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In wireless sensor networks (WSNs), the design of the energy management of the nodes and report security are important. In particular, many studies have focused on maintaining report in applications where an Internet of Things (IoT) system is connected with a WSN, with the IoT actuator operated based on measured data of WSNs. A Fuzzy-based Cluster-based False Data Filtering Scheme (FBCFFS), which can dynamically adjust security in a vulnerable network situation, maintains security using the cluster state information of the network. This scheme uses fuzzy logic, a type of rule-based expert system. The fuzzy logic system of the FBCFFS determines security strength based on network monitoring information. However, previous work with the FBCFFS has not addressed the security of the cluster information. Thus, there exists risk of data transformation at the middle transmission step in the previous approach. In addition, the node periodically transmits state information to the base station, which is inefficient in terms of network lifetime management. In this paper, we provide a method to secure the state information message and to reduce the communication cost by controlling the number of messages.

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.

An autonomous vehicle is a car that drives itself to its destination without driver intervention. Autonomous driving provides driver convenience and prevents accidents caused by driver carelessness. Autonomous vehicles recognize external environments using sensors such as cameras and riders. In addition, autonomous vehicles collect information by using vehicle-to-everything communication in places they do not recognize. During vehicle-to-everything communication, vehicle-to-infrastructure communication communicates with the infrastructure installed on the road and receives information. In other words, the autonomous vehicle receives information from the infrastructure located in an unrecognized place and grasps the road conditions. However, because infrastructure is expensive to install and maintain, technology that uses wireless sensor networks instead of infrastructure has been proposed. Since the sensor node used in the wireless sensor network is placed outside and communicates wirelessly, it is easily compromised from an attacker. Attackers can use a compromised node to attempt various attacks that affect the system, such as replay attacks. These attacks can also have a fatal effect on autonomous vehicles that use information from sensor nodes. The attacker constantly transmits false information to autonomous vehicles, causing a disruption in the driver's schedule. In addition, autonomous vehicles may cause traffic accidents due to path planning using incorrect information. The proposed scheme in this paper uses an autonomous vehicle to defend against replay attacks and detects compromised nodes. The sensor node sends a message to the base station and the autonomous vehicle to notify them when an event occurs. Thereafter, the message is transmitted to the traffic management center and the base station to be mutually verified. This paper shows that by modeling and simulating EF-ITS, it is possible to defend against replay attacks with a probability of 90% and detect compromised nodes.

A selective forwarding attack in mobile wireless sensor networks is an attack that selectively drops or delivers event packets as the compromised node moves. In such an attack, it is difficult to detect the compromised node compared with the selective forwarding attack occurring in the wireless sensor network because all sensor nodes move. In order to detect selective forwarding attacks in mobile wireless sensor networks, a fog computing-based system for a selective forwarding detection scheme has been proposed. However, since the proposed detection scheme uses a single path, the energy consumption of the sensor node for route discovery when the sensor node moves is large. To solve this problem, this paper uses fuzzy logic to determine the number of multi-paths needed to improve the energy efficiency of sensor networks. Experimental results show that the energy efficiency of the sensor network is improved by 9.5737% compared with that of the existing scheme after 200 seconds when using the proposed scheme.

Wireless Sensor Network (WSN), there are low capacity, low cost, tiny sensor nodes, and sinks. Sensor nodes detect an event occurring in its surroundings and send data about the event to the sink. Sensor nodes have a limited transmission range and computational power. Since the wireless sensor network operates with limited resources than the ad hoc network, it is difficult to apply the defense method as it is, so research on a new defense method is needed. In a WSN, sensor nodes manage, monitor, and collect data for a specific environmental and physical application, and the collected data is transmitted to and used by a base station. Base stations are connected via the Internet and share data with users. Since the sensor node is composed of low power and low capacity, it is mainly used in an unattended environment, so it is easily exposed to various attacks and can be damaged. This type of network makes it difficult to detect wormhole attacks when they occur along with other attacks like false report injection attacks and Sybil attacks. Therefore, to prevent this, in this study, the hop count and the encrypted node ID are added in the report generation process of the statistical en-route filtering technique to detect wormhole attacks even when a wormhole attack occurs along with a false report injection attack to improve security.

