On-off Attacks Research Articles

A fuzzy security protocol for trust management in the internet of things (Fuzzy-IoT)

Recently, the Internet of things (IoT) has received a lot of attention from both industry and academia. A reliable and secure IoT connection and communication is essential for the proper working of the IoT network as a whole. One of the ways to achieve robust security in an IoT network is to enable and build trusted communication among the things (nodes). In this area, the existing IoT literature faces many critical issues, such as the lack of intelligent cluster-based trust approaches for IoT networks and the detection of attacks on the IoT trust system from malicious nodes, such as bad service providers. The existing literature either does not address these issues or only addresses them partially. Our proposed solution can firstly detect on-off attacks using the proposed fuzzy-logic based approach, and it can detect contradictory behaviour attacks and other malicious nodes. Secondly, we develop a fuzzy logic-based approach to detect malicious nodes involved in bad service provisioning. Finally, to maintain the security of the IoT network, we develop a secure messaging system that enables secure communication between nodes. This messaging system uses hexadecimal values with a structure similar to serial communication. We carried out extensive experimentation under varying network sizes to validate the working of our proposed solution and also to test the efficiency of the proposed methods in relation to various types of malicious behavior. The experiment results demonstrate the effectiveness of our approach under various conditions.

Detection of selective forwarding attacks based on adaptive learning automata and communication quality in wireless sensor networks

Wireless sensor networks face threats of selective forwarding attacks which are simple to implement but difficult to detect. It is difficult to distinguish between malicious packet dropping and the normal packet loss on unstable wireless channels. For this situation, a selective forwarding attack detection method is proposed based on adaptive learning automata and communication quality; the method can eliminate the impact of normal packet loss on selective forwarding attack detection and can detect ordinary selective forwarding attack and special cases of selective forwarding attack. The current and comprehensive communication quality of nodes are employed to reflect the short- and long-term forwarding behaviors of nodes, and the normal packet loss caused by unstable channels and medium-access-control layer collisions is considered. The adaptive reward and penalty parameters of a detection learning automata are determined by the comprehensive communication quality of the node and the voting of its neighbors to reward normal nodes or punish malicious ones. Simulation results indicate the effectiveness of the proposed method in detecting ordinary selective forwarding attacks, black-hole attacks, on-off attacks, and energy exhaustion attacks. In addition, the communication overhead of the method is lower than that of other methods.

A Smart Trust Management Method to Detect On-Off Attacks in the Internet of Things

Internet of Things (IoT) resources cooperate with themselves for requesting and providing services. In heterogeneous and complex environments, those resources must trust each other. On-Off attacks threaten the IoT trust security through nodes performing good and bad behaviors randomly, to avoid being rated as a menace. Some countermeasures demand prior levels of trust knowledge and time to classify a node behavior. In some cases, a malfunctioning node can be mismatched as an attacker. In this paper, we introduce a smart trust management method, based on machine learning and an elastic slide window technique that automatically assesses the IoT resource trust, evaluating service provider attributes. In simulated and real-world data, this method was able to identify On-Off attackers and fault nodes with a precision up to 96% and low time consumption.

A dynamic trust evolution model for MANETs based on mobility

Mobile ad-hoc networks (MANETs) are said to be open, anonymous, dynamic and mobile in nature which makes them vulnerable to several types of attacks. Mobility of a node is a source of vulnerability and raises challenges in setup and maintenance of secure and reliable communication. We propose here a trust model that enables a node in a network to assess confidence in its immediate and extended neighbourhood. We derive a trust parameter Mobility Factor to assess node's mobility. The effects of mobility are included as a parameter in the trust evaluation. Proposed trust assessment allows identification of node's capricious behaviour using the concept of trust flutter. A formal proof is presented here supports the adequacy of the proposed approach. ns-2 simulations with mobility and malicious nodes show better performance of proposed approach as compared to recent work (TSR (Lia et al., 2013)). Improved resilience against packet-dropping/modification attack and on-off attacks was observed.

On Mitigating On-Off Attacks in Wireless Sensor Networks

On Mitigating On-Off Attacks in Wireless Sensor Networks

Communication and Data Trust for Wireless Sensor Networks Using D–S Theory

Wireless sensor networks (WSNs) are usually deployed in insecure remote and open environments. Nodes could be attacked and compromised. The attacker can use compromised sensor nodes to disrupt communications or inject misleading sensor values. Misleading data can corrupt the entire decision making process, which depends upon WSN data. We propose a trust mechanism, which evaluates communication trust and data trust for WSNs. Communication trust is computed from direct and indirect observations of the neighbour's forwarding behavior. Direct trust is derived from the consistency of forwarding behavior. Indirect trust is derived from the neighbour's observations translated into recommendations. We use weighted Dempster-Shaffer (D-S) theory to compute indirect trust. Data trust is computed by using median of sensor data. We present arguments and simulation results to show the effectiveness of the proposed algorithm against packet forwarding/modification attacks, bad mouthing attacks, collusion attacks, and on-off attacks. Our proposed trust model helps data in WSNs to be more secure.

