Adjacent Node based Energetic Association Factor Routing Protocol in Wireless Sensor Networks

Mobile Ad-Hoc Network (MANET) consist a numerous nodes and these nodes are structured with remote transceivers. These nodes forward the message with one another by getting to the typical channel. In MANET, security is the principle challenge to be analyzed. Due to the behaviour of malevolent nodes, the network security is weakened. Along these lines, the significant goal of this research is to enhance the network security by detecting the malevolent nodes. So, for the detection of malevolent node, an effective trust management method is presented in this paper. Improving the trust score the optimized fuzzy framework is proposed. For enhancing the execution of the fuzzy framework, the triangular membership function of the input parameters is improved with the Cat Swarm Optimization. After estimating the trust score for every node in the network, threshold depend decision module is processed for detecting the activity of malevolent nodes. Implementation results illustrate that the execution of the proposed model achieves maximum network lifetime and minimum energy consumption.

     

Novel approach of distributed & adaptive trust metrics for MANET

It is known to all that mobile ad hoc network (MANET) is more vulnerable to all sorts of malicious attacks which affects the reliability of data transmission because the network has the characteristics of wireless, multi-hop, etc. We put forward novel approach of distributed & adaptive trust metrics for MANET in this paper. Firstly, the method calculates the communication trust by using the number of data packets between nodes, and predicts the trust based on the trend of this value, and calculates the comprehensive trust by considering the history trust with the predict value; then calculates the energy trust based on the residual energy of nodes and the direct trust based on the communication trust and energy trust. Secondly, the method calculates the recommendation trust based on the recommendation reliability and the recommendation familiarity; adopts the adaptive weighting, and calculates the integrate direct trust by considering the direct trust with recommendation trust. Thirdly, according to the integrate direct trust, considering the factor of trust propagation distance, the indirect trust between nodes is calculated. The feature of the proposed method is its ability to discover malicious nodes which can partition the network by falsely reporting other nodes as misbehaving and then proceeds to protect the network. Simulation experiments and tests of the practical applications of MANET show that the proposed approach can effectively avoid the attacks of malicious nodes, besides, the calculated direct trust and indirect trust about normal nodes are more conformable to the actual situation.

     

CrowWhale-ETR: CrowWhale optimization algorithm for energy and trust aware multicast routing in WSN for IoT applications

WSN serves as a medium for linking the physical and information network of IoT. Energy and trust are the two major factors that facilitate reliable communication in the network. During multicast routing, the BS engages in forwarding the data securely to the multiple destinations through the intermediate nodes, which is the major challenge in IoT. The paper addresses the challenges through proposing an energy-aware multicast routing protocol based on the optimization, CrowWhale-ETR, which is the integration of CSA and WOA based on the objective function designed with the energy and trust factors of the nodes. Initially, the trust and energy of the nodes are evaluated for establishing the routes that is chosen optimally using CWOA. This optimally chosen path is used for the data transmission, in which energy and trusts of the individual nodes are updated at the end of the individual transmission, in such a way the secure nodes can be selected, and which improves the secure communication in the network. The simulation is analyzed using 50 and 100 nodes in terms of the performance measures. The proposed method acquired the minimal delay of 0.2729 and 0.3491, maximal detection rate of 0.6726, maximal energy of 66.4275 and 71.0567, and maximal throughput of 0.4625 and 0.8649 in the presence and absence of attacks with 50 nodes for analysis.

     

Trust-Aware Fuzzy Evaluation Method for Preventive Route Generation in Mobile Network

The existence of a non-cooperative or black hole node as an intermediate node in a mobile network can degrade the performance of the network and affects the trust of neighbor nodes. In this paper, a trust-aware routing protocol is defined for improving the routing reliability against black hole attacks. A new Trust aware and fuzzy regulated AODV (TFAODV) protocol is investigated in this work as an improvement over the existing AODV protocol. The session-driven evaluation of stability, communication-delay, and failure-ratio parameters are conducted for evaluating the trust of nodes. The fuzzy rules apply to these parameters for computing the degree of trust. This trust vector isolates the attack-suspected and trustful nodes. The proposed TFAODV protocol used the trustful mobile nodes as the intermediate path nodes. The proposed protocol has been experimented with in the NS2 simulation environment. The analytical results are obtained in terms of PDR ratio, Packet Communication, Loss rate parameters. The comparative results are derived against the AODV, Probabilistic AODV, PDS-AODV, PSAODV, and Juneja et al. protocols. The analysis is performed on different scenarios varied in terms of network density, degree of stability, and the number of attackers. The simulation results ensured the proposed TFAODV protocol has improved the PDR ratio and reduced the communication loss significantly against these state-of-art protocols.

