Secure Routing Research Articles

Secure Clustering and Routing using Adaptive Decision and Levy Flight based Artificial Hummingbird Algorithm for Wireless Sensor Networks

Wireless Sensor Network (WSN) receives huge attention from various remote monitoring applications because of its self configuration, ease of maintenance and scalability features. But, the sensors of the WSNs vulnerable to malicious attackers due to the energy constraint, open deployment and lack of centralized administration. Therefore, the secure routing is established for achieving the secure and reliable data broadcasting in the WSN. In this paper, an Adaptive Decision and Levy Flight based Artificial Hummingbird Algorithm (ADLFAHA) is proposed for performing an effective secure routing under the blackhole and Denial of Service (DoS) attacks. The ADLFAHA is developed to perform Secure Cluster Head (SCH) selection and secure path identification according to the trust, energy, load and communication cost. An adaptive decision strategy and levy flight incorporated in the ADLFAHA is used to enhance exploration and achieves global optimization capacity that helps to enhance the searching process. Moreover, the developed ADLFAHA helps to avoid the congestion among the nodes by balancing the load in network. The ADLFAHA is analyzed using End to End Delay (EED), throughput, Packet Delivery Ratio (PDR) and overhead. The existing researches such as Firebug Optimized Modified Bee Colony (FOMBC) and Lightweight Secure Routing (LSR) are used to compare the ADLFAHA. The PDR of the ADLFAHA for the simulation time of 100 s is 98.21 that is high than the FOMBC and LSR.

A Systematic Roadmap on Privacy, Security, Trust, Identity Management, and Resilience: Wireless Sensor Networks and Internet of Things Architectures

As everything around us will be linked to the net in many ways via the Internet of Things (IoTs) and compared to the standard Internet, new forms of problems and complications can arise. Huge IoTs experiments are currently under way, most of which concern its sight, supporting technology, software, or facilities. Recently, a limited studies have comprehensively defined the security requirements such as privacy concerns, security, and trusting in the IoTs that are deemed special to the future net, these terms need to be discussed and addressed via numerous scholars and research groups as well. This article surveyed through 102 references from popular literature databases to explore the features\ properties that define the distinctive IoT relating to forthcoming privacy, security and trust issues. Then created security requirements that were triggered by the mentioned properties. This article examined the privacy, security, trust and resilience components of the three most popular IoT architectures in consideration of the requirements as well. Also, this survey contributed to the state-of-the-art security issues for embedded devices in Internet of Things world including provide a comparative table of well-known secure routing protocols and their countermeasures to well-known attacks on Open Systems Interconnection (OSI) structure of Wireless Sensor Networks (WSNs) within Internet of Things world. Finally, this survey identifies a number of study gaps that will serve as the foundation for future research.

Evaluating the Advantages and Challenges of Mobile Ad-Hoc Networks

Mobile Ad-Hoc Networks (MANETs) are decentralized assemblies of mobile nodes, including smartphones, laptops, iPads, and PDAs, that operate autonomously, contrasting with conventional wireless networks. These networks dynamically adapt their topology and routing tables as nodes join or leave, ensuring a seamless data packet transmission. This article aims to provide a comprehensive overview of MANETs, elucidating their advantages, challenges, and diverse applications. Unlike traditional networks that require a centralized administrator, MANETs enable mobile nodes to exchange data packets solely through wireless links. However, the volatile topologies and limited resources challenge establishing a power-efficient and secure routing system. This study introduces a reliable routing mechanism considering network power consumption and node reputation. Utilizing a Krill Herd-based Grasshopper Optimization Algorithm (KH-GOA), in conjunction with a reputation model, the proposed system establishes a trustworthy route between the origin and destination nodes. The reputation model considers node mobility, actual capabilities, historical performance, and peer reviews. Upon evaluating these reputation metrics, the KH-GOA method is employed, amalgamating the Krill Herd (KH) and Grasshopper Optimization Algorithm (GOA) techniques. The proposed KH-GOA-based routing protocol considers multi-objective criteria like reputation, power efficiency, distance, and latency for optimal route selection.