REPLACE: A Reliable Trust-Based Platoon Service Recommendation Scheme in VANET

The fast development of intelligent transportation has paved the way for innovative techniques for highways, and an entirely new driving pattern of highway vehicular platooning might offer a solution to the persistent problem of road congestion, travel comfort, and road safety. In this vehicular platooning system, a platoon head vehicle provides platoon service to its user vehicles. However, some badly behaved platoon head vehicles may put the platoon in danger, which makes it crucial for user vehicles to distinguish and avoid them. In this paper, we propose a reliable trust-based platoon service recommendation scheme, which is called REPLACE, to help the user vehicles avoid choosing badly behaved platoon head vehicles. Specifically, at the core of REPLACE, a reputation system is designed for the platoon head vehicles by collecting and modeling their user vehicle's feedback. Then, an iterative filtering algorithm is designed to deal with the untruthful feedback from user vehicles. A detailed security analysis is given to show that our proposed REPLACE scheme is secure and robust against badmouth, ballot-stuffing, newcomers, and on-off attacks that exist in vehicular ad hoc networks (VANETs). In addition, we conduct extensive experiments to demonstrate the correctness, accuracy, and robustness of our proposed scheme.

Mitigate Lying and On-Off Attacks on Trust Based Group Key Management Frameworks in MANETs

Instant collaborative group communication can be achieved by deploying Mobile Ad Hoc Networks (or MANETs) without any pre-plan and pre-existing infrastructure setup. However, the curbs thrown by these networks, motivate the necessity of a group key management framework to secure data traffic. In this context, significant research work done in the last decade and proved that the trust based frameworks deliver better performance than others. In MANETs, trust quantified as the belief held by a node about another node. It is evaluated based on the assessing node direct experiences with assessed node itself, if they are neighbors and recommendations from remote nodes in the network with which assessed node has a direct experience, if they are remote. However, the framework based on recommendations by other nodes in the network might ultimately lead to system failure due to the menace of unfair recommendations by selfish and malicious nodes. Lying and on-off attacks on the system are such type of attacks. This motivates us to work on a framework which is immune to aforesaid attacks and should be lightweight due to node's has limited computing resources. We propose a framework which scrutinizes dishonest recommendations based on the trust threshold value of remote nodes, distance from mean of trust recommendations and by maintaining a history of recommendations. Our simulation outcomes prove that proposed framework can deliver better network performance and resistance to lying and on-off attacks.

DTSRS: A Dynamic Trusted Set based Reputation System for Mobile Participatory Sensing Applications

Participatory sensing is an emerging paradigm in which citizens voluntarily use their mobile phones to capture and share sensed data from their surrounding environment in order to monitor and analyze some phenomena (e.g., weather, road traffic, pollution, etc.). Participating users can disrupt the system by contributing corrupted, fabricated, or erroneous data. Different reputation systems have been proposed to monitor participants' behavior and to estimate their honesty. There are some attacks that were not considered by the existing reputation systems in the context of participatory sensing applications including corruption, collusion, and on-off attack. In this paper, we propose a more robust and efficient reputation system designed for these applications. Our reputation system incorporates a mechanism to defend against those attacks. Experimental results indicate that our system can accurately estimate the quality of contributions even if collusion is committed. It can tolerate up to 60% of colluding adversaries involved in the sensing campaign. This enables our system to aggregate the data more accurately compared with the state-of-the art. Moreover, the system can detect adversaries even if they launch on-off attack and strategically contribute some good data with high probability (e.g. 0.8).

A Dynamic Trust Evolution Model for MANETs based on Mobility

Mobile ad-hoc networks (MANETs) are said to be open, anonymous, dynamic and mobile in nature which makes them vulnerable to several types of attacks. Mobility of a node is a source of vulnerability and raises challenges in setup and maintenance of secure and reliable communication. We propose here a trust model that enables a node in a network to assess confidence in its immediate and extended neighbourhood. We derive a trust parameter Mobility Factor to assess node's mobility. The effects of mobility are included as a parameter in the trust evaluation. Proposed trust assessment allows identification of node's capricious behaviour using the concept of trust flutter. A formal proof is presented here supports the adequacy of the proposed approach. ns-2 simulations with mobility and malicious nodes show better performance of proposed approach as compared to recent work (TSR (Lia et al., 2013)). Improved resilience against packet-dropping/modification attack and on-off attacks was observed.

