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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 466
An Efficient Dissemination and Dynamic Risk Management in
Wireless Sensor Network
Ms. Sujatha E1, Pavithra M2, Ramya R3
1,2,3 Department of Computer Science and Engineering, Velammal Institute of Technology, “Velammal Knowledge
Park”, Panchetti, Thiruvallur, Tamilnadu, India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract- A sensor cloud is comprised of several multifarious
wireless sensor networks (WSNs). These WSNs may have
different owners and run a wide variety of userapplicationson
demand in a wireless communication medium and there are
possibilities for various security attacks. Thus, a need arisesto
construct suitable security measures that protect these
applications which got affected from several attacks . Before
deploying any kind of security measures it is essential to
analyze the impact of different attacks and their cause-
consequence relationship. In this proposed method, a risk
assessment framework is developed that enhances the
efficiency and security of the sensorsdeployed.Thisframework
is mainly based on the concept of code dissemination which
propagates a new program image or relevant commands to
sensor nodes through wireless links, after a wireless sensor
network (WSN) have been deployed. The result will be
generated in the form of PDF which provides the user with the
sufficient knowledge about the risk occurred in various
regions. Along with the PDF, solutions are also provided to
overcome the risks identified and the solution act as a caution
which will avoid the cause of risk.
Index Terms- Security; RiskAssessment;WirelessSensor
Networks; Code Dissemination; Denial-of-Service.
Introduction:
Data mining can likewise be connected to different types of
information, for example, information streamsrequestedor
sequenced information, chart, or arranged information,
spatial information, content information, sight and sound,
and WWW [12].
The list items of a client inquiry are regularly returned as
rundown now and again called hits. The hits may comprise
of website pages, pictures, and different sorts of documents
[12]. Assume a web crawler needs to give setting mindful
question suggestions i.e. at the point when a client
represents a question the web crawler tries to gather the
setting of the inquiry utilizing the client's profile and his
inquiry history keeping in mind the end goal to return more
tweaked answers within a fraction of a second.
The Collaborative tagging is a mechanism in which the
resources called web links can be classified into tags based
on the end-users necessity. When the collaborativetaggingis
primarily used to assist tag-based resource discovery and
browsing, it could also be utilized for otherpurposes[5].The
tags possessed by the bookmarking service are used to
intensify the web performances like content filtering and
classification based on the user [2]. However, to achieve this
enhanced use, the current architecture of collaborative
tagging services must be extended by including a policy
layer. The objective of this layer will be to impose user
choices, purposely denoting resourceson the basis of theset
of tagsassociated with them, and, possibly,otherparameters
concerning their trustworthiness (the percentage of users
who have added a given tag, the social relationships, and
characteristics of those users, etc.).
Existing System:
Several code dissemination protocolshavebeen proposedto
propagate new code images in WSNs. Deluge is included in
the TinyOS distributions .However, since the design of
Deluge did not take security into consideration, there have
been several extensions to Deluge to provide security
protection for code dissemination .Among them, Seluge
enjoysboth strong security and high efficiency. However,all
these code dissemination protocols are based on the
centralized approach which assumes the existence of a base
station and only the base station has the authority to
reprogram sensor nodes. Unfortunately, there are WSNs
having no base station at all. For Example a military WSN in
a battlefield to monitor enemy activity a WSN deployed
along an international bordertomonitorweaponssmuggling
or human trafficking, and a WSN situated in a remote areaof
a national park monitoring illegal activities. Having a base
station in these WSNsintroducesa single point offailureand
a very attractive attack target. Also, the centralizedapproach
is inefficient, weakly scalable (i.e., inefficientforsupportinga
large number of sensor nodes and users), and vulnerable to
some potential attacks along the long communication path.
Proposed System:
In this project, we propose a risk assessment framework for
WSNs in a sensor cloud that utilizes database. Using our
proposed risk assessment framework allows the security
administrator to better understand the threats present and
take necessary actions against them.