Towards secure IoT system from a smart city perspective: An optimized algorithm and implementation

AbstractSecuring Internet of Things (IoT) systems is crucial for maintaining the resilience and trustworthiness of smart cities. In this context, the routing protocol's efficiency is pivotal for large‐scale IoT applications. However, achieving dependable and energy‐efficient routing in wireless sensor networks (WSNs) poses significant challenges due to limited and non‐rechargeable node energy resources. Also, traditional approaches often fell short of ensuring robust security and efficient data transmission. Hence, the purpose of this research was to address these shortcomings by introducing the Blowfish Honey‐Improved Spotted Hyena Optimization (BONY‐ISHO) protocol aimed at bolstering the security and efficiency of clustering and data routing in WSNs. Firstly, it introduces blockchain technology to establish secure and authenticated clustering, ensuring that only legitimate cluster heads and member nodes can participate. This innovation significantly enhances network security. Secondly, our protocol incorporates a hybrid Blowfish‐Honey cryptographic technique for data protection within the Area of Interest (AOI). This dual‐layer security approach, comprising Blowfish encryption and Honey encryption for key management, guarantees robust privacy and security. Thirdly, we have optimized data routing through the Improved Spotted Hyena Optimization (ISHO) algorithm, extending the network's lifetime and conserving energy resources. Performance evaluations confirm the superiority of the BONY‐ISHO protocol and existing solutions. It achieves a higher packet delivery ratio (99.8%), increased throughput (45 000 kbps), reduced energy consumption (1.68 joules), and minimized latency (0.068 sec) when compared to traditional methods. These performance enhancements make the BONY‐ISHO protocol a compelling choice for securing and optimizing IoT‐based WSNs. Our study concludes that the BONY‐ISHO protocol is a highly effective solution for addressing security and efficiency challenges in IoT‐based WSNs. By combining blockchain‐based authentication, hybrid cryptography, and intelligent routing algorithms, we have achieved a comprehensive enhancement of network security and data transmission efficiency. The protocol's ability to thwart malicious nodes and optimize routing pathways ensures the integrity and reliability of IoT‐based WSNs.

Secure routing in the Internet of Things (IoT) with intrusion detection capability based on software-defined networking (SDN) and Machine Learning techniques

Routing and security are the two main prerequisites for ensuring the correct operation of wireless networks. The importance of these cases doubles in wide networks such as IoT. This paper presents an algorithm to improve Secure Routing in IoT called SRAIOT. This algorithm uses a hierarchical structure to determine the connections between network components and data transfer routing. In SRAIOT, the network structure is managed hierarchically and through SDN. For this purpose, the IoT network is first divided into a set of subnets using the SDN solution, communication control and authentication are managed using the controller nodes of each subnet. The communication between two objects (located in different subnets) will be possible if their identity is confirmed through the controller nodes related to them. On the other hand, in order to identify the sources of attacks and network security threats, the controller nodes in each subnet monitor the network traffic pattern using an ensemble learning model and identify possible attacks in their subnet. The performance of SRAIOT was tested in the simulation, and the results were compared with previous methods. The results of these tests show that SRAIOT improves network performance regarding routing and detecting attacks.

Rpkiller: Threat Analysis of the BGP Resource Public Key Infrastructure

The Resource Public Key Infrastucture (RPKI) has been created to solve security shortcomings of the Border Gateway Protocol (BGP). This creates an infrastructure where resource holders (autonomous systems) can make attestations about their resources (IP-subnets). RPKI Certificate Authorities make these attestations available at Publication Points. Relying Party software retrieves and processes the RPKI-related data from all publication points, validates the data and makes it available to routers so they can make secure routing decisions. We contribute to this work by doing a threat analysis for Relying Party software, where an attacker controls a Certificate Authority and Publication Point. We implement a prototype testbed to analyse how current Relying Party software implementations react to scenarios originating from that threat model. Our results show that all current Relying Party software was susceptible to at least one of the identified threats. In addition to this, we also identified threats stemming from choices made in the protocol itself. Taken together, these threats potentially allowed an attacker to fully disrupt all RPKI Relying Party software on a global scale. We elaborate on our process, and we discuss the types of responses we received from other parties. We performed a Coordinated Vulnerability Disclosure to the implementers.

