A wireless sensor network is composed of a base station (BS) and numerous sensor nodes. The sensor
nodes lack security because they operate in an open environment, such as the military. In particular, a false
report injection attack captures and compromises sensor nodes. The attack then causes the compromised
nodes to generate forward false reports. Owing to the false report injection attack, not only does the sensor
network have a false alarm, but its limited energy is also drained. In order to defend the false report
injection attack, over the past few years, several studies have been made looking for a solution to the
attack. Ye et al. studied statistical en-route filtering (SEF). SEF is a method of stochastically verifying event
reports in the en-route filtering phase. SEF can filter many false reports early using verification of
intermediate nodes. However, because the number of keys in a sensor node is fixed by the system, the
sensor network cannot control the event report verification probability depending on the circumstances of
the network. Therefore, it is difficult to efficiently consume energy of the sensor network. In order to solve
the problem, we propose a method which controls the event report verification probability by using a key
sequence level of an event report. In the proposed method, when an intermediate node receives an event
report, the node verifies the event report by comparing a key sequence level of the report and its key
sequence level. Elements determining the key sequence level include the density of neighbour nodes in the
sensing range of a center of stimulus (CoS), the number of hops from the CoS to the BS, and the average of
the key sequence level of intermediate nodes in each path. We simulated the proposed method and the SEF
method to evaluate the performance in terms of energy efficiency and security. In the simulation results, the
proposed method consumed an average of 7.9% less energy of the sensor nodes compared to SEF method.
The number of false reports arriving at the BS of the proposed method was also less, by an average of 6.4,
compared to the SEF method. Through the results, we can see that when the number of false report is large
in the sensor network, the proposed method is more energy-efficient and secure than the SEF method.
LOAD BALANCING MANAGEMENT USING FUZZY LOGIC TO IMPROVE THE REPORT TRANSFER SU...cscpconf
A wireless sensor network (WSN) consists of multiple sensor nodes and base stations (BS) that
collect information over widely deployed sensor nodes. Sensor nodes have limited energy source
and low computing power. Due to those features, there is a disadvantage that user's individual
node management is difficult and they are easily captured by attackers. Therefore, efficient
energy allocation of nodes is important and network security protocol is needed. The
Probabilistic Voting Filtering System (PVFS) is a system that prevents false vote injection
attack and false report attack injected from attackers. The reason for the existence of this
protocol is for energy management of nodes through defence against those attacks and in order
to efficiently manage the network based on PVFS, load balancing of nodes should be performed.
In the proposed scheme, fuzzy logic is applied to each cluster head node (CH) to perform load
balancing by determine whether to perform a role as a verification node and an event
forwarding node. The experiment shows that the event detection rate and the report delivery
success rate are improved in proposed scheme compare with original PVFS.
A SECURITY PERIOD UPDATE METHOD USING EVALUATION FUNCTION FOR IMPROVING ENERG...csandit
In recent years, Wireless Sensor Networks(WSNs) research has been carried out with the goals
of achieving high security and energy efficiency. In a WSN, sensor nodes are vulnerable to
physical attacks because they are deployed in an open environment. An attacker can inject a
false report into networks using these vulnerabilities. F. Ye et al. proposed statistical en-route
filtering to prevent false report injection attacks. In order to effectively use their scheme,
techniques for determining thresholds using fuzzy logic have been studied. To effectively apply
these techniques to the network, an appropriate update period should be set according to the
network environments. In this paper, we propose a security period update method in order to
improve the lifetime of the network in the statistical en-route filtering approach based on a
wireless sensor network of the cluster environment. The experimental results show that up to an
11.96% improvement of the energy efficiency can be achieved when the security threshold is set
to the optimal period.
A KEY LEVEL SELECTION WITHIN HASH CHAINS FOR THE EFFICIENT ENERGY CONSUMPTION...IAEME Publication
A wireless sensor network is comprised of a base station (BS) and numerous sensor nodes. The sensor nodes lack security because they function in an open environment, such as the military. In particular, a false statement injection attack seizures and compromises sensor nodes. The attack then causes the compromised nodes to create forward false reports. Due to the false report injection attack, not only does the sensor network have a false alarm, but its limited energy is also emptied. In order to preserve the false report injection attack, over the past few years, several studies have been made looking for a resolution to the attack. Ye et al. studied statistical en-route filtering (SEF). SEF is a method of randomly verifying event reports in the en-route filtering phase. SEF can filter many false reports early using proof of intermediate nodes. However, because the number of keys in a sensor node is fixed by the system, the sensor network cannot control the event report proof probability depending on the conditions of the network. Therefore, it is tough to proficiently consume energy of the sensor network. In order to resolve the problem, we suggest a technique which controls the event report verification probability by using a key sequence level of an event report. In the suggested method, when an intermediate node obtains an event report, the node authenticates the event report by relating a key sequence level of the report and its key
Ensp energy efficient next hop selection in a probabilistic voting based filt...ieijjournal
In wireless sensor networks, sensor nodes are easily compromised due to their restricted hardware resources. These compromised nodes inject fabricated votes into legitimate reports, and generate false report and false vote injection attacks. These attacks deplete energy resources and block report transmission. A probabilistic voting-based filtering scheme was proposed to detect the bogus votes in reports en-route to protect against attacks. Although this method detects false votes in intermediate nodes, the sensor network needs to be effectively operated in consideration of a node's conditions. In this paper, the proposed method selects effective verification nodes by considering the condition of nodes based on a fuzzy logic system. In the proposed method, the intermediate node selects between two next hop nodes in its range through a fuzzy logic system before forwarding the report. Experimental results suggest that, compared to the original method, the proposed method improves energy savings up to 11% while maintaining a high security level.
ENSP: ENERGY EFFICIENT NEXT HOP SELECTION IN A PROBABILISTIC VOTING-BASED FIL...ieijjournal
In wireless sensor networks, sensor nodes are easily compromised due to their restricted hardware resources. These compromised nodes inject fabricated votes into legitimate reports, and generate false report and false vote injection attacks. These attacks deplete energy resources and block report transmission. A probabilistic voting-based filtering scheme was proposed to detect the bogus votes in reports en-route to protect against attacks. Although this method detects false votes in intermediate nodes, the sensor network needs to be effectively operated in consideration of a node's conditions. In this paper, the proposed method selects effective verification nodes by considering the condition of nodes based on a fuzzy logic system. In the proposed method, the intermediate node selects between two next hop nodes in its range through a fuzzy logic system before forwarding the report. Experimental results
suggest that, compared to the original method, the proposed method improves energy savings up to 11% while maintaining a high security level.
WSN LIFETIME EXTENSION USING GA OPTIMISED FUZZY LOGICijcsit
A wireless sensor network (WSN) consists of multiple sensor nodes and base stations that collect information from widely deployed sensors. However, the disadvantage is that WSNs are randomly distributed in an open environment, which makes them difficult to manage individually and more easily found and compromised by an attacker. An attacker can execute a false report insertion or invalid vote insertion attack through a compromised node. The Probabilistic Voting Filtering System (PVFS) is a system that prevents these two types of attacks. Before sending a report, the proposed method probabilistically selects a validation node, determines the validity of the report, and filters the report based on the thresholds that have been set. In this paper, the proposed scheme improves the lifetime, detection rate, and report delivery rate of the entire network by increasing the lifetime of the cluster head (CH) by selecting the numbers of message authentication codes (MACs) and verification nodes of the report. Using this system, the event detection rate and the network lifetime are improved by up to 18% and 6%, respectively, relative to the existing PVFS.
LOAD BALANCING MANAGEMENT USING FUZZY LOGIC TO IMPROVE THE REPORT TRANSFER SU...cscpconf
A wireless sensor network (WSN) consists of multiple sensor nodes and base stations (BS) that
collect information over widely deployed sensor nodes. Sensor nodes have limited energy source
and low computing power. Due to those features, there is a disadvantage that user's individual
node management is difficult and they are easily captured by attackers. Therefore, efficient
energy allocation of nodes is important and network security protocol is needed. The
Probabilistic Voting Filtering System (PVFS) is a system that prevents false vote injection
attack and false report attack injected from attackers. The reason for the existence of this
protocol is for energy management of nodes through defence against those attacks and in order
to efficiently manage the network based on PVFS, load balancing of nodes should be performed.
In the proposed scheme, fuzzy logic is applied to each cluster head node (CH) to perform load
balancing by determine whether to perform a role as a verification node and an event
forwarding node. The experiment shows that the event detection rate and the report delivery
success rate are improved in proposed scheme compare with original PVFS.
A SECURITY PERIOD UPDATE METHOD USING EVALUATION FUNCTION FOR IMPROVING ENERG...csandit
In recent years, Wireless Sensor Networks(WSNs) research has been carried out with the goals
of achieving high security and energy efficiency. In a WSN, sensor nodes are vulnerable to
physical attacks because they are deployed in an open environment. An attacker can inject a
false report into networks using these vulnerabilities. F. Ye et al. proposed statistical en-route
filtering to prevent false report injection attacks. In order to effectively use their scheme,
techniques for determining thresholds using fuzzy logic have been studied. To effectively apply
these techniques to the network, an appropriate update period should be set according to the
network environments. In this paper, we propose a security period update method in order to
improve the lifetime of the network in the statistical en-route filtering approach based on a
wireless sensor network of the cluster environment. The experimental results show that up to an
11.96% improvement of the energy efficiency can be achieved when the security threshold is set
to the optimal period.
A KEY LEVEL SELECTION WITHIN HASH CHAINS FOR THE EFFICIENT ENERGY CONSUMPTION...IAEME Publication
A wireless sensor network is comprised of a base station (BS) and numerous sensor nodes. The sensor nodes lack security because they function in an open environment, such as the military. In particular, a false statement injection attack seizures and compromises sensor nodes. The attack then causes the compromised nodes to create forward false reports. Due to the false report injection attack, not only does the sensor network have a false alarm, but its limited energy is also emptied. In order to preserve the false report injection attack, over the past few years, several studies have been made looking for a resolution to the attack. Ye et al. studied statistical en-route filtering (SEF). SEF is a method of randomly verifying event reports in the en-route filtering phase. SEF can filter many false reports early using proof of intermediate nodes. However, because the number of keys in a sensor node is fixed by the system, the sensor network cannot control the event report proof probability depending on the conditions of the network. Therefore, it is tough to proficiently consume energy of the sensor network. In order to resolve the problem, we suggest a technique which controls the event report verification probability by using a key sequence level of an event report. In the suggested method, when an intermediate node obtains an event report, the node authenticates the event report by relating a key sequence level of the report and its key
Ensp energy efficient next hop selection in a probabilistic voting based filt...ieijjournal
In wireless sensor networks, sensor nodes are easily compromised due to their restricted hardware resources. These compromised nodes inject fabricated votes into legitimate reports, and generate false report and false vote injection attacks. These attacks deplete energy resources and block report transmission. A probabilistic voting-based filtering scheme was proposed to detect the bogus votes in reports en-route to protect against attacks. Although this method detects false votes in intermediate nodes, the sensor network needs to be effectively operated in consideration of a node's conditions. In this paper, the proposed method selects effective verification nodes by considering the condition of nodes based on a fuzzy logic system. In the proposed method, the intermediate node selects between two next hop nodes in its range through a fuzzy logic system before forwarding the report. Experimental results suggest that, compared to the original method, the proposed method improves energy savings up to 11% while maintaining a high security level.
