Biblio

With the rapid growth of the number of global network entities and interconnections, the security risks of network relationships are constantly accumulating. As the basis of network interconnection and communication, Internet routing is facing severe challenges such as insufficient online monitoring capability of large-scale routing events and lack of effective and credible verification mechanism. Major global routing security events emerge one after another, causing extensive and far-reaching impacts. To solve these problems, China Telecom studied the BGP (border gateway protocol) SDN (software defined network) controller technology to monitor the interconnection routing, constructed the global routing information database trust source integrating multi-dimensional information and developed the function of the protocol level based real-time monitoring system of Internet routing security events. Through these means, it realizes the second-level online monitoring capability of large-scale IP network Internet service routing events, forms the minute-level route leakage interception and route hijacking blocking solutions, and achieves intelligent protection capability of Internet routing security.

Fuzzing is a popular technique for finding soft-ware vulnerabilities. Despite their success, the state-of-art fuzzers will inevitably produce a large number of low-quality inputs. In recent years, Machine Learning (ML) based selection strategies have reported promising results. However, the existing ML-based fuzzers are limited by the lack of training data. Because the mutation strategy of fuzzing can not effectively generate useful input, it is prohibitively expensive to collect enough inputs to train models. In this paper, propose a generative adversarial networks based solution to generate a large number of inputs to solve the problem of insufficient data. We implement the proposal in the American Fuzzy Lop (AFL), and the experimental results show that it can find more crashes at the same time compared with the original AFL.

The correctness of user traffic forwarding paths is an important goal of trusted transmission. Many network security issues are related to it, i.e., denial-of-service attacks, route hijacking, etc. The current path-aware network architecture can effectively overcome this issue through path verification. At present, the main problems of path verification are high communication and high computation overhead. To this aim, this article proposes a lightweight real-time verification mechanism of intradomain forwarding paths in autonomous systems to achieve a path verification architecture with no communication overhead and low computing overhead. The problem situation is that a packet finally reaches the destination, but its forwarding path is inconsistent with the expected path. The expected path refers to the packet forwarding path determined by the interior gateway protocols. If the actual forwarding path is different from the expected one, it is regarded as an incorrect forwarding path. This article focuses on the most typical intradomain routing environment. A few routers are set as the verification routers to block the traffic with incorrect forwarding paths and raise alerts. Experiments prove that this article effectively solves the problem of path verification and the problem of high communication and computing overhead.

In Wireless Sensor Networks (WSNs), energy and security are two critical concerns that must be addressed. Because of the scarcity of energy, several security measures are restricted. For secure data routing in WSN, it becomes vital to identify insider packet drop attacks. The trust mechanism is an effective strategy for detecting this assault. Each node in this system validates the trustworthiness of its neighbors before transmitting packets, ensuring that only trust-worthy nodes get packets. With such a trust-aware scheme, however, there is a risk of false alarm. This work develops an adaptive trust computation model (TCM)which is implemented in our already proposed Chimp Optimization Algorithm-based Energy-Aware Secure Routing Protocol (COA-EASRP) for WSN. The proposed technique computes the optimal path using the hybrid combination of COA-EASRP and AODV as well as TCM is used to indicate false alarms in detecting selfish nodes. Our Proposed approach provides the series of Simulation outputs carried out based on various parameters

Multi-active bridge (MAB) converter has played an important role in the power conversion of renewable-based smart grids, electrical vehicles, and more/all electrical aircraft. However, the increase of MAB submodules greatly complicates the control architecture. In this regard, the conventional centralized control strategies, which rely on a single controller to process all the information, will be limited by the computation burden. To overcome this issue, this paper proposes a decentralized power management strategy for MAB converter. The switching frequencies of MAB submodules are adaptively regulated based on the submodule local information. Through this effort, flexible electrical power routing can be realized without communications among submodules. The proposed methodology not only relieves the computation burden of MAB control system, but also improves its modularity, flexibility, and expandability. Finally, the experiment results of a three-module MAB converter are presented for verification.

With the advent of the 5G era, high-speed and secure network access services have become a common pursuit. The QUIC (Quick UDP Internet Connection) protocol proposed by Google has been studied by many scholars due to its high speed, robustness, and low latency. However, the research on the security of the QUIC protocol by domestic and foreign scholars is insufficient. Therefore, based on the self-similarity of QUIC network traffic, combined with traffic characteristics and signal processing methods, a QUIC-based network traffic anomaly detection model is proposed in this paper. The model decomposes and reconstructs the collected QUIC network traffic data through the Empirical Mode Decomposition (EMD) method. In order to judge the occurrence of abnormality, this paper also intercepts overlapping traffic segments through sliding windows to calculate Hurst parameters and analyzes the obtained parameters to check abnormal traffic. The simulation results show that in the network environment based on the QUIC protocol, the Hurst parameter after being attacked fluctuates violently and exceeds the normal range. It also shows that the anomaly detection of QUIC network traffic can use the EMD method.