     

基于改进的朴素贝叶斯的入侵检测方法

随着当前网络安全环境的日益严峻,针对网络入侵事件的检测至关重要。面对网络入侵检测中数据集合存在的冗余特征,提出一种改进后的朴素贝叶斯算法。该算法在原有朴素贝叶斯的基础上巧妙引入卡方检验,通过筛选数据集中占比重要的特征降低数据维度,提高了入侵检测的准确性。最后,结合实验结果证明,该方法有效提高了入侵检测的准确性。     

A Novel Technique for Gateway Selection in Hybrid MANET Using Genetic Algorithm

Integration of Mobile Ad hoc NETworks (MANETs) with the Internet has been paid immense attention in the field of heterogeneous networks. In MANET some intermediate nodes called Internet Gateways (IGs) are responsible for sending the data traffic of source nodes towards the fixed nodes in the Internet. The key issue considered while selecting IG nodes is its optimised throughput with the reduced delay in resource constraint mobile nodes. In this paper, a genetic algorithm inspired Delay Sensitive Gateway Selection (DSGS) scheme is proposed considering the issue of network delay by minimising the total distance travelled by the source nodes to the gateway. The performance of the proposed GA-based DSGS scheme is studied using a comparative approach. The simulation results demonstrate that the proposed scheme significantly outperforms the conventional schemes and is capable of achieving higher network throughput while minimising the end-to-end delay.

     

A Novel QoS Based Secure Unequal Clustering Protocol with Intrusion Detection System in Wireless Sensor Networks

Wireless sensor network (WSN) becomes a hot research topic owing to its application in different fields. Minimizing the energy dissipation, maximizing the network lifetime, and security are considered as the major quality of service (QoS) factors in the design of WSN. Clustering is a commonly employed energy-efficient technique; however, it results in a hot spot issue. This paper develops a novel secure unequal clustering protocol with intrusion detection technique to achieve QoS parameters like energy, lifetime, and security. Initially, the proposed model uses adaptive neuro fuzzy based clustering technique to select the tentative cluster heads (TCHs) using three input parameters such as residual energy, distance to base station (BS), and distance to neighbors. Then, the TCHs compete for final CHs and the optimal CHs are selected using the deer hunting optimization (DHO) algorithm. The DHO based clustering technique derives a fitness function using residual energy, distance to BS, node degree, node centrality, and link quality. To further improve the performance of the proposed method, the cluster maintenance phase is utilized for load balancing. Finally, to achieve security in cluster based WSN, an effective intrusion detection system using a deep belief network is executed on the CHs to identify the presence of intruders in the network. An extensive set of experiments were performed to ensure the superior performance of the proposed method interms of energy efficiency, network lifetime, packet delivery ratio, average delay, and intrusion detection rate.

     

Energy Attentive and Pre-fault Recognize Mechanism for Distributed Wireless Sensor Network Using Fuzzy Logic Approach

Wireless sensor networks (WSNs) have been transforming over recent years with development in the design of smart real-time applications. However, it presents numerous challenges in terms of fault-tolerant communication, low latency, scalability, and transmission efficiency. It is extremely difficult for WSNs to detect runtime faults since they're unaware of the internal processes at work within the sensor node. As a result, valuable sensed information cannot reach its destination and performance starts degrading. Towards this objective, the proposed mechanism applies a novel pre-fault detection mechanism based on a fuzzy rule-based method for multilevel transmission in distributed sensor networks. The proposed mechanism uses a fuzzy rule set to make routing decisions. A fuzzy decision rule set is proposed to perform routing based on the fuzzy fault count status of a node. The proposed mechanism assists in identifying the fault in advance and determining the optimal routing path to save energy and improve network performance. In accordance with the node fault status, the data transmission rate is finalized to prevent further energy consumption. The results demonstrated that the proposed mechanism performed well on judgment evaluation metrics like the energy dissipation ratio, throughput, packet loss rate and communication delay.