Satellite Network Security Routing Technology Based on Deep Learning and Trust Management.

The conventional trust model employed in satellite network security routing algorithms exhibits limited accuracy in detecting malicious nodes and lacks adaptability when confronted with unknown attacks. To address this challenge, this paper introduces a secure satellite network routing technology founded on deep learning and trust management. The approach embraces the concept of distributed trust management, resulting in all satellite nodes in this paper being equipped with trust management and anomaly detection modules for assessing the security of neighboring nodes. In a more detailed breakdown, this technology commences by preprocessing the communication behavior of satellite network nodes using D-S evidence theory, effectively mitigating interference factors encountered during the training of VAE modules. Following this preprocessing step, the trust vector, which has undergone prior processing, is input into the VAE module. Once the VAE module's training is completed, the satellite network can assess safety factors by employing the safety module during the collection of trust evidence. Ultimately, these security factors can be integrated with the pheromone component within the ant colony algorithm to guide the ants in discovering pathways. Simulation results substantiate that the proposed satellite network secure routing algorithm effectively counters the impact of malicious nodes on data transmission within the network. When compared to the traditional trust management model of satellite network secure routing algorithms, the algorithm demonstrates enhancements in average end-to-end delay, packet loss rate, and throughput.

Node authentication and encrypted data transmission in mobile ad hoc network using the swarm intelligence‐based secure ad‐hoc on‐demand distance vector algorithm

AbstractIn a mobile ad hoc network (MANET), all nodes are communicated with one another across wireless networks to create a temporary network without the support of centralised management. Due to dynamic topology in MANET, secure routing is a crucial issue. The existing secure routing protocol and their security concerns are analysed in this work. The suggested Swarm Intelligence‐based Secure Ad‐hoc On‐demand Distance Vector (SIS‐AODV) algorithm offers security by applying a secret key and hash mechanism to prevent the involvement of malicious nodes in routing operations. A secure routing system of MANET guards against internal and external network attacks. The proposed SIS‐AODV algorithm consists of two sections: the secret key value generated by applying Elliptical Curve Cryptography (ECC)‐based algorithm and the PRESENT algorithm to encrypt the data packets. Besides, authentication and non‐repudiation are applied using the H‐PRESENT 128 algorithm. The PRESENT algorithm and H‐PRESENT 128 hash function require less computational power. Centralised management is optional in this scheme, so overhead decreases. The second section of SIS‐AODV consists of Ant Colony Grey Wolf Optimization over the AODV algorithm to improve network performance while implementing a security algorithm over MANET. Analysis results show maximum performance with a packet delivery ratio of 98% and throughput of 85%. In addition, end‐to‐end delay is reduced by up to 25%, and routing overhead decreases by up to 20%. Keywords: AODV, Elliptical Curve, PRESENT, H‐PRESENT, Euclidean Algorithm, ACO, GWO, Blackhole attack.

Cluster head based secure routing using optimized dual-discriminator conditional generative adversarial network in wireless ad-hoc networks

Cluster head based secure routing using optimized dual-discriminator conditional generative adversarial network in wireless ad-hoc networks

Improve the quality of service through secure routing networks secured in the mail

A mobile ad hoc network (MANET) is a stand-alone system with mobile nodes. Nodes can move around at will. Communication is subject to security breaches without a centralized, secure infrastructure, and the nodes are the biggest offenders. Since security has become one of the most important issues for data transfer via wired and wireless networks, many security-enhanced solutions have been created to enhance the security of data transmission over public networks. The goal of this project is to make routing safer. Proactive routing, as is well known, involves finding alternative routes and requiring packets to choose one at random from their immediate neighbors. Sending hello packets allows us to maintain track of each node's neighbors. The delivery path is then selected from nearby nodes, with the prior hop which is retained as the history node having been arbitrarily excluded. To randomize delivery channels, the proactive routing protocols DSDV and RDSDV were contrasted for various node counts. The Simulation employs this project. The rapid development of mobile computing appli-cations and distant systems has raised awareness of quality of service (QoS) for mobile ad hoc networks (MANETs). In the MANET sce-nario, security is a key component of Qos provisioning. Attacks on the system could result in problems with direction, asset reservations, or even the collapse of the QoS structure if no security tool is used. In this study, two new plans will be provided from the perspectives of two alternative techniques to manage the updating of the organizational idea and allay the worries caused by interface annoyances in order to handle the security challenges of MANET Qos and the actual commitments of this investigation.