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.

Wireless sensor networks are widely deployed and implicitly characterized by stringent energy and computation constraints. Sensor nodes are vulnerable to false positive and false negative attacks that inject false data through compromised nodes. Such attacks cause false alarms with energy drain and information loss. Although several en-route filtering schemes have been designed to detect the attacks, they focus on saving energy through early filtering or continuous delivery of data in accordance with verification records; they cannot exclude compromised nodes. In this paper, we propose a scheme that effectively identifies the compromised nodes and copes with new attacks using a context-aware architecture. In addition, the proposed scheme improves the security strength and energy efficiency of the network. Simulation results validate that the proposed scheme provides energy savings of up to 45 percent and allows fewer attack successes than the existing scheme.

Wireless sensor networks (WSNs) have unprecedented environment-monitoring capabilities with low cost, small size, and limited energy. In security protocols, the general approach for energy efficiency is to reduce the number of attacks while underlying routing protocols are often ignored. In this paper, we present an energy-aware routing and filtering node (ERF) selection to extend network lifetime in commutative cipher-based en-route filtering (CCEF). In addition to distance to the destination, the residual energy is considered for forwarding node selection. In a given path, filtering nodes are carefully selected based on attack information, presence of witness key (), and current state of a node in sensor network. Results demonstrate the validity of our simple approach to significantly prolong the network lifetime by balancing network energy consumption.

In wireless sensor networks (WSNs), the energy and computational capacity of the sensor nodes are limited and they are deployed in a hostile environment. An adversary can easily compromise a sensor node and injects false data into the network. This injection of false data drastically depletes the energy of the nodes designated on the route for forwarding the source data. Many filtering methods have been proposed to tackle the security issues but they also increase the communication cost by exchanging the control keying messages which consumes more energy with in the network. Fuzzy logic for TICK was proposed to reduce the communication cost and increase the energy efficiency of the en-route nodes by selecting the re-encrypting nodes efficiently and avoiding the exchange of control keying messages in the network. Membership functions in the fuzzy system need to be optimized in order to use the fuzzy inferencing more efficiently. We propose an optimized fuzzy membership functions method by using genetic algorithm. The genetic algorithm determines the optimal membership functions which help in selecting the most favourite re-encrypting nodes in TICK based wireless sensor network. Simulation results show that the proposed method optimizes the membership functions and achieves better energy conservation at sensor nodes.

In Wireless Sensor Networks, sensor nodes are highly vulnerable to several security attacks because they are usually installed in hostile environments. These energy and hardware-resource-constrained nodes, without suitable safeguards, may be compromised by adversaries. Adversaries launch two major types of attacks: false-report injection and false-vote injection attacks via these compromised nodes. These attacks drain significant amounts of energy and drop valid reports. PVFS11Probabilistic voting-based filtering scheme by F. Li et al. 1 counters these two major attacks. One of the reasons to launch false-report injection attack is to drain the energy resource of the entire network to render it unresponsive. We propose Fuzzy-based adaptive selection of the intermediate verification nodes in PVFS to achieve optimal energy savings. We demonstrate that our proposed method achieves better energy conservation in the presence of both the aforementioned security threats while providing the same high filtering control of the PVFS.

