventing cybercrimes on internet.  In case of live analysis, fraud monetary transactions can be detected and blocked.  In case, the database data is deleted by the criminal, it can be recovered with the help of metadata.
  • 11. Literature Survey Sr. No. Paper name Author /Publication Description 01 A survey of communication/networking in Smart Grids Jingcheng Gaoa, Yang Xiao(2012) Current situation is that most of the blackouts and voltage sags could be prevented if we have better and faster communication devices and technologies for the electrical grid. 02 Blockchains and Smart Contracts for the Internet of Things K. Christidis (2016) Blockchains allow us to have a distributedpeer-to- peer network where non-trusting members can interact with each other without a trusted intermediary, in a veriable manner. 03 Pattern Recognition Letters journal homepage: www.elsevier.com Guojun Gana,, Michael Kwok-Po Ngb(2016) As an unsupervised learning process, data clustering is often used as a preliminary step for data analytics. For example, data clustering is used to identify
  • 12. REFRANCES [1] J.-J. Gao et al., “A survey of communication/networking in smart grids,” Future Comp Sy., vol. 28, no. 2, pp. 391–404, Feb. 2012. [2] G. W. Arnold, “Challenges and opportunities in smart grid: A position article,” P IEEE., vol. 99, no. 6, pp. 922–927, Jun. 2011. [3] W.-X. Meng, R.-F. Ma, and H.-H. Chen, “Smart grid neighborhood area networks: a survey,” IEEE Network., vol. 28, no. 1, pp. 24–32, Jan. 2014. [4] A. Jamshidi et al., “A comprehensive fuzzy risk-based maintenance framework for prioritization of medical devices,” Appl Soft Comput., vol. 32, PP. 322–334, Jul. 2015. [5] G.-Q. Ji et al., “A time-varying component outage model for power system condition-based maintenance,” Proc CSEE., vol. 33, no. 25, PP. 139–146, Sep. 2013.