Hybrid trust-based secure routing protocol for detection of routing attacks in environment monitoring over MANETs

Maintaining a healthy environment requires constant vigilance. Keeping constant tabs on environmental factors might be a useful tool in the fight against and recovery from environmental degradation. It is possible to send environmental data from strategically positioned sensors that monitor the surrounding circumstances. Environmentalists are the first to arrive at a disaster site, assess the situation, and take corrective measures. To get information from the sensors, they must coordinate with one another. Remote environmental sensing, the tracking from several physical systems, as well as risk assessment and management, have all seen significant improvements as a result of the use of these networks, which are comprised of many dispersed devices, each of which includes sensing, processing, and wireless technology capabilities. To facilitate communication between sensors and ecologists, the authors of this research suggest the usage of MANETs. To address these issues, a hybrid trust-based secure routing protocol is designed. Firstly, nodes are clustered using the Skill Optimization Technique. The Direct and Indirect (Hybrid) trust is computed using the Deep Q-Learning technique and then Routing is established using Diffusion Convolutional Neural Networks. With these methods, routing attacks such as Black Hole, Gray hole, and Wormhole attacks are identified and compared with the traditional security protocols using network simulation tools.

A Deep-Learning-Based Secure Routing Protocol to Avoid Blackhole Attacks in VANETs.

Vehicle ad hoc networks (VANETs) are a vital part of intelligent transportation systems (ITS), offering a variety of advantages from reduced traffic to increased road safety. Despite their benefits, VANETs remain vulnerable to various security threats, including severe blackhole attacks. In this paper, we propose a deep-learning-based secure routing (DLSR) protocol using a deep-learning-based clustering (DLC) protocol to establish a secure route against blackhole attacks. The main features and contributions of this paper are as follows. First, the DLSR protocol utilizes deep learning (DL) at each node to choose secure routing or normal routing while establishing secure routes. Additionally, we can identify the behavior of malicious nodes to determine the best possible next hop based on its fitness function value. Second, the DLC protocol is considered an underlying structure to enhance connectivity between nodes and reduce control overhead. Third, we design a deep neural network (DNN) model to optimize the fitness function in both DLSR and DLC protocols. The DLSR protocol considers parameters such as remaining energy, distance, and hop count, while the DLC protocol considers cosine similarity, cosine distance, and the node's remaining energy. Finally, from the performance results, we evaluate the performance of the proposed routing and clustering protocol in the viewpoints of packet delivery ratio, routing delay, control overhead, packet loss ratio, and number of packet losses. Additionally, we also exploit the impact of the mobility model such as reference point group mobility (RPGM) and random waypoint (RWP) on the network metrics.

A secure routing approach based on league championship algorithm for wireless body sensor networks in healthcare.

Patients must always communicate with their doctor for checking their health status. In recent years, wireless body sensor networks (WBSNs) has an important contribution in Healthcare. In these applications, energy-efficient and secure routing is really critical because health data of individuals must be forwarded to the destination securely to avoid unauthorized access by malicious nodes. However, biosensors have limited resources, especially energy. Recently, energy-efficient solutions have been proposed. Nevertheless, designing lightweight security mechanisms has not been stated in many schemes. In this paper, we propose a secure routing approach based on the league championship algorithm (LCA) for wireless body sensor networks in healthcare. The purpose of this scheme is to create a tradeoff between energy consumption and security. Our approach involves two important algorithms: routing process and communication security. In the first algorithm, each cluster head node (CH) applies the league championship algorithm to choose the most suitable next-hop CH. The proposed fitness function includes parameters like distance from CHs to the sink node, remaining energy, and link quality. In the second algorithm, we employs a symmetric encryption strategy to build secure connection links within a cluster. Also, we utilize an asymmetric cryptography scheme for forming secure inter-cluster connections. Network simulator version 2 (NS2) is used to implement the proposed approach. The simulation results show that our method is efficient in terms of consumed energy and delay. In addition, our scheme has good throughput, high packet delivery rate, and low packet loss rate.