Wireless sensor networks are vulnerable to an adversary due to scarce resources and wireless communication. An adversary can compromise a sensor node and launch a variety of attacks such as false report injection attacks. This attack may cause monetary damage resulting in energy drain by forwarding the false reports and false alarms at the base station. In order to address this problem, a number of en-route filtering schemes has been proposed. Notably, a dynamic en-route filtering scheme can save energy by filtering of the false report. In the key dissemination phase of the existing scheme, the nodes closer to the source node may not have matching keys to detect the false report. Therefore, continuous attacks may result in unnecessary energy wastage. In this paper, we propose a key re-distribution scheme to solve this issue. The proposed scheme early detects the false report injection attacks using initially assigned secret keys in the phase of the key pre-distribution. The experimental results demonstrate the validity of our scheme with energy efficiency of up to 26.63% and filtering capacity up to 15.92% as compared to the existing scheme.Key Words : Wireless Sensor Network, False Report Injection Attack, Dynamic En-route Filtering Scheme, Key Re-distribution이 논문은 2015년도 정부(미래창조부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(No. NRF-2013R1A2A2A01013971).This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Most devices in the Internet of Things (IoT) utilize WiMAX communication, and Femtocells are used to provide reliable communication by eliminating shaded areas where wireless signals become weaker with distance and underground facilities. One downfall of this method is the possibility of eavesdropping through Man-in-the-Middle attacks. Forced latency interlock protocol is used to detect these attacks. This protocol uses a fixed latency value and does not consider packet size and distance. In this paper, we propose a dynamic delay time decision method for reducing the fixed delay time of the forced latency interlock protocol in wireless communications based on the IoT. The evaluation function considers the distance between the device, the packet size, and the bit rate of the broadband internet. The simulation experiments demonstrate the validity of our method, which reduces delay time by an average of 88.19% and increases detection rate by an average of 7.97%.

Wireless sensor networks are supplied with limited energy resource, deployed in hostile environments, and use wireless communication. Thus, sensor nodes are prone to failure, which makes the network topology configurations highly dynamic in real world application. This vulnerability means that an attacker can easily compromise a node to inject false report and launch DoS attacks. A number of en-route filtering schemes have been proposed to drop and defeat these attacks using their own cryptographic methods. Some of them ask for a fixed path between base station and each cluster, so they are not feasible for dynamic network. And the others, they do not consider various environment variables in dynamic environment, so they only choose static paths. By contrast, we consider topology changes, communication cost, maximum number of key dissemination hops, and the spread of nodes for providing optimum filtering capacity. This paper presents an adaptive multipath selection method using fuzzy logic for the en-route filtering schemes in dynamic environment of wireless sensor network. Our proposed method can adjust optimized the number of multipath in key dissemination. Experimental results show that compared to existing solutions, our method can achieve higher filtering capacity with lower energy consumption, as well as choose more suitable nodes for highly dynamic networks.

Wireless sensor networks are characterized by stringent energy and computation constraints. They are often deployed in hostile environments and are left unattended for long periods of time without recharging. These sensor nodes can be compromised by adversaries who launch network layer attacks, such as sinkhole attacks, in which a compromised node is disguised as a base station and all packets forwarded to it are exposed to attackers. A localized encryption and authentication protocol (LEAP) observes the different types of the packets exchanged between the sensors to cope with the attacks. Although this method performs well for securing communication using multiple keys, the data is transmitted without consideration of efficient routing paths to limit energy consumption. Our proposed method selects the next forwarding node to allow an efficient path setup for the packet routing based on a fuzzy logic system. Experimental results indicate that the proposed method provides energy savings of up to 10% while maintaining the same level of security against sinkhole attacks compared to the existing method.

Balancing energy usage over a larger group of participating nodes in a sensor network extends the network's lifetime. Security protocols mainly focus on saving energy through early filtering of attacks; however, this does not necessarily prolong the network lifetime. In order to save more energy and extend the network lifetime, the underlying routing is equally important. Security protocols such as commutative cipher en-route filtering (CCEF), which considers shortest path routing, do not take advantage of the opportunity to save more energy by considering an energy efficient underlying routing at the design level. In this paper, we propose pre-deterministic key-distribution based CCEF (PKCCEF), which extends the network life significantly through pre-deterministic and random distribution of the witness keys with a modified underlying routing that considers the residual energy. For high FTR, our method selects a path with more filtering nodes to be able to detect more attacks. This needs further verification for legitimate reports and needs more energy as compared to original method, but it can save energy by filtering fabricated or false report earlier. For low FTR, our method selects an energy efficient path with fewer verifications of legitimate reports. Independent of the number of attacks, our method extends the network lifetime as compared to the original method i.e. CCEF. Our method achieves energy efficiency without compromising the security of the original scheme. The results show the effectiveness of the proposed method in terms of the energy efficiency (up to 16.05 %) and extending the network lifetime (up to 84.01 %).