1. A distributed approach can be employed for code
dissemination in WSNs. It allows multiple authorized
network users to simultaneously and directly update code
imageson different nodeswithout involvingthebasestation.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 467
2. Another advantage of distributed code dissemination is
that different authorized users may be assigned different
privileges of reprogramming sensor nodes. Thisisespecially
important in large scale WSNs owned by an owner and used
by different users from both public and private sectors.
3. Very recently, an identity-based signature scheme to
achieve secure and distributed code dissemination is
proposed. In this project, we further extend this scheme in
three important aspects.
Firstly, we consider denial-of-service (DOS) attacksoncode
dissemination, which have severe consequencesonnetwork
availability, as well as propose and implement two
approaches to defeat DOS attacks.
Secondly, the proposed code dissemination protocol is
based on a secure and efficient Proxy Signature by Warrant
(PSW) technique.
Thirdly, we consider how to avoid reprogramming conflict
and support dynamic participation.
A secure distributed code dissemination protocol should
satisfy the following requirements
1. Integrity of Code Images
2. Freshness
3. DOS Attacks Resistance
4. Node Compromise Tolerance
5. Distributed
6. Supporting Different User Privileges
7. Partial Reprogram Capability
8. Avoiding Reprogramming Conflicts
9. User Traceability
10. Scalability
11. Dynamic Participation
To satisfy the above requirements, we propose in this paper
a practical secure and distributed code dissemination
protocol which is built on the PSW technique.
There are seven attacks performed in this paper namely,
1. Key Mismatch
2. User Exists
3. Registered region
4. Old Version
5. Hash Fail
6. Denial of Service(DOS)
7. Access Over
At last, we take risk assessment of every attacks based on
impact level of each attack in a network.
Fig.1: Architecture Diagram
A. Network Formation & User Registration
A Network is first formed with different regions. Regionsare
splitted based on the Sensor ranges .The Regions are fully
controlled by Network Admin. Keys are shared with the
Sensors in different Region by the Network Admin. User
Requests are processed and Keys are issued for issuing
warrant. Only the public key of the network owner is pre-
loaded on each node before deployment.
Attacks: Registered region
If a user present in network by registering one region, the
same region cannot be registered by any other users.
Fig.2.1: Network Admin Fig.2.2:User Registration
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 468
B. Installing Code Image
Proper registration of user is updated in admin table. Aftera
Network is deployed, Admin should provideissuewarrantto
User for describing the User privileges, that the User is able
to update Code Images. There are three stepsinvolvedinthis
module.
System Initialization
User registers to the Network Admin. After verifyinghis/her
registration information, the network owner assigns an
identity for him. Then the network owner computesa proxy
signature key for user .The warrant mw records, the identity
of the network owner and the user privilege such as the
sensor nodes set with specified identities or/and within a
specific region that user is allowed to reprogram, and valid
periods of delegation.
User Pre-processing
Assume that user enters to the WSN and has a new
program image. User generates the Code Image with the
proxy Key given by Admin. Here the targeted node identities
set field indicates the identities of the sensor nodes which
the user wishes to reprogram. User cannot control the
Regions beyond the warrant description. If hetrieshewillbe
denied by the Warrant of admin .User Checks the
genuineness of warrant with the Pre-Shared public Key of
Admin.
Sensor Node Verification
Upon receiving a signature message each sensor node
verifies it as follows:
The node firstly pays attention to the legality of the warrant
mw and the message m. For example, the node needs to
check whether the identity of itself is included in the node
Identities set of the warrant mw. Also, according to the valid
periods of delegation field of warrant mw, the node can
check whether reprogramming service to a user is expired.
Only if
The above verification passes, the node believes that the
message m and the warrant mw are from an authorizeduser.
Attacks: Key Mismatch, User Exists, Old Version
-Admin asks its public key to every new user entered into a
network, if user reply wrong public key of admin means,
admin removed the user from network.
-For example, if a user named as Ravi present in network,
mock user (Ravi) cannot be register again.
-Code generation is only by using new versions; otherwiseit
will become an attack.