With the development of computer technology and information security technology, computer networks will increasingly become an important means of information exchange, permeating all areas of social life. Therefore, recognizing the vulnerabilities and potential threats of computer networks as well as various security problems that exist in reality, designing and researching computer quality architecture, and ensuring the security of network information are issues that need to be resolved urgently. The purpose of this article is to study the design and realization of information security technology and computer quality system structure. This article first summarizes the basic theory of information security technology, and then extends the core technology of information security. Combining the current status of computer quality system structure, analyzing the existing problems and deficiencies, and using information security technology to design and research the computer quality system structure on this basis. This article systematically expounds the function module data, interconnection structure and routing selection of the computer quality system structure. And use comparative method, observation method and other research methods to design and research the information security technology and computer quality system structure. Experimental research shows that when the load of the computer quality system structure studied this time is 0 or 100, the data loss rate of different lengths is 0, and the correct rate is 100, which shows extremely high feasibility.

Cognitive Radio (CR) is an attractive solution in mobile communication for solving the spectrum scarcity problem. Moreover, security concerns are not yet fully satisfied. This article focuses on attacks such as the Primary user emulation attack (PUE) and the jammer attack. These attacks create anomalous spectrum access thereby disturbing the dynamic spectrum usage in the CR networks. A framework based on cross-layer has been designed effectively to determine these attacks in the CR networks. First, each secondary user will sense the spectrum in the physical layer and construct a feature space. Using the extracted features, the clusters are formed effectively for each user. In the network layer, multipath routing is employed to discover the routes for the secondary user. If the node in the path identifies any spectrum shortage, it will verify that location with the help of constructed cluster. If the node does not belong to any of the clusters, then it will be identified as the attacker node. Simulation results and security analysis are performed using the NS2 simulations, which show improvement in detection of the attacks, decrease in the detection delay, and less route dis-connectivity. The proposed cross-layer framework identifies the anomalous spectrum access attack effectively.

Key challenges faced in the Internet today can be enumerated as follows: (1) complex route discovery mechanisms (2) latency and instability during link or device failure recovery (3) inadequacy in extending routing and addressing to limited domains, (4) complex interworking of multiple routing protocols at border routers. Routing table sizes increase with increasing number of networks indicating a scalability issue. One approach to address this spiraling complexity and performance challenges is to start fresh and re-think Internet routing and addressing. The Expedited Internet Bypass protocol (EIBP) is such a clean slate approach. In the interim, EIBP works in parallel with IP and has no dependency on layer 3 protocols. We demonstrated EIBP for routing and forwarding in an Autonomous system (AS) in our earlier work. In this article, we demonstrate EIBP for inter-AS routing. We compare EIBP's inter-AS operations and performance to Open Shortest Path First (OSPF) and Border Gateway Protocol (BGP) deployed in an intra-AS, inter-AS communications scenario with two AS.

Ant Colony Optimization is applied to design a suitable and shortest route between the starting node point and the end node point in the Wireless Sensor Network (WSN). In general ant colony algorithm plays a good role in path planning process that can also applied in improving the network security. Therefore to protect the network from the malicious nodes an ACO based Dynamic Key Management (ACO-DKM) scheme is proposed. The routes are diagnosed through ACO method also the actual coverage distance and pheromone updating strategy is updated simultaneously that prevents the node from continuous monitoring. Simulation analysis gives the efficiency of the proposed scheme.

Wireless Sensor Networks (WSN) have assisted applications of multi-agent system. Abundant sensor nodes, densely distributed around a base station (BS), collect data and transmit to BS node for data analysis. The concept of cluster has been emerged as the efficient communication structure in resource-constrained environment. However, the security still remains a major concern due to the vulnerability of sensor nodes. In this paper, we propose a percolation-based secure routing protocol. We leverage the trust score composed of three indexes to select cluster heads (CH) for unevenly distributed clusters. By considering the reliability, centrality and stability, legitimate nodes with social trust and adequate energy are chosen to provide relay service. Moreover, we design a multi-path inter-cluster routing protocol to construct CH chains for directed inter-cluster data transmission based on the percolation. And the measurement of transit score for on-path CH nodes contributes to load balancing and security. Our simulation results show that our protocol is able to guarantee the security to improve the delivery ratio and packets delay.