A secure routing protocol using hybrid deep regression based trust evaluation and clustering for mobile ad-hoc network

A secure routing protocol using hybrid deep regression based trust evaluation and clustering for mobile ad-hoc network

Trust based multi objective honey badger algorithm to secure routing in vehicular ad-hoc networks

<span lang="EN-US">A vehicular ad-hoc network (VANET) is a set of intelligent vehicles that interact without any fixed infrastructure. Data transmission between each transmitter/receiver pair is accomplished using routing protocols. However, communication over the VANET is vulnerable to malicious attacks, because of the unavailability of fixed infrastructure and wireless communication. In this paper, the trust based multi objective honey badger algorithm (TMOHBA) is proposed to achieve secure routing over the VANET. The TMOHBA is optimized by incorporating different cost functions, namely, trust, end to end delay (EED), routing overhead, energy, and distance. The developed secure route discovery using the TMOHBA is used to improve the robustness against the malicious attacks, for increasing the data delivery. Moreover, the shortest path discovery is used to minimize the delay while improving the security of VANET. The TMOHBA method is evaluated using the packet delivery ratio (PDR), throughput and EED. Existing researches such as hybrid enhanced glowworm swarm optimization (HEGSO) and ad-hoc on-demand distance vector based secure protocol (AODV-SP) are used to evaluate the TMOHBA method. The PDR of the TMOHBA method for 10 malicious attacks is 90.6446% which is higher when compared to the HEGSO and AODV-SP.</span>

MO-CBACORP: A new energy-efficient secure routing protocol for underwater monitoring wireless sensor network

With the rapid progress of sensor technology, underwater monitoring wireless sensor network (UMWSN) equipped with water resource monitoring capabilities have surfaced. UMWSN is currently emerging as a popular research and application area, with a wide range of applications in various fields, including but not limited to disaster warning, pollutant monitoring and hydrological data monitoring. However, due to the limited size and computing power of wireless sensors, UMWSN are exceedingly susceptible to network security attacks by contaminating entities. In order to tackle the problems of inadequate security, elevated network energy consumption, and high system latency in existing QoS routing research, this paper puts forward an innovative multi-objective routing protocol named multi-objective chaotic Boltzmann ant colony optimization routing protocol (MO-CBACORP). MO-CBACORP can minimize the energy consumption of sensor nodes in UMWSN routing, thereby effectively diminishing system latency and significantly enhancing routing security. During the routing optimization process, MO-CBACORP proposed an innovative design of the chaos operator and Boltzmann selection strategy, which effectively avoids the issue of being stuck in local optimal solutions and greatly enhances the convergence speed of the algorithm. Additionally, a novel experiment for underwater monitoring environments is presented that precisely replicates underwater monitoring conditions and attack scenarios. According to the experimental results, MO-CBACORP exhibits superior performance compared to the latest state-of-the-art research including THOA-MHR, ACO-MCMC, and MAP-ACO, with a minimum improvement of 7.25%, 9.31%, and 7.68% in terms of route security, network energy consumption, and delay, respectively. All in all, MO-CBACORP exhibits superior performance compared to the three latest research algorithms.

Fast and Secure Routing Algorithms for Quantum Key Distribution Networks

We investigate the problem of fast and secure packet routing in multi-hop Quantum Key Distribution (QKD) networks. We consider a practical trusted-node setup where a QKD protocol randomly generates symmetric private key pairs over each QKD-enabled link in a network. Packets are first encrypted with the available quantum keys and then transmitted on a point-to-point basis. A fundamental problem in this setting is the design of a secure and capacity-achieving routing policy that takes into account the time-varying availability of the encryption keys and diverse physical-layer link capacities. To address this problem, we propose a new secure throughput-optimal policy called Tandem Queue Decomposition (TQD). The TQD policy is designed by incorporating the QKD process into the Universal Max Weight (UMW) routing policy. We show that the TQD policy achieves the entire secure capacity region for a broad class of traffic, including unicast, broadcast, multicast, and anycast. The TQD policy operates by reducing the problem to the generalized network flow problem without the key availability constraints over a transformed network. The throughput-optimality of the TQD policy is established using the Lyapunov stability theory by carefully analyzing the interdependent queueing process and the key-storage dynamics. Finally, we demonstrate the practical efficiency of the TQD policy over the existing routing algorithms by numerically comparing their performance on a realistic simulator built on top of the state-of-the-art OMNeT++ network simulator platform.