     

New Approaches to Routing in Mobile Ad hoc Networks

Worldwide Interoperability for Microwave Access (Wimax) is power station through which mobile network, commonly known as A Mobile Ad-hoc Network (MANET) is used by the people. A MANET can be described as an infrastructure-less and self-configure network with autonomous nodes. Participated nodes in MANETs move through the network constantly causing frequent topology changes. Designing suitable routing protocols to handle the dynamic topology changes in MANETs can enhance the performance of the network. In this regard, this paper proposes four algorithms for the routing problem in MANETs. First, we propose a new method called Classical Logic-based Routing Algorithm for the routing problem in MANETs. Second is a routing algorithm named Fuzzy Logic-based Routing Algorithm (FLRA). Third, a Reinforcement Learning-based Routing Algorithm is proposed to construct optimal paths in MANETs. Finally, a fuzzy logic-based method is accompanied with reinforcement learning to mitigate existing problems in FLRA. This algorithm is called Reinforcement Learning and Fuzzy Logic-based (RLFLRA) Routing Algorithm. Our proposed approaches can be deployed in dynamic environments and take four important fuzzy variables such as available bandwidth, residual energy, mobility speed, and hop-count into consideration. Simulation results depict that learning process has a great impact on network performance and RLFLRA outperforms other proposed algorithms in terms of throughput, route discovery time, packet delivery ratio, network access delay, and hop-count.

     

E‐TDGO: An encrypted trust‐based dolphin glowworm optimization for secure routing in mobile ad hoc network

Mobile ad hoc networks (MANETs) are independent networks, where mobile nodes communicate with other nodes through wireless links by multihop transmission. Security is still an issue to be fixed in MANETs. Hence, a routing protocol named encrypted trust‐based dolphin glowworm optimization (DGO) (E‐TDGO) is designed using Advanced Encryption Standard‐128 (AES‐128) and trust‐based optimization model for secure routing in MANET. The proposed E‐TDGO protocol includes three phases, namely, k‐path discovery, optimal path selection, and communication. At first, k paths are discovered based on the distance and the trust level of the nodes. From the k paths discovered, the optimal path is selected using a novel algorithm, DGO, which is developed by combining glowworm swarm optimization (GSO) algorithm and dolphin echolocation algorithm (DEA). Once the optimal path is selected, communication begins in the network such that E‐TDGO protocol ensures security. The routing messages are encrypted using AES‐128 with shared code and key to offer security. The experimental results show that the proposed E‐TDGO could attain throughput of 0.11, delay of 0.01 second, packet drop of 0.44, and detection rate of 0.99, at the maximum number of rounds considered in the network of 75 nodes with attack consideration.     

Cross‐layer design for topology control and routing in MANETs

A mobile ad hoc network (MANET) is a self‐organized and adaptive wireless network formed by dynamically gathering mobile nodes. Since the topology of the network is constantly changing, the issue of routing packets and energy conservation become challenging tasks. In this paper, we propose a cross‐layer design that jointly considers routing and topology control taking mobility and interference into account for MANETs. We called the proposed protocol as Mobility‐aware Routing and Interference‐aware Topology control (MRIT) protocol. The main objective of the proposed protocol is to increase the network lifetime, reduce energy consumption, and find stable end‐to‐end routes for MANETs. We evaluate the performance of the proposed protocol by comprehensively simulating a set of random MANET environments. The results show that the proposed protocol reduces energy consumption rate, end‐to‐end delay, interference while preserving throughput and network connectivity. Copyright © 2010 John Wiley & Sons, Ltd.     