ENSP: ENERGY EFFICIENT NEXT HOP SELECTION IN A PROBABILISTIC VOTING-BASED FIL...ieijjournal
In wireless sensor networks, sensor nodes are easily compromised due to their restricted hardware resources. These compromised nodes inject fabricated votes into legitimate reports, and generate false report and false vote injection attacks. These attacks deplete energy resources and block report transmission. A probabilistic voting-based filtering scheme was proposed to detect the bogus votes in reports en-route to protect against attacks. Although this method detects false votes in intermediate nodes, the sensor network needs to be effectively operated in consideration of a node's conditions. In this paper, the proposed method selects effective verification nodes by considering the condition of nodes based on a fuzzy logic system. In the proposed method, the intermediate node selects between two next hop nodes in its range through a fuzzy logic system before forwarding the report. Experimental results
suggest that, compared to the original method, the proposed method improves energy savings up to 11% while maintaining a high security level.
WSN LIFETIME EXTENSION USING GA OPTIMISED FUZZY LOGICijcsit
A wireless sensor network (WSN) consists of multiple sensor nodes and base stations that collect information from widely deployed sensors. However, the disadvantage is that WSNs are randomly distributed in an open environment, which makes them difficult to manage individually and more easily found and compromised by an attacker. An attacker can execute a false report insertion or invalid vote insertion attack through a compromised node. The Probabilistic Voting Filtering System (PVFS) is a system that prevents these two types of attacks. Before sending a report, the proposed method probabilistically selects a validation node, determines the validity of the report, and filters the report based on the thresholds that have been set. In this paper, the proposed scheme improves the lifetime, detection rate, and report delivery rate of the entire network by increasing the lifetime of the cluster head (CH) by selecting the numbers of message authentication codes (MACs) and verification nodes of the report. Using this system, the event detection rate and the network lifetime are improved by up to 18% and 6%, respectively, relative to the existing PVFS.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Wireless sensor networks provide ubiquitous computing systems in various open environments. In the
environment, sensor nodes can easily be compromised by adversaries to generate injecting false data
attacks. The injecting false data attack not only consumes unnecessary energy in en-route nodes, but also
causes false alarms at the base station. To detect this type of attack, a bandwidth-efficient cooperative
authentication (BECAN) scheme was proposed to achieve high filtering probability and high reliability
based on random graph characteristics and cooperative bit-compressed authentication techniques. This
scheme may waste energy resources in en-route nodes due to the fixed number of forwarding reports. In
this paper, our proposed method effectively selects a dynamic number of forwarding reports in the source
nodes based on an evaluation function. The experimental results indicate that our proposed method
enhances the energy savings while maintaining security levels as compared to BECAN.
AN EVALUATION OF ENERGY EFFICIENT SOURCE AUTHENTICATION METHODS FOR FALSE DA...ijsptm
The false data injection attack is a major security threat in Wireless Sensor Network (WSN) since is
degrades the network capability. The bandwidth efficient cooperative authentication (BECAN) scheme is
used for filtering the false data injection attack. It is used to save energy of sensor nodes in WSN by early
detection and filtering of maximum possible injected false data. Source authentication is a critical security
requirement in wireless sensor networks to identify attacker nodes that injects false data. Solutions based
on Elliptic Curve Cryptography (ECC) have been used for source authentication, but they suffer from
severe energy depletion. This results in high computational and communication overheads. Bloom filter
based Symmetric-key source authentication scheme exhibits low authentication overhead .This avoids the
inherent problems associated with public key cryptography based schemes. The current work demonstrates
the efficiency of bloom filter based source authentication using BECAN scheme by comparing ECC and
Bloom filter based methods in terms of energy consumption
Detection of PUE Attack by SPARS Model using WSPRTEditor IJCATR
Cognitive radio is a system which improves the utilization of the spectrum by sensing the white spaces in its vicinity. This
sensed information will be utilized by the Secondary User (SU) to transmit the data. But some of the malicious users attacks th
system by generating the signal same as that of the primary transmitter. The attack caused by generating the signal same as t
primary transmitter is called as Primary User Emulation Attack (PUEA). In this paper the Signal Activity Pattern Acquisition
Reconstruction System (SPARS) is used to detect the attack. But this system suffers from low True Positive Rate. To incr
positive rate or sensitivity a new technique was proposed called as Weighted Sequential Probability Ratio Test (WSPRT). By
improving the true positive rate or sensitivity, the detection capability of the system will be improved.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Limiting Self-Propagating Malware Based on Connection Failure Behavior csandit
Self-propagating malware (e.g., an Internet worm) exploits security loopholes in software to
infect servers and then use them to scan the Internet for more vulnerable servers. While the
mechanisms of worm infection and their propagation models are well understood, defense
against worms remains an open problem. One branch of defense research investigates the
behavioral difference between worm-infected hosts and normal hosts to set them apart. One
particular observation is that a worm-infected host, which scans the Internet with randomly
selected addresses, has a much higher connection-failure rate than a normal host. Rate-limit
algorithms have been proposed to control the spread of worms by traffic shaping based on
connection failure rate. However, these rate-limit algorithms can work properly only if it is
possible to measure failure rates of individual hosts efficiently and accurately. This paper points
out a serious problem in the prior method and proposes a new solution based on a highly
efficient double-bitmap data structure, which places only a small memory footprint on the
routers, while providing good measurement of connection failure rates whose accuracy can be
tuned by system parameters.
AN ENERGY EFFICIENT COUNTERMEASURE AGAINST MULTIPLE ATTACKS OF THE FALSE DATA...ijcsity
Nodes are easily exposed from generated attacks on various layers because they compose simple functions in sensor networks. The false data injection attack drains finite energy resource in a compromised node,and the false HELLO flood attack threatens constructed routing paths in an adversary node. A localized encryption and authentication protocol (LEAP) was developed to prevent the aforementioned attacks through the use of four keys. However, when these attacks occur simultaneously, LEAP may not prevent damage from spreading rapidly throughout the network. In this paper, we propose a method that addresses these attacks through the use of four types of keys, including two new keys. We also improve energy consumption while maintaining a suitable security level. The effectiveness of the proposed method was evaluated relative to that of LEAP when multiple attacks occur. The experimental results reveal that the proposed method enhances energy saving by up to 12% while maintaining sufficient detection power
Improving performance of routing protocols using mrp frameworkijasa
These days MANET (Mobile Ad-hoc Network) is an amazing remarkably altering or rising technology, for
the reason that of its elite nature of scattered mobile devices and self-motivated network topology. The
mobile ad-hoc routing protocol follows several principles in wireless MANET’s. The up to date and novel
applications based on wireless technology are being produced in the private as well as commercial sectors.
A lot of challenges which are facing wireless MANETs like network stability, security, energy efficiency
and performance analysis etc. At present wireless ad-hoc network get much more attention because of its
accessibility everywhere. As a result researchers produce several routing protocols. In this paper first of
all we analyzed the performance investigation of wireless routing protocols on the basis of ROH (Routing
Overhead), throughput, end-2-end delay and PDR (Packet Delivery Ratio). After that we proposed an MRP
(Mixed Routing Protocol) framework which improve performance.
BLOSEN: BLOG SEARCH ENGINE BASED ON POST CONCEPT CLUSTERINGijasa
This paper focuses on building a blog search engine which doesn’t focus only on keyword search but
includes extended search capabilities. It also incorporates the blog-post concept clustering which is based
on the category extracted from the blog post semantic content analysis. The proposed approach is titled as
“BloSen (Blog Search Engine)” It involves in extracting the posts from blogs and parsing them to extract
the blog elements and store them as fields in a document format. Inverted index is being built on the fields
of the documents. Search is induced on the index and requested query is processed based on the documents
so far made from blog posts. It currently focuses on Blogger and Wordpress hosted blogs since both these
hosting services are the most popular ones in the blogosphere. The proposed BloSen model is experimented
with a prototype implementation and the results of the experiments with the user’s relevance cumulative
metric value of 95.44% confirms the efficiency of the proposed model.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Wireless sensor networks provide ubiquitous computing systems in various open environments. In the
environment, sensor nodes can easily be compromised by adversaries to generate injecting false data
attacks. The injecting false data attack not only consumes unnecessary energy in en-route nodes, but also
causes false alarms at the base station. To detect this type of attack, a bandwidth-efficient cooperative
authentication (BECAN) scheme was proposed to achieve high filtering probability and high reliability
based on random graph characteristics and cooperative bit-compressed authentication techniques. This
scheme may waste energy resources in en-route nodes due to the fixed number of forwarding reports. In
this paper, our proposed method effectively selects a dynamic number of forwarding reports in the source
nodes based on an evaluation function. The experimental results indicate that our proposed method
enhances the energy savings while maintaining security levels as compared to BECAN.