Mitigating On-Off Attacks in the Internet of Things Using a Distributed Trust Management Scheme

In the Internet of Things (IoT), physical objects are able to provide or require determined services. The purpose of this work is to identify malicious behavior of nodes and prevent possible On-Off attacks to a multiservice IoT. The proposed trust management model uses direct information generated from direct communication with the nodes to evaluate trust between nodes. This distributed approach allows nodes to be completely autonomous in making decisions about the behavior of other nodes. We perform network simulations using Contiki-OS to analyze the performance of the proposed trust model. Simulation results show effectiveness against On-Off attacks and also a good performance to recognize malicious nodes in the network.

A Novel Trust Establishment Method for Wireless Sensor Networks

Establishment of trust is important in wireless sensor networks for security enhancement and successful collaboration. Basically, a node establishes trust with other nodes by estimating a trust value based on monitored behavior of the other nodes. Since a malicious/misbehaving node might launch different attack strategies and might demonstrate random misbehavior, a trust estimation method should be robust against such attacks and misbehavior. Otherwise, the operation of trust establishment will be meaningless, and performance of an application that runs on top of trust establishment will degrade. In this paper, we propose a robust and novel trust estimation method. Unlike traditional trust estimation methods, we consider not only the weight of misbehavior but also the frequency of misbehavior. The frequency-of-misbehavior component explicitly demonstrates how frequently a node misbehaves during a certain observed time period, and it tracks the behavior of nodes more efficiently, which is a main factor in deriving an accurate trust value. In addition, the weight of misbehavior is comprehensively measured to mitigate the effect of an on-off attack. Frequency and weight of misbehavior are comprehensively combined to obtain the trust value. Evaluation results show that the proposed method outperforms other trust estimation methods under different attacks and types of misbehavior.

Trust Management for Defending On-Off Attacks

A trust management scheme can be used to aid an automated decision-making process for an access control policy. Since unintentional temporary errors are possible, the trust management solution must provide a redemption scheme to allow nodes to recover trust. However, if a malicious node tries to disguise its malicious behaviors as unintentional temporary errors, the malicious node may be given more opportunities to attack the system by disturbing the redemption scheme. Existing trust management schemes that employ redemption schemes fail to discriminate between temporary errors and disguised malicious behaviors in which the attacker cleverly behaves well and badly alternatively. In this paper, we present the vulnerabilities of existing redemption schemes, and describe a new trust management and redemption scheme that can discriminate between temporary errors and disguised malicious behaviors with a flexible design. We show the analytical results of the trust management scheme, and demonstrate the advantages of the proposed scheme with simulation conducted in a Wireless Sensor Network.

A robust trust establishment scheme for wireless sensor networks.

Security techniques like cryptography and authentication can fail to protect a network once a node is compromised. Hence, trust establishment continuously monitors and evaluates node behavior to detect malicious and compromised nodes. However, just like other security schemes, trust establishment is also vulnerable to attack. Moreover, malicious nodes might misbehave intelligently to trick trust establishment schemes. Unfortunately, attack-resistance and robustness issues with trust establishment schemes have not received much attention from the research community. Considering the vulnerability of trust establishment to different attacks and the unique features of sensor nodes in wireless sensor networks, we propose a lightweight and robust trust establishment scheme. The proposed trust scheme is lightweight thanks to a simple trust estimation method. The comprehensiveness and flexibility of the proposed trust estimation scheme make it robust against different types of attack and misbehavior. Performance evaluation under different types of misbehavior and on-off attacks shows that the detection rate of the proposed trust mechanism is higher and more stable compared to other trust mechanisms.

An Improved Trusted Greedy Perimeter Stateless Routing for Wireless Sensor Networks

In this paper, an improvement over Trusted Greedy Perimeter Stateless Routing (T-GPSR) is presented. T-GPSR employs heuristic weight values to evaluate total trust value of neighboring nodes. However, heuristic assignment of weights provide flexibility but it is not suitable in presence of several security attacks such as Grey hole, selfish behavior, on-off attack etc., are launched in the network in different proportions. To overcome this limitation, an improvement is suggested with an emphasis on trust update, lightweight trust computation and storage to reduce communication and storage overhead. The simulation study indicates that the packet delivery ratio of the improved T-GPSR has improved by 10% over T-GPSR in the presence of 50% of malicious nodes in the network.

