• International Journal of Computer Science & Network Security
• /
• v.21 no.6
• /
• pp.89-100
• /
• 2021

Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.3
• /
• pp.35-45
• /
• 2013

MANET has a weak point because it allows access from not only legal nodes but also illegal nodes. Most of the MANET researches had been focused on attack on routing path or packet forwarding. Nevertheless, there are insuffcient studies on a comprehensive approach to detect various attacks on malicious nodes at packet forwarding processes. In this paper, we propose a technique, named DTecBC (detection technique of malicious node behaviors based on collaboration), which can handle more effciently various types of malicious node attacks on MANET environment. The DTecBC is designed to detect malicious nodes by communication between neighboring nodes, and manage malicious nodes using a maintain table. OPNET tool was used to compare with Watchdog, CONFIDANT, SRRPPnT for verifying effectiveness of our approach. As a result, DTecBC detects various behaviors of malicious nodes more effectively than other techniques.

• The KIPS Transactions:PartC
• /
• v.12C no.5 s.101
• /
• pp.617-622
• /
• 2005

Lately, the MANET research has focused on providing routing services with security and previous schemes have been proposed for detecting malicious nodes in a MANET. However, they still include some problems which malicious nodes cannot be found when they falsely report other nodes as malicious. Accordingly, we propose a novel and efficient scheme for detecting malicious nodes using report messages and a report table which is consisted of node ID both for suspecting and reporting when the malicious nodes behave normally during the route discovery, but the other hand they drop and modify packets, or falsely report other nodes as malicious during the data transmission. Our proposed scheme is applicable to not only DSR but aiso AODV. And we provide some simulation results of our proposed scheme by comparing general AODV with our proposed scheme. Simulation results show that our Proposed scheme outperforms general AODV in terms of average packet loss ratio and packet delivery ratio.

• Journal of Communications and Networks
• /
• v.17 no.1
• /
• pp.75-83
• /
• 2015

In mobile ad-hoc networks (MANETs), nodes are mobile in nature. Collaboration between mobile nodes is more significant in MANETs, which have as their greatest challenges vulnerabilities to various security attacks and an inability to operate securely while preserving its resources and performing secure routing among nodes. Therefore, it is essential to develop an effective secure routing protocol to protect the nodes from anonymous behaviors. Currently, game theory is a tool that analyzes, formulates and solves selfishness issues. It is seldom applied to detect malicious behavior in networks. It deals, instead, with the strategic and rational behavior of each node. In our study,we used the dynamic Bayesian signaling game to analyze the strategy profile for regular and malicious nodes. This game also revealed the best actions of individual strategies for each node. Perfect Bayesian equilibrium (PBE) provides a prominent solution for signaling games to solve incomplete information by combining strategies and payoff of players that constitute equilibrium. Using PBE strategies of nodes are private information of regular and malicious nodes. Regular nodes should be cooperative during routing and update their payoff, while malicious nodes take sophisticated risks by evaluating their risk of being identified to decide when to decline. This approach minimizes the utility of malicious nodes and it motivates better cooperation between nodes by using the reputation system. Regular nodes monitor continuously to evaluate their neighbors using belief updating systems of the Bayes rule.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.11
• /
• pp.4644-4661
• /
• 2015

Wireless sensor networks are often organized in the form of clusters leading to the new framework of WSN called cluster or hierarchical WSN where each cluster head is responsible for its own cluster and its members. These hierarchical WSN are prone to various routing layer attacks such as Black hole, Gray hole, Sybil, Wormhole, Flooding etc. These routing layer attacks try to spoof, falsify or drop the packets during the packet routing process. They may even flood the network with unwanted data packets. If one cluster head is captured and made malicious, the entire cluster member nodes beneath the cluster get affected. On the other hand if the cluster member nodes are malicious, due to the broadcast wireless communication between all the source nodes it can disrupt the entire cluster functions. Thereby a scheme which can detect both the malicious cluster member and cluster head is the current need. Abnormal energy consumption of nodes is used to identify the malicious activity. To serve this purpose a learning based energy prediction algorithm is proposed. Thus a two level energy prediction based intrusion detection scheme to detect the malicious cluster head and cluster member is proposed and simulations were carried out using NS2-Mannasim framework. Simulation results achieved good detection ratio and less false positive.