AN EVALUATION OF ENERGY EFFICIENT SOURCE AUTHENTICATION METHODS FOR FALSE DA...ijsptm
The false data injection attack is a major security threat in Wireless Sensor Network (WSN) since is
degrades the network capability. The bandwidth efficient cooperative authentication (BECAN) scheme is
used for filtering the false data injection attack. It is used to save energy of sensor nodes in WSN by early
detection and filtering of maximum possible injected false data. Source authentication is a critical security
requirement in wireless sensor networks to identify attacker nodes that injects false data. Solutions based
on Elliptic Curve Cryptography (ECC) have been used for source authentication, but they suffer from
severe energy depletion. This results in high computational and communication overheads. Bloom filter
based Symmetric-key source authentication scheme exhibits low authentication overhead .This avoids the
inherent problems associated with public key cryptography based schemes. The current work demonstrates
the efficiency of bloom filter based source authentication using BECAN scheme by comparing ECC and
Bloom filter based methods in terms of energy consumption
Detection of PUE Attack by SPARS Model using WSPRTEditor IJCATR
Cognitive radio is a system which improves the utilization of the spectrum by sensing the white spaces in its vicinity. This
sensed information will be utilized by the Secondary User (SU) to transmit the data. But some of the malicious users attacks th
system by generating the signal same as that of the primary transmitter. The attack caused by generating the signal same as t
primary transmitter is called as Primary User Emulation Attack (PUEA). In this paper the Signal Activity Pattern Acquisition
Reconstruction System (SPARS) is used to detect the attack. But this system suffers from low True Positive Rate. To incr
positive rate or sensitivity a new technique was proposed called as Weighted Sequential Probability Ratio Test (WSPRT). By
improving the true positive rate or sensitivity, the detection capability of the system will be improved.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Limiting Self-Propagating Malware Based on Connection Failure Behavior csandit
Self-propagating malware (e.g., an Internet worm) exploits security loopholes in software to
infect servers and then use them to scan the Internet for more vulnerable servers. While the
mechanisms of worm infection and their propagation models are well understood, defense
against worms remains an open problem. One branch of defense research investigates the
behavioral difference between worm-infected hosts and normal hosts to set them apart. One
particular observation is that a worm-infected host, which scans the Internet with randomly
selected addresses, has a much higher connection-failure rate than a normal host. Rate-limit
algorithms have been proposed to control the spread of worms by traffic shaping based on
connection failure rate. However, these rate-limit algorithms can work properly only if it is
possible to measure failure rates of individual hosts efficiently and accurately. This paper points
out a serious problem in the prior method and proposes a new solution based on a highly
efficient double-bitmap data structure, which places only a small memory footprint on the
routers, while providing good measurement of connection failure rates whose accuracy can be
tuned by system parameters.
AN ENERGY EFFICIENT COUNTERMEASURE AGAINST MULTIPLE ATTACKS OF THE FALSE DATA...ijcsity
Nodes are easily exposed from generated attacks on various layers because they compose simple functions in sensor networks. The false data injection attack drains finite energy resource in a compromised node,and the false HELLO flood attack threatens constructed routing paths in an adversary node. A localized encryption and authentication protocol (LEAP) was developed to prevent the aforementioned attacks through the use of four keys. However, when these attacks occur simultaneously, LEAP may not prevent damage from spreading rapidly throughout the network. In this paper, we propose a method that addresses these attacks through the use of four types of keys, including two new keys. We also improve energy consumption while maintaining a suitable security level. The effectiveness of the proposed method was evaluated relative to that of LEAP when multiple attacks occur. The experimental results reveal that the proposed method enhances energy saving by up to 12% while maintaining sufficient detection power
Improving performance of routing protocols using mrp frameworkijasa
These days MANET (Mobile Ad-hoc Network) is an amazing remarkably altering or rising technology, for
the reason that of its elite nature of scattered mobile devices and self-motivated network topology. The
mobile ad-hoc routing protocol follows several principles in wireless MANET’s. The up to date and novel
applications based on wireless technology are being produced in the private as well as commercial sectors.
A lot of challenges which are facing wireless MANETs like network stability, security, energy efficiency
and performance analysis etc. At present wireless ad-hoc network get much more attention because of its
accessibility everywhere. As a result researchers produce several routing protocols. In this paper first of
all we analyzed the performance investigation of wireless routing protocols on the basis of ROH (Routing
Overhead), throughput, end-2-end delay and PDR (Packet Delivery Ratio). After that we proposed an MRP
(Mixed Routing Protocol) framework which improve performance.
BLOSEN: BLOG SEARCH ENGINE BASED ON POST CONCEPT CLUSTERINGijasa
This paper focuses on building a blog search engine which doesn’t focus only on keyword search but
includes extended search capabilities. It also incorporates the blog-post concept clustering which is based
on the category extracted from the blog post semantic content analysis. The proposed approach is titled as
“BloSen (Blog Search Engine)” It involves in extracting the posts from blogs and parsing them to extract
the blog elements and store them as fields in a document format. Inverted index is being built on the fields
of the documents. Search is induced on the index and requested query is processed based on the documents
so far made from blog posts. It currently focuses on Blogger and Wordpress hosted blogs since both these
hosting services are the most popular ones in the blogosphere. The proposed BloSen model is experimented
with a prototype implementation and the results of the experiments with the user’s relevance cumulative
metric value of 95.44% confirms the efficiency of the proposed model.
The International Journal of Ambient Systems and Applications (IJASA) ijasa
The International Journal of Ambient Systems and applications is a quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of ambient Systems. The journal focuses on all technical and practical aspects of ambient Systems, networks, technologies and applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced ambient Systems and establishing new collaborations in these areas.Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in ambient Systems.
Fuzzy Logic-based Efficient Message Route Selection Method to Prolong the Net...IJCNCJournal
Recently, sensor networks have been used in a wide range of applications, and interest in sensor node performance has increased. A sensor network is composed of tiny nodes with limited resources. The sensor network communicates between nodes in a configured network through self-organization. An energyefficient security protocol with a hierarchy structure with various advantages has been proposed to prolong the network lifetime of sensor networks. But due to structural problems in traditional protocols, nodes located upstream tend to consume relatively high energy compared to other nodes. A network protocol should be considered to provide minimal security and efficient allocation of energy consumption by nodes to increase the network lifetime. In this paper, we introduce a solution to solve the bottleneck problem through an efficient message route selection method. The proposed method selects an efficient messaging path using GA and fuzzy logic composed of multiple rules. Message route selection plays an important role in controlling the load balancing of nodes. A principal benefit of the proposed scheme is the potential portability of the clustering-based protocol. In addition, the proposed method is updated to find the optimal path through the genetic algorithm to respond to various environments. We demonstrated the effectiveness of the proposed method through an experiment in which the proposed method is applied to a probabilistic voting-based filtering scheme that is one of the cluster-based security schemes.
FUZZY LOGIC-BASED EFFICIENT MESSAGE ROUTE SELECTION METHOD TO PROLONG THE NET...IJCNCJournal
Recently, sensor networks have been used in a wide range of applications, and interest in sensor node
performance has increased. A sensor network is composed of tiny nodes with limited resources. The sensor
network communicates between nodes in a configured network through self-organization. An energyefficient security protocol with a hierarchy structure with various advantages has been proposed to
prolong the network lifetime of sensor networks. But due to structural problems in traditional protocols,
nodes located upstream tend to consume relatively high energy compared to other nodes. A network
protocol should be considered to provide minimal security and efficient allocation of energy consumption
by nodes to increase the network lifetime. In this paper, we introduce a solution to solve the bottleneck
problem through an efficient message route selection method. The proposed method selects an efficient
messaging path using GA and fuzzy logic composed of multiple rules. Message route selection plays an
important role in controlling the load balancing of nodes. A principal benefit of the proposed scheme is the
potential portability of the clustering-based protocol. In addition, the proposed method is updated to find
the optimal path through the genetic algorithm to respond to various environments. We demonstrated the
effectiveness of the proposed method through an experiment in which the proposed method is applied to a
probabilistic voting-based filtering scheme that is one of the cluster-based security schemes.
An Enhanced Detection and Energy-Efficient En-Route Filtering Scheme in Wirel...ieijjournal
Wireless sensor networks (WSNs), due to their small size, low cost, and untethered communication over a short-range, have great potential for applications and services. Due to hostile environments and an unattended nature, they are prone to many types of attacks by adversaries. False data injection attacks compromise data accuracy at the sink node and cause undesirable energy depletion at the sink and intermediate nodes. In order to detect and counter false data attacks, a number of en-route filtering schemes have been proposed. However, they lack a strong false report detection capacity or cannot support network dynamics well. Commutative cipher-based en-route filtering (CCEF) is based on fixed paths, and a fixed detection probability, and does not consider the residual energy of a node. In an enhanced detectioncapacity and energy-efficient en-route filtering (EDEF) scheme, we use a fuzzy logic system which considers the residual energy, false traffic ratio (FTR), and number of message authentication codes (MACs) in a report to evaluate the fitness of a node to be a verification node. This helps to balance network energy usage and reduce the number of hops a false report may travel. The simulation results demonstrate the validity of our scheme with increased energy-efficiency (4.55 to 13.92%) and detection power (99.95%)
AN ENHANCED DETECTION AND ENERGYEFFICIENT EN-ROUTE FILTERING SCHEME IN WIRELE...ieijjournal
Wireless sensor networks (WSNs), due to their small size, low cost, and untethered communication over a short-range, have great potential for applications and services. Due to hostile environments and an unattended nature, they are prone to many types of attacks by adversaries. False data injection attacks compromise data accuracy at the sink node and cause undesirable energy depletion at the sink and intermediate nodes. In order to detect and counter false data attacks, a number of en-route filtering schemes have been proposed. However, they lack a strong false report detection capacity or cannot support network dynamics well. Commutative cipher-based en-route filtering (CCEF) is based on fixed paths, and a
fixed detection probability, and does not consider the residual energy of a node. In an enhanced detectioncapacity and energy-efficient en-route filtering (EDEF) scheme, we use a fuzzy logic system which considers the residual energy, false traffic ratio (FTR), and number of message authentication codes
(MACs) in a report to evaluate the fitness of a node to be a verification node. This helps to balance network
energy usage and reduce the number of hops a false report may travel. The simulation results demonstrate the validity of our scheme with increased energy-efficiency (4.55 to 13.92%) and detection power (99.95%) against false report attacks in WSNs.
Fuzzy-Based Multiple Path Selection Method for Improving Energy Efficiency in...aciijournal
In wireless sensor networks, adversaries can easily compromise sensors because the sensor resources are
limited. The compromised nodes can inject false data into the network injecting false data attacks. The
injecting false data attack has the goal of consuming unnecessary energy in en-route nodes and causing
false alarms in a sink. A bandwidth-efficient cooperative authentication scheme detects this attack based on
the random graph characteristics of sensor node deployment and a cooperative bit-compressed
authentication technique. Although this scheme maintains a high filtering probability and high reliability in
the sensor network, it wastes energy in en-route nodes due to a multireport solution. In this paper, our
proposed method effectively selects a number of multireports based on the fuzzy rule-based system. We
evaluated the performance in terms of the security level and energy savings in the presence of the injecting
false data attacks. The experimental results indicate that the proposed method improves the energy
efficiency up to 10% while maintaining the same security level as compared to the existing scheme.