Enhancing Security in Mobile Ad Hoc Networks: Enhanced Particle Swarm Optimization-driven Intrusion Detection and Secure Routing Algorithm

Wireless technologies have grown in popularity and are used in many applications. Transient Mobile Ad hoc Networks (MANETs) serve specific goals without infrastructure. The dynamism of these networks makes them useful for ubiquitous computing. However, high mobility, the lack of a centralized authority, and open media make MANETs vulnerable to various security risks. Thus, an Intrusion Detection System (IDS) should be used to monitor and detect system security issues. To prevent and improve security against unauthorized access, intrusion screening is crucial. The depletion of a mobile node's power supply can impact its capacity to transmit packets, as this functionality is contingent upon the system's overall lifespan. Computational Optimization-driven solutions have been prevalent in the context of IDS and secure routing inside MANETs. This research employs the Enhanced Particle Swarm Optimization-driven Intrusion Detection and Secure Routing Algorithm (EPSO-IDSRA). Enhanced Particle Swarm Optimization technique (EPSO) has provided confidence-based, secure, and energy-efficient routing in MANETs. The EPSO technique is applied to identify optimal hops for enhancing the routing process. The initial step involves the activation of the fuzzy clustering algorithm, followed by selecting Cluster Heads (CHs) based on assessing their indirect, direct, and recent confidence values. Furthermore, the identification of value nodes was contingent upon assessing confidence levels. Also, the CHs are involved in multi-hop routing, and determining the optimal route depends on the anticipated protocol, which chooses the most favorable paths considering factors such as latency, throughput, and connectivity within the designated area. The EPSO method, presented for secure routing (at time 50ms), yielded an optimal energy consumption of 0.15 millijoules, a minimal delay of 0.008 milliseconds, a maximum throughput of 0.8 bits per second, and an 89% detection rate.

ADAPTIVE SECURE AND EFFICIENT ROUTING PROTOCOL FOR ENHANCE THE PERFORMANCE OF MOBILE AD HOC NETWORK

Nowadays Mobile Ad Hoc Network (MANET) is an emerging area of research to provide various communication services to end users. Mobile Ad Hoc Networks (MANETs) are self-organizing wireless networks where nodes communicate with each other without a fixed infrastructure. Due to their unique characteristics, such as mobility, autonomy, and ad hoc connectivity, MANETs have become increasingly popular in various applications, including military, emergency response, and disaster management. However, the lack of infrastructure and dynamic topology of MANETs pose significant challenges to designing a secure and efficient routing protocol. This paper proposes an adaptive, secure, and efficient routing protocol that can enhance the performance of MANET. The proposed protocol incorporates various security mechanisms, including authentication, encryption, key management, and intrusion detection, to ensure secure routing. Additionally, the protocol considers energy consumption, network load, packet delivery fraction, route acquisition latency, packets dropped and Quality of Service (QoS) requirements of the applications to optimize network performance. Overall, the secure routing protocol for MANET should provide a reliable and secure communication environment that can adapt to the dynamic nature of the network. The protocol should ensure that messages are delivered securely and efficiently to the intended destination, while minimizing the risk of attacks and preserving the network resources Simulation results demonstrate that the proposed protocol outperforms existing routing protocols in terms of network performance and security. The proposed protocol can facilitate the deployment of various applications in MANET while maintaining security and efficiency.

Retracted: A Secure Routing Protocol for Wireless Sensor Energy Network Based on Trust Management

Retracted: A Secure Routing Protocol for Wireless Sensor Energy Network Based on Trust Management