• Journal of KIISE:Computing Practices and Letters
• /
• v.14 no.5
• /
• pp.487-491
• /
• 2008

This paper proposes the Byzantine fault tolerant clock synchronization scheme for wireless sensor networks to cope with the clock synchronization disturbance attack of malicious nodes. In the proposed scheme, a node which is requiring clock synchronization receives 3m+1 clock synchronization messages not only from its parent nodes but also from its sibling nodes in order to tolerate malicious attacks even if up to m malicious nodes exist among them. The results show that the proposed scheme is 7 times more resilient to the clock synchronization disturbance attack of malicious nodes than existing schemes in terms of synchronization accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.12
• /
• pp.2716-2723
• /
• 2010

An Ad-hoc network will operate properly and provide smooth communication when nodes cooperate mutually with each of them having equal authority. Although it is possible to form a network consisting only of authenticated nodes in order to ensure reliability, authentication by itself is not sufficient to remove malicious nodes and their activities jeopardizing the whole network. Detection and prevention of such activities are vital for maintaining a safe and reliable network, but research on this matter is relatively lacking. Hence a suggestion is made on how to detect and prevent malicious or uncooperative ones among the nodes forming a network by a relationship of mutual trust, thereby maintaining safety and stability of the network and improving its processing abilities

• ETRI Journal
• /
• v.41 no.6
• /
• pp.739-749
• /
• 2019

Security and accuracy are two issues in the localization of wireless sensor networks (WSNs) that are difficult to balance in hostile indoor environments. Massive numbers of malicious positioning requests may cause the functional failure of an entire WSN. To eliminate the misjudgments caused by malicious nodes, we propose a compressive-sensing-based multiregional secure localization (CSMR_SL) algorithm to reduce the impact of malicious users on secure positioning by considering the resource-constrained nature of WSNs. In CSMR_SL, a multiregion offline mechanism is introduced to identify malicious nodes and a preprocessing procedure is adopted to weight and balance the contributions of anchor nodes. Simulation results show that CSMR_SL may significantly improve robustness against attacks and reduce the influence of indoor environments while maintaining sufficient accuracy levels.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.9 no.4
• /
• pp.95-101
• /
• 2013

MANET has an advantage that can build a network quickly and easily in difficult environment to build network. In particular, routing protocol that uses in existing mobile environment cannot be applied literally because it consists of only mobile node. Thus, routing protocol considering this characteristic is necessary. Malicious nodes do extensive damage to the whole network because each mobile node has to act as a router. In this paper, we propose technique that can detect accurately the suspected node which causes severely damage to the performance of the network. The proposed technique divides the whole network to zone of constant size and is performed simultaneously detection technique based zone and detection technique by collaboration between nodes. Detection based zone translates the information when member node finishes packet reception or transmission to master node managing zone and detects using this. The collaborative detection technique uses the information of zone table managing in master node which manages each zone. The proposed technique can reduce errors by performing detection which is a reflection of whole traffic of network.

• Journal of Communications and Networks
• /
• v.9 no.1
• /
• pp.56-66
• /
• 2007

Mobile ad-hoc networks (MANETs) have attracted great research interest in recent years. Among many issues, lack of motivation for participating nodes to collaborate forms a major obstacle to the adoption of MANETs. Many contemporary collaboration enforcement techniques employ reputation mechanisms for nodes to avoid and penalize malicious participants. Reputation information is propagated among participants and updated based on complicated trust relationships to thwart false accusation of benign nodes. The aforementioned strategy suffers from low scalability and is likely to be exploited by adversaries. In this paper, we propose a novel approach to address these problems. With the proposed technique, no reputation information is propagated in the network and malicious nodes cannot cause false penalty to benign hosts. Nodes classify their one-hop neighbors through direct observation and misbehaving nodes are penalized within their localities. Data packets are dynamically rerouted to circumvent selfish nodes. As a result, overall network performance is greatly enhanced. This approach significantly simplifies the collaboration enforcement process, incurs low overhead, and is robust against various malicious behaviors. Simulation results based on different system configurations indicate that the proposed technique can significantly improve network performance with very low communication cost.