Energy Efficient Clustering for Certificate Revocation Scheme in Mobile Ad-Hoc Network

Mobile ad hoc networks (MANETs) have a wide range of uses because of their dynamic topologies and simplicity of processing. Inferable from the autonomous and dynamic behavior of mobile nodes, the topology of a MANET frequently changes and is inclined to different attacks. So, we present certificate revocation which is an efficient scheme is for security enhancement in MANET. This certificate revocation scheme is used to revoke the certificate of malicious nodes in the network. However, the accuracy and speed of the certificate revocation are further to be improved. By considering these issues along with the energy efficiency of the network, an energy-efficient clustering scheme is presented for certificate revocation in MANET. For cluster head (CH) selection, an opposition based cat swarm optimization algorithm (OCSOA) is proposed. This selected CH participates in quick certificate revocation and also supports to recover the falsely accused nodes in the network. Simulation results show that the performance of the proposed cluster-based certificate revocation outperforms existing voting and non-voting based certificate revocation in terms of delivery ratio, throughput, energy consumption, and network lifetime.

     

Faster-than-Nyquist Transmission in SC-FDE System Over Frequency Selective Channel with Concatenated Equalizers

The trustworthiness and connectivity of the network depends on the energy drain rate of mobile nodes. Colluders like vampire nodes in ad hoc network make it more vulnerable as they rapidly drain considerable amount of energy. This generic vampire attacks seem to capitalize on the potential features of the incorporated baseline protocol used for facilitating trustworthy data dissemination. The main goal of this paper is to formulate an attack prevention scheme that uses fuzzy trust relationship perspective for detecting vampire attacks and enforcing reduced energy drain rate of colluding mobile nodes. This fuzzy trust relationship perspective-based prevention mechanism (FTRPPM) initially estimates the associative trust and associative reputation of mobile nodes. Further, it quantifies the impact of factors that could induce vampire attack in the network under its influence. Finally, it facilitates the detection of vampire nodes based on the established ranges of threshold that are dynamically adjusted based on quantified level of probability factor. The empirical and simulation results of FTRPPM is confirmed to be exceptional as it ensures a remarkable improvement in mean PDR of 16% and mean throughput of 14% under the impact of increasing number of mobile nodes on par with the existing vampire attack mitigation schemes.     

Survey on Ultra-Dense Networks (UDNs) and Applied Stochastic Geometry

The innovation of services offered by cellular networks gained the attention of researchers in the communication field. Thus, mobile industries deal with remarkable technological competition regarding service quality. The quality is determined by how superior, consistent, and quick a service is delivered to the user. Thus, mobility management is a basic factor as it deals with imperative information for managing user’s mobility. However, due to the expansion of connected devices, the users are set up densely which inspires the researcher for devising a novel mode switching model. This paper devises a novel mode switching model using the Naive Bayes classifier. Here, the switching of modes is based on certain quality parameters, like link utilization, bandwidth, delay, energy consumption, and signal strength. Whenever the network switches the communication link from cellular-mode to user-mode, it must maintain the quality parameters. For enhancing the performance of network mobility management, a mobility management model is devised in which user mobility is computed. Thus, the proposed method is essential for supporting improved user mobility during communication The proposed mode switching using Naïve Bayes classifier provides superior performance with a minimal delay of 0.164 s, maximal power of 58.786 bpm, maximal link utilization ratio of 0.727 and maximal throughput of 1,641,723 respectively.

     

An EDRI-based approach for detecting and eliminating cooperative black hole nodes in MANET

Mobile Ad hoc Network (MANET) is a self-configurable, self-maintenance network with wireless, mobile nodes. Special features of MANET like dynamic topology, hop-by-hop communications and open network boundary, made security highly challengeable in this network. From security aspect, routing protocols are highly vulnerable against a wide range of attacks like black hole. In black hole attack malicious node injects fault routing information to the network and leads all data packets toward it-self. In this paper, we proposed an approach to detect and eliminate cooperative malicious nodes in MANET with AODV routing protocol. A data control packet is used in order to check the nodes in selected path; also, by using an Extended Data Routing Information table, all malicious nodes in selected path are detected, then, eliminated from network. For evaluation, our approach and a previous work have been implemented using Opnet 14 in different scenarios. Referring to simulation results, the proposed approach decreases packet overhead and delay of security mechanism with no false positive detection. In addition, network throughput is improved by using the proposed approach.     