C. Resisting DOS:
The Region Head Checks periodically weather a DOS is
suspected .If found from a User it validates the User by
asking a puzzle periodically before data send. In particular,
the node attaches a unique puzzle into the beacon messages
and requiresthe solutionof the puzzle to be attachedineach
signature message. The node commitsresourcestoprocessa
signature message only when the solution is correct .If the
answer for the puzzle is correct it sends the data. Otherwise
it informs all nodes in the Region about the Attack and
suggests to drop User and not to send data further to the
specified User. Now the DOS Attacker is dropped and the
corresponding region free for other Users.
Attacks: Access Over, DOS
-If a user exceeds warrant, access over attack is performed.
-If an attacker generates code continuously, then DOS is
suspected.
Fig.3: Resisting attacks
D. Predict Impact level of attacks & report to admin
For each and every attacks, weightageandrecoverycost
is calculated. Database contains six fields namely type of
attackers, attacker’s name, type of attack, time of attack,
recovery time of attack and impact level of attacks. The
impact level of attack is updated based on the value of
weightage, recovery cost and recovery time of attacks.Then,
this database is exported to PDF to admin. PDF also contains
description of each attacks performed in network.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 469
Fig.4.1: Predicting attacks
Fig.4.2: Report
Conclusion:
In this project, we have presented a risk assessment
framework for WSNs in a sensor cloud environment. We
depicted the cause-consequence relationship for attacks on
WSNs using database. Thus, we deployed Code Images
securely in distributed manner and had taken risk
assessment of every attacks successfully. The proposed risk
assessment will also be used to determine how efficient a
security measure will be, which can be measured in termsof
resource utilization and the capability to reduce the overall
threat level to WSN security parameters.
Enhancement
 Intimate to admin about the attacks performed in
network periodically, in order to take necessary steps
for preventing these attacks in future.
 Maintain database which includes overall attacks
information with recovery cost rather than plot in
graph.
REFERENCES:
[1] S. Madria, V. Kumar, and R. Dalvi, “Sensor cloud: A cloud
of virtual sensors,” IEEE Software , vol. 99, no. PrePrints,p.1,
2013.
[2] N. Poolsappasit, V. Kumar, S. Madria, and S. Chellappan,
“Challenges in secure sensor-cloud computing,” in
Proceedings of the 8th VLDB international conference on
Secure data manage- ment , ser. SDM’11. Berlin, Heidelberg:
Springer-Verlag, 2011, pp. 70–84.
[3] A. Kapadia, S. Myers, X. Wang, and G. Fox, “Toward
securing sensor clouds,” in Collaboration Technologies and
Systems(CTS), 2011 International Conference on , 2011,pp.
280–289.
[4] K. Pongaliur, C. Wang, and L. Xiao, “Maintaining
functional module integrity in sensor networks.” in MASS .
IEEE, 2005.
[5] E.-H. Ngai, J. Liu, and M. Lyu, “On the intruder detection
for sinkhole attack in wireless sensor networks,” in
Communi- cations, 2006. ICC ’06. IEEE International
Conference on , vol. 8, 2006, pp. 3383–3389.
[6] J. Newsome, E. Shi, D. Song, and A. Perrig, “The sybil
attack in sensor networks: analysisdefenses,”inInformation
Processing in Sensor Networks, 2004. IPSN 2004. Third
International Sympo- sium on , 2004, pp. 259–268.
[7] J. P. Walters, Z. Liang, W. Shi, and V. Chaudhary, “Wireless
sen- sor network security: A survey, in book chapter of
security,” in in Distributed, Grid, and Pervasive Computing,
Yang Xiao (Eds . CRC Press, 2007, pp. 0–849.
[8] I. Ray and N. Poolsapassit, “Using attack trees to identify
malicious attacks from authorized insiders,” in Proceedings
of the 10th European conference on Research in Computer
Security , ser. ESORICS’05. Berlin, Heidelberg: Springer-
Verlag, 2005, pp. 231–246.