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 them into the network. This causes unnecessary energy consumption associated with the process of transmitting false alarm messages and false data reports to the system. If the attacker keeps repeatedly attacking, the attacks will cause problems such as a reduction in the entire network life or disabling of the networks. Yu and Guan proposed a dynamic en-route filtering scheme to detect and drop these false reports before they reach the base station. In 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 its report information. The base station is able to find the cluster of compromised nodes using that information. In particular, by knowing 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 allow attackers to inject false reports by compromising sensor nodes due to the use of wireless communication, the limited energy resources of the sensor nodes, and deployment in an open environment. The forwarding of false reports causes false alarms at the Base Station and consumes the energy of the sensor nodes unnecessarily. As a defense against false report injection attacks, interleaved hop-by-hop authentication was proposed. In interleaved hop-by-hop authentication, the security threshold is a design parameter that influences the number of Message Authentication Codes; the sensor nodes must verify, based on the security requirements of the application and the node density of the network. However, interleaved hop-by-hop authentication fails to defend against false report injection attacks when the number of compromised sensor nodes exceeds the security threshold. To solve this problem, in this paper we propose a security scheme that adjusts the security threshold according to the network situation using an evaluation function. The proposed scheme minimizes the energy consumption of the sensor nodes and reinforces security.

Wireless sensor networks are supplied with limited energy resources and are usually installed in unattended and unfriendly environments. These networks are also highly exposed to security attacks aimed at draining the energy of the network to render it unresponsive. Adversaries launch counterfeit report injection attacks and false vote injection attacks through compromised sensor nodes. Several filtering solutions have been suggested for detecting and filtering false reports during the multi-hop forwarding process. However, almost all such schemes presuppose a conventional underlying protocol for data routing that do not consider the attack status or energy dissipation on the route. Each design provides approximately the equivalent resilience in terms of protection against compromised node. However, the energy consumption characteristics of each design differ. We propose a fuzzy adaptive path selection to save energy and avoid the emergence of favored paths. Fresh authentication keys are generated periodically, and these are shared with the filtering nodes to restrict compromised intermediate filtering nodes from the verification process. The scheme helps delay the emergence of hotspot problems near the base station and exhibits improved energy conserving behavior in wireless sensor networks. The proposed scheme provides an extended network lifetime and better false data filtering capacity.

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.

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.

In a large-scale wireless sensor network, damage spreads rapidly in the network when under false report injection, false votes injection, or wormhole attacks. These attacks cause finite energy resources to be drained, legitimate reports to be dropped, and data to be intercepted by adversary nodes. A probabilistic voting-based filtering scheme (PVFS) and localized encryption and authentication protocol (LEAP) can be used to cope with these attacks. When multiple attacks occur simultaneously, PVFS and LEAP should be operated together. But the concurrent application of PVFS and LEAP provides inefficient duplications of operations in the sensor network. In this paper, we propose a security method which improves the energy efficiency while maintaining the security level of applying PVFS and LEAP simultaneously. The proposed method was designed by identifying and eliminating the redundancies of employing both methods together and providing more efficient functionalities. Four types of new keys were also designed for simultaneous detection of multiple attacks. We evaluated the effectiveness of the proposed method compared to simply applying PVFS and LEAP simultaneously when under multiple attacks. The experimental results demonstrate that our proposed method saves energy by up to 11% while maintaining detection power.