Analytical Termination of Malicious Nodes (ATOM): An Intrusion Detection System for Detecting Black Hole attack in Mobile Ad Hoc Networks

The decentralized administration and the lack of an appropriate infrastructure causes the MANET prone to attacks. The attackers play on the vulnerable characteristics of the MANET and its underlying routing protocols such as AODV, DSR etc. to bring about a disruption in the data forwarding operation. Hence, the routing protocols need mechanisms to confront and tackle the attacks by the intruders. This research introduces the novel host-based intrusion detection system (HIDS) known as analytical termination of malicious nodes (ATOM) that systematically detects one of the most significant black hole attacks that affects the performance of AODV routing protocol. ATOM IDS performs detection by computing the RREP count (Route Reply) and the packet drop value for each individual node. This system has been simulated over the AODV routing protocol merged with the black hole nodes and the resultant simulation scenario in NS2 has been generated. The trace obtained shows a colossal increase in the packet delivery ratio (PDR) and throughput. The results prove the efficacy of the proposed system.

     

信任感知的安全虚拟网络映射算法

针对网络虚拟化技术带来的新的安全威胁,将信任关系和信任度引入到虚拟网络资源分配中,量化分析了网络虚拟化环境中的安全问题,构建了安全虚拟网络映射的数学模型,并在映射过程中考虑节点的局部和全局重要性,采用逼近理想排序法方法对节点进行多属性重要度排序,提出了一种信任感知的安全虚拟网络映射算法。仿真结果表明,该算法在满足虚拟网络请求可信需求的条件下,获得了较好的映射成功率、映射收益和资源利用率。     

面向MANET报文丢弃攻击的模糊入侵检测系统

为了检测MANET报文丢弃攻击行为,提出一种异常模糊入侵检测系统（FIADS）。FIADS基于Sugeno型模糊推理,通过分布式方式检测每个节点可能遭受的攻击行为,并通过移除所有可能实施攻击的恶意节点提高MANET频谱资源。最后,构建模糊规则库仿真分析了FIADS,并和传统IDES进行了性能比较。仿真结果证明,相比IDES,FIADS能够有效检测报文丢弃攻击,具有更高的识别效率。     

Friend-assisted intrusion detection and response mechanisms for mobile ad hoc networks

Nowadays, a commonly used wireless network (i.e., Wi-Fi) operates with the aid of a fixed infrastructure (i.e., an access point) to facilitate communication between nodes. The need for such a fixed supporting infrastructure limits the adaptability and usability of the wireless network, especially in situations where the deployment of such an infrastructure is impractical. Recent advancements in computer network introduced a new wireless network, known as a mobile ad hoc network (MANET), to overcome the limitations. Often referred as a peer to peer network, the network does not have any fixed topology, and through its multi hop routing facility, each node can function as a router, thus communication between nodes becomes available without the need of a supporting fixed router or an access point. However, these useful facilities come with big challenges, particularly with respect to providing security. A comprehensive analysis of attacks and existing security measures suggested that MANET are not immune to a colluding blackmail because such a network comprises autonomous and anonymous nodes. This paper addresses MANET security issues by proposing a novel intrusion detection system based upon a friendship concept, which could be used to complement existing prevention mechanisms that have been proposed to secure MANETs. Results obtained from the experiments proved that the proposed concepts are capable of minimising the problem currently faced in MANET intrusion detection system (IDS). Through a friendship mechanism, the problems of false accusations and false alarms caused by blackmail attackers in intrusion detection and response mechanisms can be eliminated.     

基于图论的MANET入侵检测方法

移动Ad hoc网络(MANET)易遭受各种安全威胁,入侵检测是其安全运行的有效保障,已有方法主要关注特征选择以及特征权重,而忽略特征间潜在关联性,针对此问题该文提出基于图论的MANET入侵检测方法。首先通过对典型攻击行为分析,合理选择9种特征作为节点,依据欧式距离确定节点间的边以构建结构图。其次发掘节点(即特征)间关联性,综合考虑节点邻居规模属性和节点邻居之间的紧密程度属性,利用图论所对应的统计特性度分布和聚集系数具体实现两属性。最后对比实验结果证明此方法与传统方法相比平均检测率和误检率分别提高10.15%、降低1.8%。