Security and Trust for Wireless Autonomic Networks Systems and Control Methods

Baras, John S.

doi:10.3166/ejc.13.105-133

Cited by 18 publications

(9 citation statements)

References 63 publications

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“…The control of the admission is of the new session's user is based on a model of response time. The dynamic approach of adaptation in response times adapts the model to the changes of the characteristics according to the workload and the system requirements so that the system can function automatically, without human intervention [12].…”

Section: Dynamic Adaptation Of the Models In Response Times For The Mmentioning

confidence: 99%

“…The autonomic networks are considered as a solution for the concept of management autonomous the policies make it possible to guide the autonomous elements in terms of objectives to be reached, or service to be returned, load with this one to adapt to the dynamic modification of the rules of policy. To avoid the intervention of the human administrators, the autonomous networks have an automatic characteristic of reflection through well-defined techniques of training but the problems of safety of network (confidence of information, defense, tackles protocols of routing, the dynamic confidence of self-management…) remain stakes [12]. The management of future internet requires the adaptation of autonomous networks to intelligent strategies that provide the technical support for the construction of temporary and highly dynamic networks to meet the human needs for the future ubiquitous and flexible network [13][14][15][16][17].…”

Section: Conclusion and Prospectsmentioning

confidence: 99%

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Self-organization and Autonomous Network Survey

Sakly¹

2020

IJNSA

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PurposeThe autonomic network gathers several aspects of Self-organization, which is depicted, into different autonomous function such as the Self-configuration, the Self-optimization, the Self-repair, the Selfprotection, and the Self-cure. The latter is considered as one of the autonomous functions wished of a system network, which could be described by autonomous behavior is realized by structures of the control loops and loop of control. IssueThese various aspects require an architectural framework, which integrates several protocols of telecommunication as well as programs proactive and reagents for the prevention and the resolution of the unforeseen problems. To ensure a reduction of the loops of the operator, we need good management per policy. An autonomic vision must guarantee the safety and the availability of the resources for the endusers by respecting the constraints of QoS and the deadlines for replies. GoalsDepict the challenges, the interests, and the anomalies and compare the autonomic approaches of the networks which consist of discovering neighbor's in the self-organizing wireless network. These points are considered the cornerstone of extending autonomous coverage and improving performance. However, the objective is to detect the hidden node in the neighbor discovery procedure based on the simple flood caused by the uncoordinated transmission, which can cause an unnecessary loss of energy.

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Section: Dynamic Adaptation Of the Models In Response Times For The Mmentioning

confidence: 99%

Section: Conclusion and Prospectsmentioning

confidence: 99%

Self-organization and Autonomous Network Survey

Sakly¹

2020

IJNSA

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“…There is a large body of literature regarding game theoretical approaches to cyber and network security [1][2][3]16]. Byzantine attacks have their root in the Byzantine generals problem where the traitor generals want to prevent the loyal generals from reaching an agreement [10].…”

Section: Related Workmentioning

confidence: 99%

Detection in Adversarial Environments

Vamvoudakis

Hespanha

Sinopoli

et al. 2014

IEEE Trans. Automat. Contr.

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We propose new game theoretic approaches to estimate a binary random variable based on sensor measurements that may have been corrupted by a cyber-attacker. The estimation problem is formulated as a zero-sum partial information game in which a detector attempts to minimize the probability of an estimation error and an attacker attempts to maximize this probability. While this problem can be solved exactly by reducing it to the computation of the value of a matrix, this approach is computationally feasible only for a small number of sensors. The two key results of this paper provide complementary computationally efficient solutions to the construction of the optimal detector. The first result provides an explicit formula for the optimal detector but it is only valid when the number of sensors is roughly smaller than two over the probability of sensor errors. In contrast, the detector provided by the second result is valid for an arbitrary number of sensor. While it may result in a probability of estimation error that is above the minimum achievable, we show that this error is small when the number of sensors is large, which is precisely the case for which the first result does not apply.

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“…In the last decade or two, this question has been asked in the computer science community from various viewpoints. The result has been the formulation of the notion that two interacting objects or agents can and must establish trust before they can work together to attain whatever common goal they might share [5], [6]. In this paper, we develop this notion in the context of wireless network theory.…”

Section: Introductionmentioning

confidence: 98%

Modelling trust in random wireless networks

Coon

2014

2014 11th International Symposium on Wireless Communications Systems (ISWCS)

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We present an analysis of the probability that a set of devices capable of communicating wirelessly can form a fully connected, trusted network. The network model that is used accounts for the geometric properties of the physical network boundaries, the statistical nature of the propagation environment, and the notion that both trustworthy and untrustworthy devices may occupy the network domain. Two local (pairwise) trust models are explored in the context of this model: proximitybased trust, where trust between two devices is a function of the distance between them, and experience-based trust, where trust is dependent upon the outcomes from prior inter-device interactions. Both models are probabilistic, a condition that is motivated by our interest in the steady state or average behaviour of the network as well as several practical applications, including sensor and device-to-device (D2D) networks for disaster relief, public safety, and peer-to-peer file sharing in 5G cellular systems. Our analysis illustrates a clear and simple mathematical relationship between the local trust probabilities and the underlying physics of the system, thus pointing to a need for trust protocols that are tailored to specific deployments.

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Security and Trust for Wireless Autonomic Networks Systems and Control Methods

Cited by 18 publications

References 63 publications

Self-organization and Autonomous Network Survey

Self-organization and Autonomous Network Survey

Detection in Adversarial Environments

Modelling trust in random wireless networks

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