NUMBER OF NEIGHBOUR NODES BASED NEXT FORWARDING NODES DETERMINATION SCHEME FO...ijcsity
Wireless Sensor Networks (Wsn) Are Used In Various Areas. These Networks Are Deployed In An Open Environment. So, They Are Very Weak Against An Attack, And Easily Damaged.The Wsn Has Limited Resources In Terms Of Battery Life, Computing Power, Communication Bandwidth And So On. Many Attacks Aim At That Point.The False Report Injection Attack Is One Of Them. Yu Et Al. Proposed A Dynamic En-Route Filtering Scheme (Def),To Prevent A False Report Injection Attack.In This Paper, We Propose An Energy Enhancement Scheme For Def Using A Fuzzy System. The Def Is Divided Into Three Phases (Key Pre-Distribution Phase, Key Dissemination Phase, Report Forwarding Phase). We Applied Our Scheme At The Next Forwarding Node Determination. So We Used Three Input Factors Of A Fuzzy System To Make A Determination. These Are The Availability Of Energy, Distance To The Base Station,
And Usage Count.Through The Experiments, Our Proposed Method Shows Up To 8.2% Energy Efficiency,Compared With The Def. If The Networks Consume More Energy, Our Proposed Method Shows More Efficiency For The Energy.
A KEY LEVEL SELECTION WITHIN HASH CHAINS FOR THE EFFICIENT ENERGY CONSUMPTION...IAEME Publication
A wireless sensor network is comprised of a base station (BS) and numerous sensor nodes. The sensor nodes lack security because they function in an open environment, such as the military. In particular, a false statement injection attack seizures and compromises sensor nodes. The attack then causes the compromised nodes to create forward false reports. Due to the false report injection attack, not only does the sensor network have a false alarm, but its limited energy is also emptied. In order to preserve the false report injection attack, over the past few years, several studies have been made looking for a resolution to the attack. Ye et al. studied statistical en-route filtering (SEF). SEF is a method of randomly verifying event reports in the en-route filtering phase. SEF can filter many false reports early using proof of intermediate nodes. However, because the number of keys in a sensor node is fixed by the system, the sensor network cannot control the event report proof probability depending on the conditions of the network. Therefore, it is tough to proficiently consume energy of the sensor network. In order to resolve the problem, we suggest a technique which controls the event report verification probability by using a key sequence level of an event report. In the suggested method, when an intermediate node obtains an event report, the node authenticates the event report by relating a key sequence level of the report and its key
A wireless sensor network (WSN) consists of multiple sensor nodes and base stations that collect information from widely deployed sensors. However, the disadvantage is that WSNs are randomly distributed in an open environment, which makes them difficult to manage individually and more easily found and compromised by an attacker. An attacker can execute a false report insertion or invalid vote insertion attack through a compromised node. The Probabilistic Voting Filtering System (PVFS) is a system that prevents these two types of attacks. Before sending a report, the proposed method probabilistically selects a validation node, determines the validity of the report, and filters the report based on the thresholds that have been set. In this paper, the proposed scheme improves the lifetime, detection rate, and report delivery rate of the entire network by increasing the lifetime of the cluster head (CH) by selecting the numbers of message authentication codes (MACs) and verification nodes of the report. Using this system, the event detection rate and the network lifetime are improved by up to 18% and 6%, respectively, relative to the existing PVFS.
A wireless sensor network (WSN) consists of multiple sensor nodes and base stations that collect information from widely deployed sensors. However, the disadvantage is that WSNs are randomly distributed in an open environment, which makes them difficult to manage individually and more easily found and compromised by an attacker. An attacker can execute a false report insertion or invalid vote insertion attack through a compromised node. The Probabilistic Voting Filtering System (PVFS) is a system that prevents these two types of attacks. Before sending a report, the proposed method probabilistically selects a validation node, determines the validity of the report, and filters the report based on the thresholds that have been set. In this paper, the proposed scheme improves the lifetime, detection rate, and report delivery rate of the entire network by increasing the lifetime of the cluster head (CH) by selecting the numbers of message authentication codes (MACs) and verification nodes of the report. Using this system, the event detection rate and the network lifetime are improved by up to 18% and 6%, respectively, relative to the existing PVFS.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
BLACKLIST MANAGEMENT USING A VERIFICATION REPORT TO IMPROVE THE ENERGY EFFICI...ijwmn
Recently, the applications scope of Wireless Sensor Networks (WSNs) has been broadened. WSN communication security is important because sensor nodes are vulnerable to various security attacks when deployed in an open environment. An adversary could exploit this vulnerability to inject false reports into the network. En-route filtering techniques have been researched to block false reports. The CFFS scheme
filters the false report by collaboratively validating the report by clustering the nodes. However, CFFS is not considered effective against repetitive attacks. Repeated attacks have a significant impact on network lifetime. In this paper, we propose a method to detect repetitive attacks with cluster-based false data
filtering and to identify the compromised nodes and quickly block them. The proposed scheme uses fuzzy logic to determine the distribution of additional keys according to the network conditions, thereby improving energy efficiency.
A security method for multiple attacks in sensor networks against the false r...ijitjournal
In a large scale wireless sensor network, various attacks rapidly spread damages in the network from
inside and outside attacks such as the false report injection attack and the sinkhole attack, respectively.
These attacks drain finite energy resources and devastate constructed routing paths via compromised
nodes. The security methods like SEF (statistical en-route filtering scheme) and LEAP (localized encryption
and authentication protocol) try to cope with these attacks. When these attacks occur at the same time, SEF
and LEAP should be operated simultaneously in the sensor network thus, it introduces some inefficiency. In
this paper, we propose a security method which improves the energy efficiency while maintaining the
security level compared to the simultaneous application of SEF and LEAP. The proposed method is
designed by identifying and eliminating the redundancies within the simultaneous application of the two
methods and providing more efficient functionalities. In the proposed method, two types of new keys are
designed and provided for simultaneous detection of the attacks. Four types of keys are used in each sensor
node – a P1 for encrypting information, a PK (pairwise key) for keeping secure paths, a P2 for verifying a
specific cluster, and a GK (group key) for encrypting message. Among these keys, P1 and P2 are newly
provided keys. We have evaluated the effectiveness of the proposed method compared to the simultaneous
application of SEF and LEAP when the multiple attacks occur. The experiment results show that our
proposed method saves energy up to 10% while maintaining the detection power
GEOGRAPHIC INFORMATION-BASED ROUTING OPTIMIZATION USING GA FOR CLUSTER-BASED ...ijwmn
Wireless sensor networks are used for data collection and event detection in various fields such as home networks, military systems, and forest fire monitoring, and are composed of many sensor nodes and a base station. Sensor nodes have limited computing power, limited energy, are randomly distributed in an open environment that operates independently, and have difficulties in individual management. Taking advantage of those weaknesses, attackers can compromise sensor nodes for various kinds of network attacks. Several security protocols have been proposed to prevent these attacks. Most of the security protocols form routings with cluster head nodes. In the case of routing using only cluster head nodes, it is difficult to re-route when the size of the cluster is increased or the number of the surviving nodes is reduced. To prevent these attacks, the proposed scheme maintains security in a cluster-based security protocol and shows energy efficient routing using genetic algorithm by selecting the appropriate cluster head nodes and
utilizing the characteristics of the sensor node with different transmission outputs based on the distance between each node. In this paper, we use a probabilistic voting-based filtering scheme, one of the clusterbased security protocols, and the shortest path, which is a hierarchical routing protocol that the original probabilistic voting-based filtering scheme is using, to test the proposed scheme. This experiment shows the performance comparison of the routing success rate and routing cost according to the number of nodes on the field, as well as the performance comparison according to the cluster size per number of nodes.
GEOGRAPHIC INFORMATION-BASED ROUTING OPTIMIZATION USING GA FOR CLUSTER-BASED ...ijwmn
Wireless sensor networks are used for data collection and event detection in various fields such as homenetworks, military systems, and forest fire monitoring, and are composed of many sensor nodes and a basestation. Sensor nodes have limited computing power, limited energy, are randomly distributed in an open environment that operates independently, and have difficulties in individual management. Taking advantage of those weaknesses, attackers can compromise sensor nodes for various kinds of network attacks. Several security protocols have been proposed to prevent these attacks. Most of the security protocols form routings with cluster head nodes. In the case of routing using only cluster head nodes, it is difficult to re-route when the size of the cluster is increased or the number of the surviving nodes is reduced. To prevent these attacks, the proposed scheme maintains security in a cluster-based security protocol and shows energy efficient routing using genetic algorithm by selecting the appropriate cluster head nodes and
utilizing the characteristics of the sensor node with different transmission outputs based on the distance between each node. In this paper, we use a probabilistic voting-based filtering scheme, one of the clusterbased security protocols, and the shortest path, which is a hierarchical routing protocol that the original probabilistic voting-based filtering scheme is using, to test the proposed scheme. This experiment shows the performance comparison of the routing success rate and routing cost according to the number of nodes on the field, as well as the performance comparison according to the cluster size per number of nodes.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
IMPROVEMENT OF FALSE REPORT DETECTION PERFORMANCE BASED ON INVALID DATA DETEC...IJCNCJournal
WSN consists of a number of nodes and base stations and is used for event monitoring in various fields such as war situations, forest fires, and home networks. WSN sensor nodes are placed in fields that are difficult for users to manage. It is therefore vulnerable to attackers, and attackers can use false nodes or MAC injection attacks through the hijacked nodes to reduce the lifetime of the network or trigger false alarms. In order to prevent such attacks, several security protocols have been proposed, and all of them have been subjected to MAC-dependent validation, making it impossible to defend against false report attacks in extreme attack circumstances. As attacks have recently become more diverse and more intelligent, WSNs require intelligent methods of security. Based on the report information gathered from the base station, the proposed method provides a technique to prevent attacks that may occur where all MAC information is damaged by carrying out verification of a false report attack through the machine learning based prediction model and the evaluation function.
Wireless sensor networks collect data through collaborative communication between sensor nodes. sensor nodes of wireless sensor networks are deployed in open environments. Hence, an attacker can easily compromise the node. An attacker can compromise a node to generate false reports and inject into the network. This causes unnecessary energy consumption in the process of transmitting false alarm messages and false data reports to the system. If the attacker keeps repeatedly attacking thereby causing problems such as reduction in the entire network life or disabling the networks. Yu and Guan proposed a dynamic en-route filtering scheme to detect and drop these false reports before reaching to the Base station. In the dynamic en-route filtering, the energy waste of the intermediate nodes occurs until it is detected early. In this paper, we propose a method to save the energy of the intermediate nodes by searching for the compromised node and blocking the reports generated at that node. When verifying a false report at the verification node, it can know report information. The base station is able to find the cluster of compromised nodes using that information. In particular, the base station can know the location of the node that has been compromised, we can block false alarms and energy losses by blocking reports generated in that cluster.