In case of deploying additional network security equipment in a new location, network service providers face difficulties such as precise management of large number of network security equipment and expensive network operation costs. Accordingly, there is a need for a method for security-aware network service provisioning using the existing network security equipment. In order to solve this problem, there is an existing reinforcement learning-based routing decision method fixed for each node. This method performs repeatedly until a routing decision satisfying end-to-end security constraints is achieved. This generates a disadvantage of longer network service provisioning time. In this paper, we propose security constraints reinforcement learning based routing (SCRR) algorithm that generates routing decisions, which satisfies end-to-end security constraints by giving conditional reward values according to the agent state-action pairs when performing reinforcement learning.

The phenomenon known as "Internet ossification" describes the process through which certain components of the Internet’s older design have become immovable at the present time. This presents considerable challenges to the adoption of IPv6 and makes it hard to implement IP multicast services. For new applications such as data centers, cloud computing and virtualized networks, improved network availability, improved internal and external domain routing, and seamless user connectivity throughout the network are some of the advantages of Internet growth. To meet these needs, we've developed Software Defined Networking for the Future Internet (SDN). When compared to current networks, this new paradigm emphasizes control plane separation from network-forwarding components. To put it another way, this decoupling enables the installation of control plane software (such as Open Flow controller) on computer platforms that are substantially more powerful than traditional network equipment (such as switches/routers). This research describes Mininet’s routing techniques for a virtualized software-defined network. There are two obstacles to overcome when attempting to integrate SDN in an LTE/WiFi network. The first problem is that external network load monitoring tools must be used to measure QoS settings. Because of the increased demand for real-time load balancing methods, service providers cannot adopt QoS-based routing. In order to overcome these issues, this research suggests a router configuration method. Experiments have proved that the network coefficient matrix routing arrangement works, therefore it may provide an answer to the above-mentioned concerns. The Java-based SDN controller outperforms traditional routing systems by nine times on average highest sign to sound ratio. The study’s final finding suggests that the field’s future can be forecast. We must have a thorough understanding of this emerging paradigm to solve numerous difficulties, such as creating the Future Internet and dealing with its obliteration problem. In order to address these issues, we will first examine current technologies and a wide range of current and future SDN projects before delving into the most important issues in this field in depth.

The security of manycore systems has become increasingly critical. In system-on-chips (SoCs), Hardware Trojans (HTs) manipulate the functionalities of the routing components to saturate the on-chip network, degrade performance, and result in the leakage of sensitive data. Existing HT detection techniques, including runtime monitoring and state-of-the-art learning-based methods, are unable to timely and accurately identify the implanted HTs, due to the increasingly dynamic and complex nature of on-chip communication behaviors. We propose AGAPE, a novel Generative Adversarial Network (GAN)-based anomaly detection and mitigation method against HTs for secured on-chip communication. AGAPE learns the distribution of the multivariate time series of a number of NoC attributes captured by on-chip sensors under both HT-free and HT-infected working conditions. The proposed GAN can learn the potential latent interactions among different runtime attributes concurrently, accurately distinguish abnormal attacked situations from normal SoC behaviors, and identify the type and location of the implanted HTs. Using the detection results, we apply the most suitable protection techniques to each type of detected HTs instead of simply isolating the entire HT-infected router, with the aim to mitigate security threats as well as reducing performance loss. Simulation results show that AGAPE enhances the HT detection accuracy by 19%, reduces network latency and power consumption by 39% and 30%, respectively, as compared to state-of-the-art security designs.