[9] N. Poolsappasit, R. Dewri, and I. Ray, “Dynamic security
risk management using bayesian attack graphs,” IEEETrans.
Dependable Secur. Comput. , vol. 9, no. 1, pp. 61–74, Jan.
2012.
[10] A. Terje, “Trends in quantitative risk assessments.

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  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 466 An Efficient Dissemination and Dynamic Risk Management in Wireless Sensor Network Ms. Sujatha E1, Pavithra M2, Ramya R3 1,2,3 Department of Computer Science and Engineering, Velammal Institute of Technology, “Velammal Knowledge Park”, Panchetti, Thiruvallur, Tamilnadu, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract- A sensor cloud is comprised of several multifarious wireless sensor networks (WSNs). These WSNs may have different owners and run a wide variety of userapplicationson demand in a wireless communication medium and there are possibilities for various security attacks. Thus, a need arisesto construct suitable security measures that protect these applications which got affected from several attacks . Before deploying any kind of security measures it is essential to analyze the impact of different attacks and their cause- consequence relationship. In this proposed method, a risk assessment framework is developed that enhances the efficiency and security of the sensorsdeployed.Thisframework is mainly based on the concept of code dissemination which propagates a new program image or relevant commands to sensor nodes through wireless links, after a wireless sensor network (WSN) have been deployed. The result will be generated in the form of PDF which provides the user with the sufficient knowledge about the risk occurred in various regions. Along with the PDF, solutions are also provided to overcome the risks identified and the solution act as a caution which will avoid the cause of risk. Index Terms- Security; RiskAssessment;WirelessSensor Networks; Code Dissemination; Denial-of-Service. Introduction: Data mining can likewise be connected to different types of information, for example, information streamsrequestedor sequenced information, chart, or arranged information, spatial information, content information, sight and sound, and WWW [12]. The list items of a client inquiry are regularly returned as rundown now and again called hits. The hits may comprise of website pages, pictures, and different sorts of documents [12]. Assume a web crawler needs to give setting mindful question suggestions i.e. at the point when a client represents a question the web crawler tries to gather the setting of the inquiry utilizing the client's profile and his inquiry history keeping in mind the end goal to return more tweaked answers within a fraction of a second. The Collaborative tagging is a mechanism in which the resources called web links can be classified into tags based on the end-users necessity. When the collaborativetaggingis primarily used to assist tag-based resource discovery and browsing, it could also be utilized for otherpurposes[5].The tags possessed by the bookmarking service are used to intensify the web performances like content filtering and classification based on the user [2]. However, to achieve this enhanced use, the current architecture of collaborative tagging services must be extended by including a policy layer. The objective of this layer will be to impose user choices, purposely denoting resourceson the basis of theset of tagsassociated with them, and, possibly,otherparameters concerning their trustworthiness (the percentage of users who have added a given tag, the social relationships, and characteristics of those users, etc.). Existing System: Several code dissemination protocolshavebeen proposedto propagate new code images in WSNs. Deluge is included in the TinyOS distributions .However, since the design of Deluge did not take security into consideration, there have been several extensions to Deluge to provide security protection for code dissemination .Among them, Seluge enjoysboth strong security and high efficiency. However,all these code dissemination protocols are based on the centralized approach which assumes the existence of a base station and only the base station has the authority to reprogram sensor nodes. Unfortunately, there are WSNs having no base station at all. For Example a military WSN in a battlefield to monitor enemy activity a WSN deployed along an international bordertomonitorweaponssmuggling or human trafficking, and a WSN situated in a remote areaof a national park monitoring illegal activities. Having a base station in these WSNsintroducesa single point offailureand a very attractive attack target. Also, the centralizedapproach is inefficient, weakly scalable (i.e., inefficientforsupportinga large number of sensor nodes and users), and vulnerable to some potential attacks along the long communication path. Proposed System: In this project, we propose a risk assessment framework for WSNs in a sensor cloud that utilizes database. Using our proposed risk assessment framework allows the security administrator to better understand the threats present and take necessary actions against them. 1. A distributed approach can be employed for code dissemination in WSNs. It allows multiple authorized network users to simultaneously and directly update code imageson different nodeswithout involvingthebasestation.