PREVENTION METHOD OF FALSE REPORT GENERATION IN CLUSTER HEADS FOR DYNAMIC EN-...ijcsit
Wireless sensor networks collect data through collaborative communication between sensor nodes. sensor nodes of wireless sensor networks are deployed in open environments. Hence, an attacker can easily compromise the node. An attacker can compromise a node to generate false reports and inject into the network. This causes unnecessary energy consumption in the process of transmitting false alarm messages and false data reports to the system. If the attacker keeps repeatedly attacking thereby causing problems such as reduction in the entire network life or disabling the networks. Yu and Guan proposed a dynamic en-route filtering scheme to detect and drop these false reports before reaching to the Base station. In the dynamic en-route filtering, the energy waste of the intermediate nodes occurs until it is detected early. In this paper, we propose a method to save the energy of the intermediate nodes by searching for the compromised node and blocking the reports generated at that node. When verifying a false report at the verification node, it can know report information. The base station is able to find the cluster of compromised nodes using that information. In particular, the base station can know the location of the node that has been compromised, we can block false alarms and energy losses by blocking reports
generated in that cluster.
Wireless sensor networks collect data through collaborative communication between sensor nodes. sensor
nodes of wireless sensor networks are deployed in open environments. Hence, an attacker can easily
compromise the node. An attacker can compromise a node to generate false reports and inject into the
network. This causes unnecessary energy consumption in the process of transmitting false alarm messages
and false data reports to the system. If the attacker keeps repeatedly attacking thereby causing problems
such as reduction in the entire network life or disabling the networks. Yu and Guan proposed a dynamic
en-route filtering scheme to detect and drop these false reports before reaching to the Base station. In the
dynamic en-route filtering, the energy waste of the intermediate nodes occurs until it is detected early. In
this paper, we propose a method to save the energy of the intermediate nodes by searching for the
compromised node and blocking the reports generated at that node. When verifying a false report at the
verification node, it can know report information. The base station is able to find the cluster of
compromised nodes using that information. In particular, the base station can know the location of the
node that has been compromised, we can block false alarms and energy losses by blocking reports
generated in that cluster.
A secure routing process to simultaneously defend against false report and wo...ieijjournal
Most research related to secure routing in sensor networks has focused on how to detect and defend against a single attack. However, it is not feasible to predict which attack will occur in sensor networks. It is possible for multiple attacks to occur simultaneously, degrading the performance of the existing security schemes. For example, an attacker may try simultaneous false report and wormhole attacks to effectively damage a sensor network. Hence, a multiple simultaneous attack environment is much more complex than a single attack environment. Thus, a new security scheme that can detect multiple simultaneous attacks with a high probability and low energy consumption is needed. In this paper, we propose a secure routing scheme to defend against wormhole and false report attacks in sensor networks. The proposed method achieves a higher attack detection ratio and consumes less energy in a multi-attack scenario compared to existing schemes. It can also be extended to other types of attacks and security schemes to detect and defend against possible combinations of multiple attacks.
Similar to A KEY LEVEL SELECTION WITHIN HASH CHAINS FOR THE EFFICIENT ENERGY CONSUMPTION IN WSNS (20)
A CONCEPTUAL FRAMEWORK OF A DETECTIVE MODEL FOR SOCIAL BOT CLASSIFICATIONijasa
Social media platform has greatly enhanced human interactive activities in the virtual community. Virtual
socialization has positively influenced social bonding among social media users irrespective of one’s
location in the connected global village. Human user and social bot user are the two types of social media
users. While human users personally operate their social media accounts, social bot users are developed
software that manages a social media account for the human user called the botmaster. This botmaster in
most cases are hackers with bad intention of attacking social media users through various attacking mode
using social bots. The aim of this research work is to design an intelligent framework that will prevent
attacks through social bots on social media network platforms.
DESIGN OF A MINIATURE RECTANGULAR PATCH ANTENNA FOR KU BAND APPLICATIONSijasa
A significant portion of communication devices employs microstrip antennas because of their compact size,
low profile, and ability to conform to both planar and non-planar surfaces. To achieve this, we present a
miniature inset-fed rectangular patch antenna using partial ground plane for Ku band applications. The
proposed antenna design used an operating frequency of 15.5 GHz, a FR4 substrate with a dielectric
constant of 4.3, and a thickness of 1.4 mm. It is fed by a 50 Ω inset feedline. Computer simulation
technology (CST) software is used to design, simulate, and analyze. The simulation yields the antenna
performance parameters, including return loss (S11), bandwidth, VSWR, gain, directivity, and radiation
efficiency. The simulation findings revealed that the proposed antenna resonated at 15.5 GHz, with a
return loss of -22.312 dB, a bandwidth of 2.73 GHz (2730 MHz), VSWR of 1.17, a gain of 3.843 dBi, a
directivity of 5.926 dBi, and an antenna efficiency of -2.083 dB (61.901%).
SMART SOUND SYSTEM APPLIED FOR THE EXTENSIVE CARE OF PEOPLE WITH HEARING IMPA...ijasa
We, as normal people, have access to a potent communication tool, which is sound. Although we can continuously gather, analyse, and interpret sounds thanks to our sense of hearing, it can be challenging for people with hearing impairment to perceive their surroundings through sound. Also known as PWHI (People with Hearing Impairment). Auditory/phonic impairment is one of the most prevailing sensory deficits in humans at present. Fortunately, there is room to apply a solution to this issue, given the development of technology. Our project involves capturing ambient sounds from the user’s surroundings and notifying the user through a mobile application using IoT and Deep Learning. Its architecture offers sound recognition using a tool, such as a microphone, to capture sounds from the user's surroundings. These sounds are identified and categorized as ambient sounds, like a doorbell, baby cry, and dog barking; as well as emergency-related sounds, such as alarms, sirens, et
AN INTELLIGENT AND DATA-DRIVEN MOBILE VOLUNTEER EVENT MANAGEMENT PLATFORM USI...ijasa
In Lewis and Clark High School’s Key Club, meetings are always held in a crowded classroom. The
system of event sign-up is inefficient and hinders members from joining events. This has led to students
becoming discouraged from joining Key Club and often resulted in a lack of volunteers for important
events. The club needed a more efficient way of connecting volunteers with volunteering opportunities. To
solve this problem, we developed a VolunteerMatch Mobile application using Dart and Flutter framework
for Key Club to use. The next steps will be to add a volunteer event recommendation and matching feature,
utilizing the results from the research on machine learning models and algorithms in this paper.
A STUDY OF IOT BASED REAL-TIME SOLAR POWER REMOTE MONITORING SYSTEMijasa
We have Developed an IoT-based real-time solar power monitoring system in this paper. It seeks an opensource IoT solution that can collect real-time data and continuously monitor the power output and environmental conditions of a photovoltaic panel.The Objective of this work is to continuously monitor the status of various parameters associated with solar systems through sensors without visiting manually, saving time and ensures efficient power output from PV panels while monitoring for faulty solar panels, weather conditionsand other such issues that affect solar effectiveness.Manually, the user must use a multimeter to determine what value of measurement of the system is appropriate for appliance consumers, which is difficult for the larger System. But the Solar Energy Monitoring system is designed to make it easier for users to use the solar system.This system is comprised of a microcontroller (Node MCU), a PV panel, sensors (INA219 Current Module, Digital Temperature Sensor, LDR), a Battery Charger Module, and a battery. The data from the PV panels and other appliances are sent to the cloud (Thingspeak) via the internet using IoT technology and a Wi-Fi module (NodeMCU). It also allows users in remote areas to monitor the parameters of the solar power plant using connected devices. The user can view the current, previous, and average parameters of the solar PV system, such as voltage, current, temperature, and light intensity using a Graphical User Interface. This will facilitate fault detection and maintenance of the solar power plant easier and saves time.
SENSOR BASED SMART IRRIGATION SYSTEM WITH MONITORING AND CONTROLLING USING IN...ijasa
This paper presents the development of a sensor based smart irrigation system with the capabilities of remote monitoring and controlling of water usage in the agriculture field using Internet of Things (IoT). With the employment of IoT in irrigation system, all agricultural information can be viewed and controlled at the user's fingertips. The system consists of a microcontroller (Node MCU), sensors (soil moisture, DHT11), and irrigation of a water pump with a decision-making system. Sensors are linked to a Wi-Fi module (Node MCU) and are interdependent to provide increased sensitivity to the irrigation system. The data obtained will be uploaded to the cloud (ThingSpeak) and presented in the form of graphs accessible via the website. A web page is used to control the water pump for irrigation purposes. This paper is managed to meet all of its aims to help farmers in terms of time, project cost, labor, water consumption, power consumption, and reliability by implementing the IoT-based smart irrigation system.
COMPARISON OF BIT ERROR RATE PERFORMANCE OF VARIOUS DIGITAL MODULATION SCHEME...ijasa
Digital modulation increases information capacity, data security, and system availability while maintaining high communication quality. As a result, digital modulation techniques are in higher demand than analog modulation techniques due to their ability to transmit larger amounts of data. Amplitude Shift Keying (ASK), Frequency Shift Keying (FSK), Phase Shift Keying (PSK), Differential Phase Shift Keying (DPSK), and Quadrature Amplitude Modulation (QAM) are critical components of current communications systems development, particularly for broadband wireless communications. In this paper, the comparison of bit error rate performance of different modulation schemes (BPSK, QPSK, and16-QAM) and various equalization techniques such as constant modulus algorithm (CMA) and maximum likelihood sequence estimate (MLSE) for the AWGN and Rayleigh fading channels is analyzed using Simulink. BPSK outperforms QPSK and 16-QAM when compared to the other two digital modulation schemes. Among the three digital modulation schemes, BPSK is showing better performance as compared to QPSK and 16- QAM
PERFORMANCE OF CONVOLUTION AND CRC CHANNEL ENCODED V-BLAST 4×4 MIMO MCCDMA WI...ijasa
Wireless communications are among the rapidly growing fields in our current life and have a massive effect on every aspect of our everyday life. In this paper, the performance of the various digital modulation techniques (BPSK, DPSK, QPSK, and QAM) based wireless communication system on the audio signal transmission through the additive Gaussian Noise (AWGN) channel is assessed on the basis of bit error rate (BER) as a function of the signal-to-noise ratio (SNR). Based on the results of this study, BPSK modulation outperforms the DPSK, QPSK, and QAM modulation strategies in the MIMO MC-CDMA VBlast based wireless communication system. The digital modulation of QPSK shows the worst performance in audio signal transmission especially in comparison to other digital modulations. It is clear from the current simulation study based on MATLAB that the V-Blast encoded 4×4 MIMO MC-CDMA wireless system with minimum mean square error (MMSE) signal detection and 1⁄2-rated convolution and cyclic redundancy check (CRC) channel encoding strategies show good performance utilizing BPSK digital modulation in audio signal transmission
A SCRUTINY TO ATTACK ISSUES AND SECURITY CHALLENGES IN CLOUD COMPUTINGijasa
Cloud computing is an anthology in which one or more computers are connected in a network. Cloud
computing is a cluster of lattice computing, autonomic computing and utility computing. Cloud provides an
on demand services to the users. Many numbers of users access the cloud to utilize the cloud resources.