Design and Analysis of Lightweight Trust Mechanism for Accessing Data in MANETs

Lightweight trust mechanism with lightweight cryptographic primitives has emerged as an important mechanism in resource constraint wireless sensor based mobile devices. In this work, outlier detection in lightweight Mobile Ad-hoc NETworks (MANETs) is extended to create the space of reliable trust cycle with anomaly detection mechanism and minimum energy losses [1]. Further, system is tested against outliers through detection ratios and anomaly scores before incorporating virtual programmable nodes to increase the efficiency. Security in proposed system is verified through ProVerif automated toolkit and mathematical analysis shows that it is strong against bad mouthing and on-off attacks. Performance of proposed technique is analyzed over different MANET routing protocols with variations in number of nodes and it is observed that system provide good amount of throughput with maximum of 20% increase in delay on increase of maximum of 100 nodes. System is reflecting good amount of scalability, optimization of resources and security. Lightweight modeling and policy analysis with lightweight cryptographic primitives shows that the intruders can be detection in few milliseconds without any conflicts in access rights.

PerContRep: a practical reputation system for pervasive content services

Social network has extended its popularity from the Internet to mobile domain. Personal mobile devices can be self-organized and communicate with each other for instant social activities at any time and in any places to achieve pervasive social networking (PSN). In such a network, various content information flows. To which extent should mobile users trust it, whilst user privacy can also be preserved? Existing work has not yet seriously considered trust and reputation management, although trust plays an important role in PSN. In this paper, we propose PerContRep, a practical reputation system for pervasive content services that can assist trustworthy content selection and consumption in a pervasive manner. We develop a hybrid trust and reputation management model to evaluate node recommendation trust and content reputation in the context of frequent change of node pseudonyms. Simulations show the advantages of PerContRep in assisting user decisions and its effectiveness with regard to unfair rating attack, collaborative unfair rating attack, on-off attack and conflict behavior attack. A prototype system achieves positive user feedback on its usability and social acceptance.

A Secure Trust Establishment Scheme for Wireless Sensor Networks

Trust establishment is an important tool to improve cooperation and enhance security in wireless sensor networks. The core of trust establishment is trust estimation. If a trust estimation method is not robust against attack and misbehavior, the trust values produced will be meaningless, and system performance will be degraded. We present a novel trust estimation method that is robust against on-off attacks and persistent malicious behavior. Moreover, in order to aggregate recommendations securely, we propose using a modified one-step M-estimator scheme. The novelty of the proposed scheme arises from combining past misbehavior with current status in a comprehensive way. Specifically, we introduce an aggregated misbehavior component in trust estimation, which assists in detecting an on-off attack and persistent malicious behavior. In order to determine the current status of the node, we employ previous trust values and current measured misbehavior components. These components are combined to obtain a robust trust value. Theoretical analyses and evaluation results show that our scheme performs better than other trust schemes in terms of detecting an on-off attack and persistent misbehavior.

A generic solution for unwanted traffic control through trust management

The Internet has dramatically changed our daily life. But it is also bogged down by unwanted traffic, which is malicious, harmful or unexpected for its receivers. In order to control the unwanted traffic over the Internet, especially the mobile Internet, in this paper, we propose a generic unwanted traffic control (UTC) solution through trust management. It can control unwanted traffic from its source to destinations in a personalized manner according to trust evaluation at a Global Trust Operator, traffic and behavior analysis at hosts and traffic observation in the Internet. Thus, it can conduct UTC by integrating distributed and centralized functions and supporting both defensive and offensive approaches. Simulation based evaluation shows that the solution is effective with regard to accuracy and efficiency for botnet intrusion and DDoS intrusion via reflectors. It is also robust against a number of malicious system attacks, such as hide evidence attack, bad mouthing attack, on-off attack, malicious attack by an Internet Service Provider and combinations of the above, playing in conjunction with traffic intrusions. Meanwhile, the solution can provide a personalized UTC based on unwanted traffic detection behaviors.

Trust Management Scheme Based on D-S Evidence Theory for Wireless Sensor Networks

Trust management scheme has been regarded as a powerful tool to defend against the wide set of security attacks and identify malicious nodes. In this paper, we propose a trust management scheme based on revised Dempster-Shafer (D-S) evidence theory. D-S theory is preponderant in tackling both random and subjective uncertainty in the trust mechanism. A trust propagation mechanism including conditional trust transitivity and dynamic recommendation aggregation is developed for obtaining the recommended trust values from third part nodes. We adopt a flexible synthesis method that uses recommended trust only when no direct trust exists to keep a good trust-energy consumption balance. We also consider on-off attack and bad mouthing attack in our simulation. The simulation results and analysis show that the proposed method has excellent ability to deal with typical network attacks, better security, and longer network lifetime.