Automatic repair of pollution attacks in SDN topology network based on SOM algorithm

2021 ◽  
Vol 18 (3) ◽  
pp. 243
Author(s):  
N.A. Alun ◽  
Xiaoliang Yang ◽  
Yi Dai
Keyword(s):  
Pollution Attacks ◽  
Som Algorithm

Signature scheme for securing two-source network coding against pollution attacks

2012 ◽  
Vol 31 (6) ◽  
pp. 1512-1514
Author(s):  
Shu-fen NIU ◽  
Cai-fen WANG ◽  
Xue-yan LIU
Keyword(s):  
Network Coding ◽  
Signature Scheme ◽  
Pollution Attacks

scholarly journals A Secure Protocol against Selfish and Pollution Attacker Misbehavior in Clustered WSNs

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1244
Author(s):  
Hana Rhim ◽  
Damien Sauveron ◽  
Ryma Abassi ◽  
Karim Tamine ◽  
Sihem Guemara
Keyword(s):  
Denial Of Service ◽  
Base Station ◽  
Hierarchical Organization ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Dos Attacks ◽  
Linear Network ◽  
Secure Protocol ◽  
Misbehaving Nodes ◽  
Pollution Attacks

Wireless sensor networks (WSNs) have been widely used for applications in numerous fields. One of the main challenges is the limited energy resources when designing secure routing in such networks. Hierarchical organization of nodes in the network can make efficient use of their resources. In this case, a subset of nodes, the cluster heads (CHs), is entrusted with transmitting messages from cluster nodes to the base station (BS). However, the existence of selfish or pollution attacker nodes in the network causes data transmission failure and damages the network availability and integrity. Mainly, when critical nodes like CH nodes misbehave by refusing to forward data to the BS, by modifying data in transit or by injecting polluted data, the whole network becomes defective. This paper presents a secure protocol against selfish and pollution attacker misbehavior in clustered WSNs, known as (SSP). It aims to thwart both selfish and pollution attacker misbehaviors, the former being a form of a Denial of Service (DoS) attack. In addition, it maintains a level of confidentiality against eavesdroppers. Based on a random linear network coding (NC) technique, the protocol uses pre-loaded matrices within sensor nodes to conceive a larger number of new packets from a set of initial data packets, thus creating data redundancy. Then, it transmits them through separate paths to the BS. Furthermore, it detects misbehaving nodes among CHs and executes a punishment mechanism using a control counter. The security analysis and simulation results demonstrate that the proposed solution is not only capable of preventing and detecting DoS attacks as well as pollution attacks, but can also maintain scalable and stable routing for large networks. The protocol means 100% of messages are successfully recovered and received at the BS when the percentage of lost packets is around 20%. Moreover, when the number of misbehaving nodes executing pollution attacks reaches a certain threshold, SSP scores a reception rate of correctly reconstructed messages equal to 100%. If the SSP protocol is not applied, the rate of reception of correctly reconstructed messages is reduced by 90% at the same case.

Secret Error-Correcting Network Coding against Eavesdropping and Pollution Attacks

2012 ◽  
Vol 457-458 ◽  
pp. 1499-1507 ◽  
Author(s):  
Si Guang Chen ◽  
Meng Wu ◽  
Wei Feng Lu
Keyword(s):  
Network Coding ◽  
Necessary Condition ◽  
Information Theoretic ◽  
Transmitted Information ◽  
Information Theoretic Security ◽  
Secret Communication ◽  
Pollution Attacks ◽  
Rank Metric Codes ◽  
Shared Secret ◽  
And Performance

In this work we consider the problem of designing a secret error-correcting network coding scheme against an adversary that can re-select the tapping links in different time slot and inject z erroneous packets into network. We first derive a necessary condition for keeping the transmitted information secret from the adversary, while the network is only subject to the eavesdropping attack. We then design an error-correcting scheme by combining the rank-metric codes with shared secret model, which can decode the transmitted information correctly provided a sufficiently large q. With that, a secret error-correcting network coding is proposed by combining this error-correcting scheme with secret communication. We show that under the requirement of communication can achieve a rate of packets. Moreover, it ensures that the communicated information is reliable and information-theoretic security from the adversary. In particular, the requirement of packet length is not as large as the required in [12]. Finally, the security and performance analyses illustrate the characteristics of our scheme.

scholarly journals Mental state space visualization for interactive modeling of personalized BCI control strategies

2019 ◽  
Author(s):  
Ilya Kuzovkin ◽  
Konstantin Tretyakov ◽  
Andero Uusberg ◽  
Raul Vicente
Keyword(s):  
State Space ◽  
Mental State ◽  
Control Strategies ◽  
Muscular Activity ◽  
Mental States ◽  
Learning System ◽  
Self Organizing Map ◽  
Preliminary Validation ◽  
Som Algorithm ◽  
Mental Actions

AbstractObjectiveNumerous studies in the area of BCI are focused on the search for a better experimental paradigm – a set of mental actions that a user can evoke consistently and a machine can discriminate reliably. Examples of such mental activities are motor imagery, mental computations, etc. We propose a technique that instead allows the user to try different mental actions in the search for the ones that will work best.ApproachThe system is based on a modification of the self-organizing map (SOM) algorithm and enables interactive communication between the user and the learning system through a visualization of user’s mental state space. During the interaction with the system the user converges on the paradigm that is most efficient and intuitive for that particular user.Main resultsResults of the two experiments, one allowing muscular activity, another permitting mental activity only, demonstrate soundness of the proposed method and offer preliminary validation of the performance improvement over the traditional closed-loop feedback approach.SignificanceThe proposed method allows a user to visually explore their mental state space in real time, opening new opportunities for scientific inquiry. The application of this method to the area of brain-computer interfaces enables more efficient search for the mental states that will allow a user to reliably control a BCI system.

scholarly journals Application of self organizing map in construction, geology and petroleum industry

2017 ◽  
Vol 20 (K4) ◽  
pp. 30-38
Author(s):  
Tung Son Pham ◽  
Huy Minh Truong ◽  
Tuan Ba Pham
Keyword(s):  
Industrial Revolution ◽  
Human Life ◽  
Petroleum Industry ◽  
Self Organizing Map ◽  
Practical Applications ◽  
Fourth Industrial Revolution ◽  
Som Algorithm ◽  
Clustering Data ◽  
Self Organizing

In recent years, Artificial Intelligence (AI) has become an emerging subject and been recognized as the flagship of the Fourth Industrial Revolution. AI is subtly growing and becoming vital in our daily life. Particularly, Self-Organizing Map (SOM), one of the major branches of AI, is a useful tool for clustering data and has been applied successfully and widespread in various aspects of human life such as psychology, economic, medical and technical fields like mechanical, construction and geology. In this paper, the primary purpose of the authors is to introduce SOM algorithm and its practical applications in geology and construction. The results are classification of rock facies versus depth in geology and clustering two sets of construction prices indices and building material costs indice.

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