The security is one the major problem in cloud computing. Hence security is a major issue in cloud
computing. Providing security is a major requirement of cloud computing. The study enclose all the
security issues and attack issues in cloud computing.
A SCRUTINY TO ATTACK ISSUES AND SECURITY CHALLENGES IN CLOUD COMPUTINGijasa
Cloud computing is an anthology in which one or more computers are connected in a network. Cloud computing is a cluster of lattice computing, autonomic computing and utility computing. Cloud provides an on demand services to the users. Many numbers of users access the cloud to utilize the cloud resources. The security is one the major problem in cloud computing. Hence security is a major issue in cloud computing. Providing security is a major requirement of cloud computing. The study enclose all the security issues and attack issues in cloud computing.
TOWARD ORGANIC COMPUTING APPROACH FOR CYBERNETIC RESPONSIVE ENVIRONMENTijasa
The developpment of the Internet of Things (IoT) concept revives Responsive Environments (RE) technologies. Nowadays, the idea of a permanent connection between physical and digital world is technologically possible. The capillar Internet relates to the Internet extension into daily appliances such as they become actors of Internet like any hu-man. The parallel development of Machine-to-Machine
communications and Arti cial Intelligence (AI) technics start a new area of cybernetic. This paper presents an approach for Cybernetic Organism (Cyborg) for RE based on Organic Computing (OC). In such approach, each appli-ance is a part of an autonomic system in order to control a physical environment.The underlying idea is that such systems must have self-x properties in order to adapt their behavior to
external disturbances with a high-degree of autonomy.
A STUDY ON DEVELOPING A SMART ENVIRONMENT IN AGRICULTURAL IRRIGATION TECHNIQUEijasa
Maintaining a good irrigation system is a necessity in today’s water scarcity environment. This paper describes a new approach for automated Smart Irrigation (SIR) system in agricultural management. Using
various types of sensors in the crop field area, temperature and moisture value of the soil is monitored.Based on the sensed data, SIR will automatically decide about the necessary action for irrigation and also notifies the user. The system will also focus on the reduction of energy consumption by the sensors during communication.
A REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGYijasa
Denial of Service (DoS) or Distributed-Denial of Service (DDoS) is major threat to network security.
Network is collection of nodes that interconnect with each other for exchange the Information. This
information is required for that node is kept confidentially. Attacker in network computer captures this
information that is confidential and misuse the network. Hence security is one of the major issues. There
are one or many attacks in network. One of the major threats to internet service is DDoS (Distributed
denial of services) attack. DDoS attack is a malicious attempt to suspending or interrupting services to
target node. DDoS or DoS is an attempt to make network resource or the machine is unavailable to its
intended user. Many ideas are developed for avoiding the DDoS or DoS. DDoS happen in two ways
naturally or it may due to some botnets .Various schemes are developed defense against to this attack.
Main idea of this paper is present basis of DDoS attack. DDoS attack types, DDoS attack components,
survey on different mechanism to prevent DDoS
The smart mobile terminal operator platform Android is getting popular all over the world with its wide variety of applications and enormous use in numerous spheres of our daily life. Considering the fact of increasing demand of home security and automation, an Android based control system is presented in this paper where the proposed system can maintain the security of home main entrance and also the car door lock. Another important feature of the designed system is that it can control the overall appliances in a room. The mobile to security system or home automation system interface is established through Bluetooth. The hardware part is designed with the PIC microcontroller.
The World Wide Web is booming and radically vibrant due to the well established standards and widely accountable framework which guarantees the interoperability at various levels of the application and the society as a whole. So far, the web has been functioning at the random rate on the basis of the human intervention and some manual processing but the next generation web which the researchers called semantic web, edging for automatic processing and machine-level understanding. The well set notion, Semantic Web would be turn possible if only there exists the further levels of interoperability prevails among the applications and networks. In achieving this interoperability and greater functionality among the applications, the W3C standardization has already released the well defined standards such as RDF/RDF Schema and OWL. Using XML as a tool for semantic interoperability has not achieved anything effective and failed to bring the interconnection at the larger level. This leads to the further inclusion of inference layer at the top of the web architecture and its paves the way for proposing the common design for encoding the ontology representation languages in the data models such as RDF/RDFS. In this research article, we have given the clear implication of semantic web research roots and its ontological background process which may help to augment the sheer understanding of named entities in the web.
Artificial neural networks (ANN) consider classification as one of the most dynamic research and
application areas. ANN is the branch of Artificial Intelligence (AI). The neural network was trained by
back propagation algorithm. The different combinations of functions and its effect while using ANN as a
classifier is studied and the correctness of these functions are analyzed for various kinds of datasets. The
back propagation neural network (BPNN) can be used as a highly successful tool for dataset classification
with suitable combination of training, learning and transfer functions. When the maximum likelihood
method was compared with backpropagation neural network method, the BPNN was more accurate than
maximum likelihood method. A high predictive ability with stable and well functioning BPNN is possible.
Multilayer feed-forward neural network algorithm is also used for classification. However BPNN proves to
be more effective than other classification algorithms.
Wireless sensor networks (WSNs) are regularly deployed in harsh and unattended environments, and
sensor nodes are easily exposed to attacks due to the random arrangement of the sensor field. An attacker
can inject fabricated reports from a compromised node with false votes and false vote-based reports. The
false report attacks can waste the energy of the intermediate nodes, shortening the network lifetime.
Furthermore, false votes cause the filtering out of legitimate reports. A probabilistic voting-based filtering
scheme (PVFS) was proposed as a countermeasure against this type of attacks by Li and Wu. PVFS uses a
vote threshold, a security threshold, and a verification node. The scheme does not make additional use
energy or communications resources because the verification node and threshold values are fixed. There
needs to be a verification node selection method that considers the energy resources of the node. In this
paper, we propose a verification path election scheme based on a fuzzy logic system. In the proposed
scheme, one node transmits reports in the node with a strong state through a fuzzy logic system after which
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A KEY LEVEL SELECTION WITHIN HASH CHAINS FOR THE EFFICIENT ENERGY CONSUMPTION IN WSNS
1. International Journal of Ambient Systems and Applications (IJASA) Vol.1, No.3,september 2013
DOI : 10.5121/ijasa.2013.1301 01
A KEY LEVEL SELECTION WITHIN HASH CHAINS FOR
THE EFFICIENT ENERGY CONSUMPTION IN WSNS
Hyun Woo Lee1
, Su Man Nam2
and Tae Ho Cho3
123
College of Information and Communication Engineering, Sungkyunkwan University,
Suwon 440-746, Republic of Korea
ABSTRACT
A wireless sensor network is composed of a base station (BS) and numerous sensor nodes. The sensor
nodes lack security because they operate in an open environment, such as the military. In particular, a false
report injection attack captures and compromises sensor nodes. The attack then causes the compromised
nodes to generate forward false reports. Owing to the false report injection attack, not only does the sensor
network have a false alarm, but its limited energy is also drained. In order to defend the false report
injection attack, over the past few years, several studies have been made looking for a solution to the
attack. Ye et al. studied statistical en-route filtering (SEF). SEF is a method of stochastically verifying event
reports in the en-route filtering phase. SEF can filter many false reports early using verification of
intermediate nodes. However, because the number of keys in a sensor node is fixed by the system, the
sensor network cannot control the event report verification probability depending on the circumstances of
the network. Therefore, it is difficult to efficiently consume energy of the sensor network. In order to solve
the problem, we propose a method which controls the event report verification probability by using a key
sequence level of an event report. In the proposed method, when an intermediate node receives an event
report, the node verifies the event report by comparing a key sequence level of the report and its key
sequence level. Elements determining the key sequence level include the density of neighbour nodes in the
sensing range of a center of stimulus (CoS), the number of hops from the CoS to the BS, and the average of
the key sequence level of intermediate nodes in each path. We simulated the proposed method and the SEF
method to evaluate the performance in terms of energy efficiency and security. In the simulation results, the
proposed method consumed an average of 7.9% less energy of the sensor nodes compared to SEF method.
The number of false reports arriving at the BS of the proposed method was also less, by an average of 6.4,
compared to the SEF method. Through the results, we can see that when the number of false report is large
in the sensor network, the proposed method is more energy-efficient and secure than the SEF method.
KEYWORDS
Wireless sensor network, False report injection attack, Statistical en-route filtering, Energy Efficiency,
Security
2. International Journal of Ambient Systems and Applications (IJASA) Vol.1, No.3,september 2013
2
1. INTRODUCTION
Fig. 1. The operation of a false report injection attack
Wireless sensor networks consist of a large number of sensor nodes, which include sensing,
computation, and wireless communication capabilities [1, 2]. The sensor nodes are allocated in a
particular sensor field and operate each other collaboratively [1]. When an event occurs in the
sensor field, the nodes sense and compute data of the event. The nodes also forward the data of
the event to a BS [2]. The BS forwards the data to a user through the existing communication
infrastructure. Because the sensor networks operate in open environments such as a military
environment, the sizes of the nodes are very small and unmanned [3, 4]. Therefore, the nodes are
captured and compromised easily by an attacker from the outside [2]. A false report injection
attack especially causes a compromised node to generate a false report. Fig. 1 shows the operation
of a false report injection attack. In Fig. 1, because of the false report generation of the
compromised node in the sensor networks, the attacks lead to not only to false alarms, but also to
the depletion of the limited energy of the sensor nodes, thus shortening the life of the networks
[4]. In order to defend the false report injection attack, a lot of solutions have been proposed by
many researchers [4-14]. Ye et al. proposed a solution which is called SEF [4]. In SEF, each
intermediate node verifies an event report using authentication keys stochastically. The nodes
forward the event report to the next node or drop it depending on the verification results. When
the event report is false, the report is dropped. Thus, the false report is detected early by SEF.