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 467 2. Another advantage of distributed code dissemination is that different authorized users may be assigned different privileges of reprogramming sensor nodes. Thisisespecially important in large scale WSNs owned by an owner and used by different users from both public and private sectors. 3. Very recently, an identity-based signature scheme to achieve secure and distributed code dissemination is proposed. In this project, we further extend this scheme in three important aspects. Firstly, we consider denial-of-service (DOS) attacksoncode dissemination, which have severe consequencesonnetwork availability, as well as propose and implement two approaches to defeat DOS attacks. Secondly, the proposed code dissemination protocol is based on a secure and efficient Proxy Signature by Warrant (PSW) technique. Thirdly, we consider how to avoid reprogramming conflict and support dynamic participation. A secure distributed code dissemination protocol should satisfy the following requirements 1. Integrity of Code Images 2. Freshness 3. DOS Attacks Resistance 4. Node Compromise Tolerance 5. Distributed 6. Supporting Different User Privileges 7. Partial Reprogram Capability 8. Avoiding Reprogramming Conflicts 9. User Traceability 10. Scalability 11. Dynamic Participation To satisfy the above requirements, we propose in this paper a practical secure and distributed code dissemination protocol which is built on the PSW technique. There are seven attacks performed in this paper namely, 1. Key Mismatch 2. User Exists 3. Registered region 4. Old Version 5. Hash Fail 6. Denial of Service(DOS) 7. Access Over At last, we take risk assessment of every attacks based on impact level of each attack in a network. Fig.1: Architecture Diagram A. Network Formation & User Registration A Network is first formed with different regions. Regionsare splitted based on the Sensor ranges .The Regions are fully controlled by Network Admin. Keys are shared with the Sensors in different Region by the Network Admin. User Requests are processed and Keys are issued for issuing warrant. Only the public key of the network owner is pre- loaded on each node before deployment. Attacks: Registered region If a user present in network by registering one region, the same region cannot be registered by any other users. Fig.2.1: Network Admin Fig.2.2:User Registration
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 468 B. Installing Code Image Proper registration of user is updated in admin table. Aftera Network is deployed, Admin should provideissuewarrantto User for describing the User privileges, that the User is able to update Code Images. There are three stepsinvolvedinthis module. System Initialization User registers to the Network Admin. After verifyinghis/her registration information, the network owner assigns an identity for him. Then the network owner computesa proxy signature key for user .The warrant mw records, the identity of the network owner and the user privilege such as the sensor nodes set with specified identities or/and within a specific region that user is allowed to reprogram, and valid periods of delegation. User Pre-processing Assume that user enters to the WSN and has a new program image. User generates the Code Image with the proxy Key given by Admin. Here the targeted node identities set field indicates the identities of the sensor nodes which the user wishes to reprogram. User cannot control the Regions beyond the warrant description. If hetrieshewillbe denied by the Warrant of admin .User Checks the genuineness of warrant with the Pre-Shared public Key of Admin. Sensor Node Verification Upon receiving a signature message each sensor node verifies it as follows: The node firstly pays attention to the legality of the warrant mw and the message m. For example, the node needs to check whether the identity of itself is included in the node Identities set of the warrant mw. Also, according to the valid periods of delegation field of warrant mw, the node can check whether reprogramming service to a user is expired. Only if The above verification passes, the node believes that the message m and the warrant mw are from an authorizeduser. Attacks: Key Mismatch, User Exists, Old Version -Admin asks its public key to every new user entered into a network, if user reply wrong public key of admin means, admin removed the user from network. -For example, if a user named as Ravi present in network, mock user (Ravi) cannot be register again. -Code generation is only by using new versions; otherwiseit will become an attack. C. Resisting DOS: The Region Head Checks periodically weather a DOS is suspected .If found from a User it validates the User by asking a puzzle periodically before data send. In particular, the node attaches a unique puzzle into the beacon messages and requiresthe solutionof the puzzle to be attachedineach signature message. The node commitsresourcestoprocessa signature message only when the solution is correct .If the answer for the puzzle is correct it sends the data. Otherwise it informs all nodes in the Region about the Attack and suggests to drop User and not to send data further to the specified User. Now the DOS Attacker is dropped and the corresponding region free for other Users. Attacks: Access Over, DOS -If a user exceeds warrant, access over attack is performed. -If an attacker generates code continuously, then DOS is suspected. Fig.3: Resisting attacks D. Predict Impact level of attacks & report to admin For each and every attacks, weightageandrecoverycost is calculated. Database contains six fields namely type of attackers, attacker’s name, type of attack, time of attack, recovery time of attack and impact level of attacks. The impact level of attack is updated based on the value of weightage, recovery cost and recovery time of attacks.Then, this database is exported to PDF to admin. PDF also contains description of each attacks performed in network.