Sensor nodes are easily compromised by attacker when which are divided in open environment. The attacker may inject false report and false vote attack through compromised sensor node. These attacks interrupt to transmission legitimate report or the energy of sensor node is exhausted. PVFS are proposed by Li and Wu for countermeasure in two attacks. The scheme use inefficiency to energy of sensor node as fixed report threshold and verification node. In this paper, our propose the next neighbor node selection scheme based on fuzzy logic system for energy improvement of PVFS. The parameter of fuzzy logic system are energy, hops, verification success count, CH select high the next neighbor node among neighbor nodes of two as deduction based on fuzzy logic system. In the experimental, our proposed scheme was improvement to energy of about 9% compare to PVFS. Key words : Wireless sensor network, Probabilistic voting-based filtering scheme, Fuzzy logic system요 약무선 센서 네트워크에서 센서 노드들은 개방된 환경에 배치되기 때문에 공격자들을 통해 쉽게 훼손된다 . 공격자는 훼손된 노드를 통해 허위 보고서 및 허위 투표 주입 공격을 할 수 있다 . 이러한 공격은 센서 노드의 에너지를 고갈시키거나 정상 보고서의 전송을 막는다 . 이 두 가지 공격에 대응하기 위해 Li와 Wu는 확률적 투표 기반 여과 기법을 제안하였다 . 이 기법은 보고서 임계값과 검증 노드를 고정적으로 사용하기 때문에 센서 노드의 에너지를 비효율적으로 사용한다 . 본 논문에서는 PVFS의 에너지 향상을 위해 퍼지 로직 시스템을 기반으로 다음 이웃 노드 선택 방법을 제안한다 . 퍼지 로직 시스템의 매개변수들은 에너지, 홉의 수, 검증 성공 횟수이며, CH는 퍼지 로직 시스템을 기반으로 도출된 2개의 이웃 노드 중에서 상태 정보가 높은 다음 이웃 노드를 선택한다 . 실험을 통해 제안 기법은 기존 기법과 비교하여 약 9%의 에너지가 향상되었고, 센서 노드들의 에너지 절감을 통해 전체 네트워크의 수명 연장을 기대한다 .주요어

An adversary can easily compromise sensor nodes in wireless sensor networks, and generate multiple attacks through compromised nodes, such as false vote injection attacks and false report injection attacks. The false vote injection attack tries to drop legitimate reports in an intermediate node, and the false report injection attack tries to drain the energy consumption of each node. To prevent these attacks, a probabilistic voting-based filtering scheme (PVFS) has been proposed to select verification nodes, and to detect fabricated votes in the reports as they occur simultaneously. In this paper, we propose a method that improves the energy efficiency of each node and thesecurity level of the false report injection attack, while maintaining the detection power of the false vote injection attack. Our proposed method effectively selects verification node with considering the conditions of each node, based on a fuzzy rule -based system. The verification node is decided through the energy remaining level, distance level, and number of detected false votes in the fuzzy system. We evaluated the effectiveness of the proposed method, as compared to PVFS, when two attacks occur simul taneously in the sensor network. The experimental results show that our method saves energy by up to 8%, by improving and maintaining the defence against these multiple attacks.

Wireless sensor networks (WSNs) consist of a large number of sensor nodes that monitor the environment and a few base stations that collect the sensor readings. Individual sensor nodes are subject to compromised security because they may be deployed in hostile environments and each sensor node communicates wirelessly. An adversary can inject false reports into the networks via compromised nodes. Furthermore, an adversary can create a wormhole by directly linking two compromised nodes or using out-of-band channels. If these two kinds of attacks occur simultaneously in a network, existing methods cannot defend against them adequately. We thus propose a secure routing method for detecting false report injections and wormhole attacks in wireless sensor networks. The proposed method uses ACK messages for detecting wormholes and is based on a statistical en-route filtering (SEF) scheme for detecting false reports. Simulation results show that the proposed method reduces energy consumption by up to 20% and provide greater network security.