However, the number of authentication keys included in a node has to be large for higher
verification of false report probability. If the number of keys of the node is more, then the energy
consumption of the node is larger. The number of keys is not adjusted depending on the situation
of the networks because it is fixed by the system. This means that it is difficult for the networks to
be operated efficiently. In order to solve the problem, we proposed a method which adjusts the
verification probability of the node using a scheme of a key sequence level. The key sequence
level is an index in a hash chain of a key, which makes a message authentication code (MAC) in
the event report. In the proposed method, the BS decides the key sequence level of an event report.
Intermediate nodes receiving the event report verify it by comparing the key sequence level of the
node’s key with the level of a MAC in the event report. The key sequence level is settled by a
fuzzy system in the BS. The fuzzy inputs determining the level are the average of the level of
nodes in each path forwarding an event report, the density of neighbour nodes of a CoS, and the
number of hop from the CoS to the BS. The proposed method includes security and efficient
energy consumption of sensor nodes by determining the appropriate key sequence level. The rest
of this paper is organized as follows. Section 2 describes the SEF. Section 3 explains the problem
statements. Section 4 presents a system model of the proposed method and the operation process
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3
of the proposed method. Section 5 shows the simulation results to evaluate the performance of the
proposed method. Finally section 6 concludes this paper.
2. BACKGROUND
2.1. Statistical en-route filtering
SEF is a countermeasure method which can filter false reports early on that are made by a
compromised node in a wireless sensor network using statistical verification during the en-route
filtering phase. SEF consists of three phases: key assignment and report generation, en-route
filtering, and sink verification. In the key assignment phase, before the sensor nodes are deployed
in a sensor field, each node receives some keys where the number is fixed by the system
randomly from a selected partition at random in the global key pool. In the report generation
phase, after the nodes are deployed, sensing nodes detecting the event elect a CoS when an event
occurs in the sensor network. They forward a partition index and a MAC to the BS which was
generated by a key that each node includes to a BS. The CoS generates an event report with the
event information and the received MACs and forwards the event report to the BS. In the en-route
filtering phase, when an intermediate node receives the event report, it verifies the report
stochastically. The node checks whether there are key indices of distinct partitions and MACs in
the report. If there is either more than one key index or less than the one in the same partition or
the number of them in the report does not correspond with the number of fixed MACs, the node
regards the report as a false report and drops it. The node then examines whether there is a key
index in the report corresponding with the key index of the node. If there is not a key index, the
node forwards the report to the next node. If not, the node generates a MAC using its key. It then
compares the MAC with the MAC in the report. If the MAC of the node is different from the
MAC in the report, the report is regarded as a false report and is dropped. Otherwise, the report is
regarded as a legitimate report and is forwarded to the next node. In the sink verification phase,
all of the event reports arriving at the sink are verified, because the sink includes all keys in the
global key pool. Thus, it can filter false reports out the false reports that are not filtered in the en-
route filtering phase.
3. PROBLEM STATEMENT
If a false report injection attack occurs in a wireless sensor network, a compromised node will
continuously generate many false reports, forwarding them to a BS. When the number of
compromised nodes becomes larger, the number of false reports becomes larger. The sensor
network which communicates many false reports may easily malfunction because of the energy
depletion of the sensor nodes in the network. In SEF, a representative countermeasure method, in
order to defend the network against the attack, intermediate nodes verify event reports using their
assigned key before they are deployed in a sensor field. The key number is a very important
element determining the verification probability of the report. The number of key that a node
includes becomes larger, the probability becomes higher. However, the node has to consume a lot
of verification energy. Moreover, when an attacker compromises a node, the number of keys that
the attacker can get becomes larger. On the other hand, as the number of keys becomes smaller,
the probability becomes smaller. However, the energy consumption used in the verification
becomes lower. Subsequently, the number of keys that the attacker can get becomes smaller.
Therefore, in order to efficiently operate the sensor network, it is important to trade energy
consumption for security. Increasing the number of keys that the node includes is difficult in SEF
because the energy of the sensor nodes is limited. To solve the problem, we use a key sequence
level scheme. The scheme helps decrease the energy consumption and make up for security.
Section 4 explains the proposed method using the key sequence level.
4. International Journal of Ambient Systems and Applications (IJASA) Vol.1, No.3,september 2013
4
4. PROPOSED METHOD
4.1. System model and assumption
A wireless sensor network consists of a BS and many sensor nodes. The BS includes a global key
pool. In the global key pool, there are all the keys which are used in the sensor network. The BS
also includes a fuzzy system that computes a key sequence level. The BS knows the average of
the key sequence level of the intermediate nodes which forward event reports in each path, the
density of neighbour nodes of the CoS, and the number of hops from the CoS to the BS. The
density of sensor nodes in the network is very high, and each node is small and each node
includes simple computing capability and limited energy.
4.2. Operation
4.2.1. Key assignment and report generation
.
Fig. 2. A global key pool which consists of j hash chains
In Fig. 2, a hash chain is made up of m keys. The last sequence key in each hash chain k j
m is a
seed key of each hash chain. The next sequence key is derived using a hash function with the seed
key.
Fig. 3. Derivation of keys using the hash function
In Fig. 3, if the hash function receives a seed key as an input, the hash function outputs the
derived key km 1 . If the hash function receives km 1 as an input, then it outputs a derived key
km 2 . This operation is repeated until the function outputs the key k1 . The derived keys are
assigned to sensor nodes before the sensor nodes are deployed in the sensor network.
5. International Journal of Ambient Systems and Applications (IJASA) Vol.1, No.3,september 2013
5
(a) (b)
Fig. 4. Example of an operation of key assignment in a global key pool (Fraction of m = 50)
Figure 4 (a) shows that just one key is randomly assigned to each sensor node v1 ~ vn . Figure 4
(b) describes an example of the keys which are assigned to the sensor nodes. The sensor nodes
derive other keys from the assigned key and a hash table. For example, In Fig. 4, a node v3
receives a key kC
19 in the C hash chain of the global key pool and then v3 can get the keys from
kC
18 to kC
1 using the hash function.
(a) (b)
(c) (d)
(e)
Fig. 5. The operation of a report generation
When an event occurs in the sensor field, multiple sensing nodes detect the event, as seen in Fig.
5 (a). The sensing nodes elect a CoS, which is a node that strongly detects the event. After the
election of the CoS, the BS forwards the key sequence level, which is determined by a fuzzy
system, to the CoS, as seen in Fig. 5 (b). The CoS forwards the key sequence level to its
neighbour nodes in Fig. 5 (c). The neighbour nodes then generate MACs using the corresponding
keys with information of the key sequence level from the CoS forwarding the MACs. A node
6. International Journal of Ambient Systems and Applications (IJASA) Vol.1, No.3,september 2013
6
which does not include the corresponding key with the key sequence level does not forward the
MAC to the CoS, as seen in Fig. 5 (d). The CoS generates an event report using its information of
the event and received MACs from the neighbour nodes. It then forwards the event report to the
next node in Fig. 5 (e, f).
4.2.2. The scheme of key sequence level
The key sequence level is a generation index of a key, which makes a MAC in the event report in
a hash chain. The key sequence levels of MACs in the event report are the same.
4.2.2.1. Elements determining a key sequence level
Fig. 6. Elements determining a key sequence level
In Fig. 6, the fuzzy system computes three input values in order to get the key sequence level
as an output value. The three input values are the density of neighbor nodes, which are located
within the sensing range of a CoS, the number of hops from the CoS to a BS, and the average of
the key sequence levels of intermediate nodes in a path.
4.2.2.1.1. Density of neighbour nodes which are located in sensing range of a CoS
The higher the density of neighbor nodes in the CoS, the more the CoS collects MACs
corresponding with the key sequence level. For example, let’s suppose the key sequence level is 6
and the number of neighbor nodes in the sensing range of the CoS is 20 or 30. In the case of 30,
the CoS collects more MACs corresponding to key sequence level 6 than in the case of 20. If the
probability of the collection of MACs is higher, although the key sequence level is high, the CoS
will collect enough MACs corresponding to the fixed number of MACs in the event report. Thus,
the higher the density, the higher the key sequence level. On the other hand, the lower the density
is, the lower the key sequence level is.
4.2.2.1.2. The number of hops from a CoS to a BS
In order to decrease the energy consumption of the sensor nodes, false reports have to be filtered
early. The more hops there are from the CoS to the BS, the more sensor nodes forward the event
report, and a great amount of energy of the sensor nodes is consumed. Therefore, when the
number of hops is large, the key sequence level has to be lower, and the report verification
probability has to be high. On the contrary, when the number of hops is small, the key sequence
level has to be high and the probability has to be lower.
4.2.2.1.3. The average number of key sequence levels of intermediate nodes in a path
The average number of key sequence levels of the forwarding node in each path is a very
important element determining the key sequence level of the event report, because when the
average of the key sequence level is high, the report verification probability becomes high, and
7. International Journal of Ambient Systems and Applications (IJASA) Vol.1, No.3,september 2013
7
when the average is lower, the probability becomes lower. Thus, the higher the average is, the
higher the probability is. On the other hand, the lower the average is, the lower the probability is.
4.2.2.1. Fuzzy membership function
(a) The number of hops from the CoS to the BS
(b) Density of neighbor nodes
in a sensing range of the CoS
(c) The average of the key sequence level of
intermediate nodes in each path
(d) Key sequence level of an event report
Fig. 7. Membership functions of input and output elements
In Fig. 7, (a) is a membership function of the number of hops from a CoS to the BS, (b) is the
membership function of the density of neighbor nodes in the sensing range of the CoS, and (c) is
a membership function of the average of the key sequence level of intermediate nodes in each
path. In the membership function (a), fuzzy values are included in the fuzzy set which consists of
three levels. The three levels are Low, Medium, and Large. In the membership functions (b) and
(c), the fuzzy values are included in the fuzzy set. The fuzzy set consists of Low, Medium, and
High. The membership function (d) is a membership function of a key sequence level of an event
report. Its fuzzy values are included in a fuzzy set. The fuzzy set is composed of KLow,
KMedium, and KHigh. In all fuzzy membership functions, the fuzzy values are in the range from
0-1.
4.2.2.1. Fuzzy rules
Table 1. Fuzzy rules of the proposed method
No.