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 469 Fig.4.1: Predicting attacks Fig.4.2: Report Conclusion: In this project, we have presented a risk assessment framework for WSNs in a sensor cloud environment. We depicted the cause-consequence relationship for attacks on WSNs using database. Thus, we deployed Code Images securely in distributed manner and had taken risk assessment of every attacks successfully. The proposed risk assessment will also be used to determine how efficient a security measure will be, which can be measured in termsof resource utilization and the capability to reduce the overall threat level to WSN security parameters. Enhancement  Intimate to admin about the attacks performed in network periodically, in order to take necessary steps for preventing these attacks in future.  Maintain database which includes overall attacks information with recovery cost rather than plot in graph. REFERENCES: [1] S. Madria, V. Kumar, and R. Dalvi, “Sensor cloud: A cloud of virtual sensors,” IEEE Software , vol. 99, no. PrePrints,p.1, 2013. [2] N. Poolsappasit, V. Kumar, S. Madria, and S. Chellappan, “Challenges in secure sensor-cloud computing,” in Proceedings of the 8th VLDB international conference on Secure data manage- ment , ser. SDM’11. Berlin, Heidelberg: Springer-Verlag, 2011, pp. 70–84. [3] A. Kapadia, S. Myers, X. Wang, and G. Fox, “Toward securing sensor clouds,” in Collaboration Technologies and Systems(CTS), 2011 International Conference on , 2011,pp. 280–289. [4] K. Pongaliur, C. Wang, and L. Xiao, “Maintaining functional module integrity in sensor networks.” in MASS . IEEE, 2005. [5] E.-H. Ngai, J. Liu, and M. Lyu, “On the intruder detection for sinkhole attack in wireless sensor networks,” in Communi- cations, 2006. ICC ’06. IEEE International Conference on , vol. 8, 2006, pp. 3383–3389. [6] J. Newsome, E. Shi, D. Song, and A. Perrig, “The sybil attack in sensor networks: analysisdefenses,”inInformation Processing in Sensor Networks, 2004. IPSN 2004. Third International Sympo- sium on , 2004, pp. 259–268. [7] J. P. Walters, Z. Liang, W. Shi, and V. Chaudhary, “Wireless sen- sor network security: A survey, in book chapter of security,” in in Distributed, Grid, and Pervasive Computing, Yang Xiao (Eds . CRC Press, 2007, pp. 0–849. [8] I. Ray and N. Poolsapassit, “Using attack trees to identify malicious attacks from authorized insiders,” in Proceedings of the 10th European conference on Research in Computer Security , ser. ESORICS’05. Berlin, Heidelberg: Springer- Verlag, 2005, pp. 231–246. [9] N. Poolsappasit, R. Dewri, and I. Ray, “Dynamic security risk management using bayesian attack graphs,” IEEETrans. Dependable Secur. Comput. , vol. 9, no. 1, pp. 61–74, Jan. 2012. [10] A. Terje, “Trends in quantitative risk assessments.