Routing paths are mightily important for the network security in WSNs. To maintain such routing paths, sustained path re-selection and path management are needed. Region segmentation based path selection method (RSPSM) provides a path selection method that a sensor network is divided into several subregions, so that the regional path selection and path management are available. Therefore, RSPSM can reduce energy consumption when the path re-selection process is executed. However, it is hard to guarantee optimized secure routing path at all times since the information using the path re-selection process is limited in scope. In this paper, we propose partial path selection method in each subregion using preselected partial paths made by RSPSM for routing path optimization in SEF based sensor networks. In the proposed method, the base station collects the information of the all partial paths from every subregion and then, evaluates all the candidates that can be the optimized routing path for each node using a evaluation function. After the evaluation process is done, the result is sent to each super DN using the global routing path information (GPI) message. Thus, each super DN provides the optimized secure routing paths using the GPI. We show the effectiveness of the proposed method via the simulation results. We expect that our method can be useful for the improvement of RSPSM.

Sensor networks are vulnerable to many attacks because the sensor networks operate in open environments. It is easy to incur one or more attacks such as a selective forwarding attack, a false report injection attack. It is hard to defend the sensor network from the multiple attacks through existing security methods. Thus, we suggest an energy-efficient security method in order to detect the multiple attacks. This paper presents a security method to detect the false report injection attack and the selective forwarding attack in the sensor network using a new message type. The message type is a filtering message. The filtering message prevents from generating and forwarding false alert messages. We evaluated performance of our proposed method through a simulation in comparison with an application of SEF (statistical enroute filtering scheme) and CHEMAS (Check point-based Multi-hop Acknowledgement Scheme). The simulation results represent that the proposed method is 10% more energy-efficient than the application when the number of false reports is great while retaining the detection performance.

Wireless sensor networks (WSNs) are networked systems that are able to sense various events and report the events to a user to enable appropriate responses. One of security threats to a WSN is false data injection attacks in which an attacker steals some sensor nodes in the network and injects forged event messages into the network through the captured nodes. As a result, the intermediate nodes on the forwarding paths of the false event messages waste their limited energy. Additionally, the network cannot provide the user with correct information. There have been many studies on en-route detection of false event messages for WSNs. Yang et al. proposed the commutative cipher-based en-route filtering scheme (CCEF) which establishes a secure session between a sink node and a cluster head (CH) based on the commutative cipher. In CCEF, each intermediate node on the path between the sink node and the CH receives an event message and verifies the authenticity of the session based on a probability. Due to the probabilistic approach, it is hard to adapt to the change of false traffic ratio in the network and energy inefficiency may occur. We propose a filtering scheme which applies a deterministic approach to assign filtering nodes to a given session. The proposed method consumes less energy than that of CCEF without sacrificing security.

Sensor nodes are easily exposed to malicious attackers by physical attacks. The attacker can generate various attacks using compromised nodes in a sensor network. The false report generating application layers injects the network by the compromised node. If a base station has the injected false report, a false alarm also occurs and unnecessary energy of the node is used. In order to defend the attack, a statistical en-route filtering method is proposed to filter the false report that goes to the base station as soon as possible. A path renewal method, which improves the method, is proposed to maintain a detection ability of the statistical en-route filtering method and to consume balanced energy of the node. In this paper, we proposed the secure path cycle method to consume effective energy for a path renewal. To select the secure path cycle, the base station determines through hop counts and the quantity of report transmission by an evaluation function. In addition, three methods, which are statistical en-route filter, path selection method, and path renewal method, are evaluated with our proposed method for efficient energy use. Therefore, the proposed method keeps the secure path and makes the efficiency of energy consumption high.