INPUT OUTPUT
NUM_HOP NEIGHBOR_DENSITY AVERAGE_KEYLEVEL KEY_LEVEL
0 Small High High KHigh
4 Small Medium Medium KHigh
8 Small Low Low KHigh
9 Medium High High KMedium
12 Medium Medium High KMedium
15 Medium Low High KMedium
20 Large High Low KLow
22 Large Medium Medium KLow
26 Large Low Low KLow
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8
In Table1, NUM_HOP, NEIGHBORRR_DENSITY, and AVERAGE_KEYLEVEL are fuzzy
inputs. NUM_HOP is the number of hops that an event report has to pass from a CoS to a BS.
NEIGHBOR_DENSITY is density of neighbour nodes in a sensing range of the CoS.
AVERAGE_KEYLEVEL is the average of the key sequence levels for the sensor nodes in each
path. KEY_LEVEL is a fuzzy output and the key sequence level of the event report.
4.2.3. En-route filtering
Fig. 8. A flow chart of an event report verification
Once the node receives the event report, it checks whether the number of MACs in the event
report corresponds with the fixed number of MACs in the system (a). If the two number are
different, the node regards the event report as a false report and drops the it (b). Otherwise, the
node examines whether there is a corresponding partition in the event report with its partition of
MACs (c). If there is not a partition, it forwards the event report to the next node (d). If there is a
corresponding partition, the node compares the key sequence level of its key with the key
sequence level of the MACs in the corresponding partition (e). When the key sequence level is
lower than the one in the event report, it forwards the report to the next node (f). Alternatively,
when the key sequence level is the same or higher than the one in the event report, it generates a
MAC using its key and compares the MAC with the MAC of the event report (g, f). If the two
MACs are the same, it regards the event report as a legitimate node and forwards the report to the
next node (i). Otherwise, it regards the report as a false report and drops it (j).
4.2.4. Base station verification
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9
When event reports arrive at a BS, the BS will verify all the MACs in the event reports because it
includes a global key pool. If the BS receives an event report, it finds a key that corresponds to
the key sequence level of a MAC in the event report. If there is a key, the BS generates a MAC
using the key. It then compares the MAC with the MAC in the event report. If the two MACs are
not the same, the BS drops the event report. Thus, although there are false reports which are not
filtered in the en-route filtering phase, the BS verifies all false reports during this phase.
5. SIMULATION
In section 5, we compare the energy efficiency and security of our proposed method with that of
the SEF in order to evaluate the performance of the proposed method. We evaluate the energy
consumption of the sensor nodes versus the rate of false reports based on the number of
compromised nodes among the sensing nodes, which generate MACs included in an event report,
so as to compare the energy efficiency of the proposed method to that of the SEF. The number of
false reports means arrivals at the BS which are not filtered in the en-route filtering phase. We
also compared the number of false reports versus the rate of false reports in the proposed method
to that of the SEF, so as to evaluate security.
Section 5.1 describes our simulation environment. Section 5.2 presents the simulation results.
5.1. Simulation environment
Table 2. A simulation environment
Content Values
The number of the whole sensor nodes in a sensor network 600
The area of a sensor field 100m X 100m
A sensing range of a sensor node 10.0m
Energy consumption per 1byte when a sensor node sends an event report 16.25 Jμ
Energy consumption per 1byte when a sensor node receives an event report 12.5 Jμ
Energy consumption of an event report verification of a sensor node 75 Jμ
The number of hash chains in a global key pool 10
The number of MACs in an event report 5
The number of occurring event reports in a sensor network 100
The number of keys in a hash chain 50
The number of keys included in a sensor node. 25
The packet size of an event report 24bytes
5.2. Simulation results
In the simulation results, the rate of false reports is the entire number of event reports in the
sensor field versus the number of false reports. The energy consumption is the sum total of the
energy consumption of all of the sensor nodes in the sensor field.
Fig. 9 is a graph of energy consumption versus the rate of false reports in the proposed method
and the SEF method when a sensing node which generates a MAC included in the event report is
compromised.
10. International Journal of Ambient Systems and Applications (IJASA) Vol.1, No.3,september 2013
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Fig. 9. Energy consumption versus the rate of false reports
(Fraction of compromised node = 1)
In Fig. 9, we found that the proposed method consumes less energy of the sensor nodes than the
SEF method. We also found that the higher the rate of false reports, the larger the gap between
the energy consumption of the proposed method and SEF method. In the simulation result, the
proposed method consumed an average of 7.89% less energy than the SEF.
Fig. 10 is a graph of the number of false reports arriving at the BS in the proposed method and the
SEF method when a sensing node which generates a MAC included in the event report is
compromised.
Fig. 10. The number of false report versus the rate of false reports (Fraction of compromised node = 1)
In Fig. 10, we found that the number false reports arriving at the BS in the proposed method is
less than in the SEF method. In the simulation result, the number of false reports of the proposed
method is an average of 3.64 less than in the SEF method.
Fig. 11 is a graph of energy consumption versus the rate of false reports in the proposed method
and in the SEF method when the two sensing nodes which generate MACs included in the event
report are compromised.
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Fig. 11. Energy consumption versus the rate of false reports (Fraction of compromised nodes = 2)
In Fig. 11, the higher the rate of false reports is, the larger the gap between the energy
consumption of the proposed method and that of the SEF method. We also know that the
proposed method consumes less energy than the SEF. In the simulation result, the proposed
method consumed an average of 9.09% less energy than the SEF.
Fig. 12 is a graph of the number of false reports arriving at the BS in the proposed method and
that of the SEF method when two sensing node which generate MACs included in the event
report are compromised.
Fig. 12. The number of false reports versus the rate of false reports (Fraction of compromised nodes = 2)
In Fig. 12, we found that the number of false reports arriving at the BS in the proposed method is
less than that of the SEF method when the two nodes are compromised. In the simulation results,
the number of false reports is 7.66 less than that of the SEF method.
Fig. 13 is a graph of the energy consumption versus the rate of false reports in the proposed
method and that of the SEF method when three sensing nodes which generate MACs included in
the three event reports are compromised.
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Fig. 13. Energy consumption versus the rate of false reports (Fraction of compromised nodes = 3)
In Fig. 13, the proposed method consumed less energy than the SEF. The higher the rate of false
reports, the larger the gap of energy consumption is between the proposed method and the SEF
method. In the simulation result, the proposed method consumed an average of 9.26% less energy
than the SEF.
Fig. 14 is a graph of the number of false reports arriving at the BS in the proposed method and
that of the SEF method when three nodes which generate MACs included in an event report are
compromised.
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Fig. 14. The number of false reports versus the rate of false reports (Fraction of compromised nodes = 3)
In Fig. 14, we found that the number of false report arriving at the BS in the proposed method is
less than that of the SEF method. In the simulation result, the number of false reports was 9.22
less than in the SEF.
Fig. 15 is a graph of the energy consumption versus the rate of false reports in the proposed
method and in the SEF when four sensing nodes which generate MACs included in the three
event reports are compromised.
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Fig. 15. Energy consumption versus the rate of false reports (Fraction of compromised nodes =4)
In Fig. 15, when the rate of false reports is above 50%, the proposed method had better energy
efficiency than the SEF. In the simulation result, the proposed method consumed an average
5.63% less energy than the SEF.
Fig. 16 is a graph of the number of false reports arriving at the BS in the proposed method and in
the SEF when four nodes which generate MACs included in the event report are compromised.
Fig. 16. The number of false reports versus the rate of false reports (Fraction of compromised nodes = 4)
In Fig. 16, we found that the number of false report arriving at the BS in the proposed method is
less than in the SEF for all of the false reports rates. In the simulation result, the number of false
reports was 10.14 less than that of the SEF method.
In the simulation results, the proposed method was an average of 7.9% better than the SEF with
respect to energy efficiency. The number of false reports arriving at the BS in the proposed
method was an average of 6.43 less than in the SEF method. We verified that the higher the rate
of false reports in the sensor network, the better energy efficiency and security there was in the
proposed method compared to the SEF method.
6. CONCLUSION
In this paper, we proposed a solution which determines the key sequence level of MACs included
in an event report and verifies them by comparing the key sequence level of the MACs in the
event report with the key sequence level of a node which receives the event report. This is done in
order to defend energy efficiency so when the probability of a false report in the event report is
high, the event report verification probability is low, and the energy consumption of the sensor
nodes is low. On the other hand, when the key sequence level is low, the event report verification
probability is high, and energy consumption is high. Thus, it is important to determine an
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appropriate key sequence level. In order to determine the appropriate key sequence level, it is
computed by a fuzzy system in a BS. Elements determining the key sequence level are the density
of neighbor nodes in a sensing range of the CoS, the number of hops from the CoS to the BS, and
an average of the key sequence level of intermediate nodes in each path.
We evaluated the energy efficiency and security of the proposed method by comparing it to the
SEF method, which is a representative countermeasure method against the false report injection
attack. We measured the energy consumption of the sensor nodes versus the rate of false reports
in the sensor network to evaluate the energy efficiency of either the proposed method or the SEF.
Additionally, we also measured the number of false report received in the BS versus the rate of
false reports to evaluate the security of either the proposed method or the SEF. In the simulation
results, the proposed method consumed an average of 7.9% less energy of the sensor network.
Moreover the number of false reports arriving at the BS in the proposed method was an average
6.4 less than in the SEF method. It was found from the result that the proposed method has better
energy efficiency and security than the SEF when the rate of false reports is high.
ACKNOWLEDGEMENTS
This research was supported by Basic Science Research Program through the National Research
Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No.
2013R1A2A2A01013971)
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Authors
Hyum Woo Lee received his B.S. degrees in computer information from Kyungwon
University, Korea, in February 2009 and M.S degrees in in Electrical and Computer
Engineering from Sungkyunkwan University in 2013, respectively. Her research
interests include wireless sensor network, security in wireless sensor networks,
modelling & simulation, and AI.
Su Man Nam received his B.S. degrees in computer information from Hanseo
University, Korea, in February 2009 and M.S degrees in in Electrical and Computer
Engineering from Sungkyunkwan University in 2013, respectively. He is currently a
doctoral student in the College of Information and Communication Engineering at
Sungkyunkwan University, Korea. His research interests include wireless sensor
network, security in wireless sensor networks, and modelling & simulation.
Tae Ho Cho received the Ph.D. degree in Electrical and Computer Engineering from
the University of Arizona, USA, in 1993, and the B.S. and M.S. degrees in Electrical
Engineering from Sungkyunkwan University, Republic of Korea, and the University of
Alabama, USA, respectively. He is currently a Professor in the College of Information
and Communication Engineering, Sungkyunkwan University, Korea. His research
interests are in the areas of wireless sensor network, intelligent systems, modeling &
simulation, and enterprise resource planning.