Wireless sensor nodes operate in open environments. The deployed sensor nodes are very vulnerable to physical attacks from outside. Attackers compromise some sensor nodes. The compromised nodes by attackers can lead to false data injection into sensor networks. These attacks deplete the limited energy of sensor nodes. Ye et al. proposed the Statistical En-Route Filtering (SEF) as a countermeasure of the attacks. The sensor node in SEF examines the event reports based on certain uniform probability. Thus, the same energies are consumed in both legitimate reports and false reports. In this paper, we propose a method that each node controls the probability of attempts to verify a report to reduce energy consumption of sensor nodes. The probability is determined in consideration of the remaining energy of the node, the number of hops from the node to SINK node, the ratio of false reports. the proposed method can have security which is similar with SEF and consumes lower energy than SEF.

Sensor nodes are easily compromised to malicious attackers due to an open environment. A false injected attack which takes place on application layer is elected by the compromised node. If the false report arrives in a base station, a false alarm is occurred, and the energy of the nodes is consumed. To detect the false report, statistical en-route filtering method is proposed. In this paper, we proposed the secure path cycle selection method using fuzzy rule-based system to consume effective energy. The method makes balanced energy consumption of each node. Moreover, the lifetime of the whole network will be increased. The base station determines the path cycle using the fuzzy rule-based system. The performance of the proposed method is demonstrated using simulation studies with the three methods.

A compromised node can generate a fabricated report, which results in false alarms, information loss, and a waste of precious network energy. An interleaved hop-by-hop authentication (IHA) scheme has been proposed to minimize such serious damage by detecting and filtering false reports at the very early en-route nodes. Unfortunately, IHA, with a single path from the source to the BS, cannot keep its security goal if more than t intermediate nodes are compromised. In this paper, an enhanced multi-path interleaved hop-by-hop authentication (MIHA) scheme is proposed. MIHA sets up disjoint and braided paths and switches to alternate paths when there is more than t compromised nodes on the current path to continue dealing with en-route insider attacks. A new key assignment mechanism was also applied to enhance network security and to reduce key storage overhead. Through analysis and simulations, MIHA exhibits improved resilience to en-route insider attacks and filters more bogus reports at early hops than IHA. Specially, with an attack frequency of 1/15 and a false traffic rate of more than 60%, MIHA with three disjoint paths can filter over 27% of false reports and is more energy efficient when compared to IHA.

In wireless sensor networks, adversaries can easily launch application layer attacks, such as false data injection attacks and false vote insertion attacks. False data injection attacks may drain energy resources and waste real world response efforts. False vote insertion attacks would prevent reporting of important information on the field. In order to minimize the damage from such attacks, several prevention based solutions have been proposed by researchers, but may be inefficient in normal condition due to their overhead. Thus, they should be activated upon detection of such attacks. Existing detection based solutions, however, does not address application layer attacks. This paper presents a scheme to adaptively counter false data injection attacks and false vote insertion attacks in sensor networks. The proposed scheme consists of two sub-units: one used to detect the security attacks and the other used to select efficient countermeasures against the attacks. Countermeasures are activated upon detection of the security attacks, with the consideration of the current network status and the attacks. Such adaptive countering approach can conserve energy resources especially in normal condition and provide reliability against false vote insertion attacks.

In sensor networks, a compromised node can either generate fabricated reports with false votes or inject false votes into real reports, which causes severe damage such as false alarms, energy drain and information loss. An interleaved hop-by-hop authentication (IHA) scheme addresses the former attack by detecting and filtering false reports in a deterministic and hop-by-hop fashion. Unfortunately, in IHA, all en-route nodes must join to verify reports while only a few are necessary to the authentication procedure. In this paper, we propose a fuzzy-based interleaved multi-hop authentication scheme based on IHA. In our scheme, the fuzzy logic system only selects some nodes for verification based on the network characteristics. Moreover, we apply a voting method and a hash-based key assignment mechanism to improve network security. Through performance evaluation, the proposed scheme is found to save up to 13% of the energy consumption and to provide more network protection compared to IHA.

The application of wireless sensor networks to areas such as combat field surveillance, terrorist tracking and highway traffic monitoring requires secure communication among the sensor nodes within the networks. Logical key hierarchy (LKH) is a tree-based key management model which provides secure group communication. When a sensor node is added or evicted from the communication group, LKH updates the group key in order to ensure the security of the communications. In order to efficiently update the group key, we propose an A^*-based key tree structure, an extension to LKH, that reduces the number of re-key messages by considering the addition and eviction ratios of the history data. For the generation of the proposed key tree structure the A^* algorithm is applied, in which the branching factor at each level can take on different value. The experimental results demonstrate the efficiency of the proposed key tree structure against the existing key tree structures of fixed branching factors.

Security in sensor networks is a major issue. Sensor networks use symmetric cryptography protocol since sensor nodes have resource constrained hardware. Such netowrks are also deployed in hostile environments. Therefore, an attacker can get all information after any nodes get compromised. The adversary can inject false sensing reports or false Message Authentication Codes into real reports. A probabilistic voting-based filtering scheme is proposed but in several cases it is inefficient in terms of energy consumption and filtering effectiveness. We proposed a new method that uses a decision function regardless of whether each forwarding node executes a verification process. Through performance analysis and simulation, our result shows that the proposed method is much more efficient than the probabilistic voting-based scheme in many cases.

The paper describes the design and implementation of a security architecture for a coordination information system constructed by blackboard architecture (BBA). The need arises for systems to coordinate with one another, to manage diverse attacks across networks and time. The coordination issue is the essential problem since it is beyond the scope of any one intrusion detection system (IDS) to deal with the intrusions. This paper shows a modeling and simulation of network security in which the multiple IDSes and a firewall coordinate by sharing attacker’s information for the effective detection of the intrusion. Another characteristic in the proposed simulation is the composition of a real intrusion by generating non-abstracted intrusion packets and, accordingly, the construction of non-abstracted version of IDS and firewall model components that are closely related to the intrusion packets.

In wireless sensor networks, sensors have stringent energy and computation requirements as they must function unattended. The sensor nodes can be compromised by adversaries who attack network layers such as in sinkhole attacks. Sinkhole attacks have the goal of changing routing paths and snatching data surrounding the compromised node. A localized encryption and authentication protocol (LEAP) observes different types of messages exchanged between sensors that have different security requirements to cope with the attack. Even though this original method excels in security communication using multiple keys, the data is transmitted without optimal selection of the next nodes. In this paper, our proposed method selects the optimal next node based on a fuzzy logic system. We evaluated the energy and security performances of our method against sinkhole attack. Our focus is to improve energy efficiency and maintain the same security level as compared to LEAP. Experimental results indicated that the proposed method saves up to 5 % of the energy while maintaining the security level against the attack as compared to LEAP.

Because of the features such as limited resources, wireless communication and harsh environments, wireless sensor networks (WSNs) are prone to various security attacks. Therefore, we need intrusion detection and prevention methods in WSNs. When the two types of schemes are applied, heavy communication overhead and resulting excessive energy consumption of nodes occur. For this reason, we propose an energy efficient routing method in an environment where both intrusion detection and prevention schemes are used in WSNs. We confirmed through experiments that the proposed scheme reduces the communication overhead and energy consumption compared to existing schemes.

In wireless sensor networks, adversaries can harm the sensor nodes by launching attacks such as the false report injection and the false vote injection. These attacks drain finite energy resources and drop legitimate event information in the sensor network. A probabilistic voting-based filtering scheme (PVFS) detects fabricated votes at the verification cluster-heads (CHs) while forwarding event reports. This paper presents a genetic algorithm-based PVFS to select effective verification CHs before transmitting the reports from a source CH. The proposed method determines the verification CHs based on the remaining energy level, the number of filtered votes, and the hop counts. The effectiveness of the proposed method is evaluated against the original PVFS in case of simultaneous multiple attacks. Our experimentation results indicated that the method results in an energy saving of approximately 10% and improves security against false report injection attacks and false vote injection attacks by 7% and 20%, respectively.