As a result of the inherent weaknesses of the wireless medium, ad hoc networks are susceptible to a broad variety of threats and assaults. As a direct consequence of this, intrusion detection, as well as security, privacy, and authentication in ad-hoc networks, have developed into a primary focus of current study. This body of research aims to identify the dangers posed by a variety of assaults that are often seen in wireless ad-hoc networks and provide strategies to counteract those dangers. The Black hole assault, Wormhole attack, Selective Forwarding attack, Sybil attack, and Denial-of-Service attack are the specific topics covered in this thesis. In this paper, we describe a trust-based safe routing protocol with the goal of mitigating the interference of black hole nodes in the course of routing in mobile ad-hoc networks. The overall performance of the network is negatively impacted when there are black hole nodes in the route that routing takes. As a result, we have developed a routing protocol that reduces the likelihood that packets would be lost as a result of black hole nodes. This routing system has been subjected to experimental testing in order to guarantee that the most secure path will be selected for the delivery of packets between a source and a destination. The invasion of wormholes into a wireless network results in the segmentation of the network as well as a disorder in the routing. As a result, we provide an effective approach for locating wormholes by using ordinal multi-dimensional scaling and round trip duration in wireless ad hoc networks with either sparse or dense topologies. Wormholes that are linked by both short route and long path wormhole linkages may be found using the approach that was given. In order to guarantee that this ad hoc network does not include any wormholes that go unnoticed, this method is subjected to experimental testing. In order to fight against selective forwarding attacks in wireless ad-hoc networks, we have developed three different techniques. The first method is an incentive-based algorithm that makes use of a reward-punishment system to drive cooperation among three nodes for the purpose of vi forwarding messages in crowded ad-hoc networks. A unique adversarial model has been developed by our team, and inside it, three distinct types of nodes and the activities they participate in are specified. We have shown that the suggested strategy that is based on incentives prohibits nodes from adopting an individualistic behaviour, which ensures collaboration in the process of packet forwarding. To guarantee that intermediate nodes in resource-constrained ad-hoc networks accurately convey packets, the second approach proposes a game theoretic model that uses non-cooperative game theory. This model is based on the idea that game theory may be used. This game reaches a condition of desired equilibrium, which assures that cooperation in multi-hop communication is physically possible, and it is this state that is discovered. In the third algorithm, we present a detection approach that locates malicious nodes in multihop hierarchical ad-hoc networks by employing binary search and control packets. We have shown that the cluster head is capable of accurately identifying the malicious node by analysing the sequences of packets that are dropped along the path leading from a source node to the cluster head. A lightweight symmetric encryption technique that uses Binary Playfair is presented here as a means of safeguarding the transport of data. We demonstrate via experimentation that the suggested encryption method is efficient with regard to the amount of energy used, the amount of time required for encryption, and the memory overhead. This lightweight encryption technique is used in clustered wireless ad-hoc networks to reduce the likelihood of a sybil attack occurring in such networks

Metaverse technologies depend on various advanced human-computer interaction (HCI) devices to be supported by extended reality (XR) technology. Many new HCI devices are supported by wireless Internet of Things (IoT) networks, where a reliable routing scheme is essential for seamless data trans-mission. Routing Protocol for Low power and Lossy networks (RPL) is a key routing technology used in IPv6-based low power and lossy networks (LLNs). However, in the networks that are configured, such as small wireless devices applying the IEEE 802.15.4 standards, due to the lack of a system that manages the identity (ID) at the center, the maliciously compromised nodes can make fabricated IDs and pretend to be a legitimate node. This behavior is called Sybil attack, which is very difficult to respond to since attackers use multiple fabricated IDs which are legally disguised. In this paper, Sybil attack countermeasures on RPL-based networks published in recent studies are compared and limitations are analyzed through simulation performance analysis.

In the IoT (Internet of Things) domain, it is still a challenge to modify the routing behavior of IoT traffic at the decentralized backbone network. In this paper, centralized and flexible software-defined networking (SDN) is utilized to route the IoT traffic. The management of IoT data transmission through the SDN core network gives the chance to choose the path with the lowest delay, minimum packet loss, or hops. Therefore, fault-tolerant delay awareness routing is proposed for the emulated SDN-based backbone network to handle delay-sensitive IoT traffic. Besides, the hybrid form of GNS3 and Mininet-WiFi emulation is introduced to collaborate the SDN-based backbone network in GNS3 and the 6LoWPAN (IPv6 over Low Power Personal Area Network) sensor network in Mininet-WiFi.

Although 6LoWPAN has brought about a revolutionary leap in networking for Low-power Lossy Networks, challenges still exist, including security concerns that are yet to answer. The most common type of attack on 6LoWPANs is the network layer, especially routing attacks, since the very members of a 6LoWPAN network have to carry out packet forwarding for the whole network. According to the initial purpose of IoT, these nodes are expected to be resource-deficient electronic devices with an utterly stochastic time pattern of attachment or detachment from a network. This issue makes preserving their authenticity or identifying their malignity hard, if not impossible. Since 6LoWPAN is a successor and a hybrid of previously developed wireless technologies, it is inherently prone to cyber-attacks shared with its predecessors, especially Wireless Sensor Networks (WSNs) and WPANs. On the other hand, multiple attacks have been uniquely developed for 6LoWPANs due to the unique design of the network layer protocol of 6LoWPANs known as RPL. While there exist publications about attacks on 6LoWPANs, a comprehensive survey exclusively on RPL-specific attacks is felt missing to bold the discrimination between the RPL-specific and non-specific attacks. Hence, the urge behind this paper is to gather all known attacks unique to RPL in a single volume.

Low-Power and Lossy Networks (LLNs) run on resource-constrained devices and play a key role in many Industrial Internet of Things and Cyber-Physical Systems based applications. But, achieving an energy-efficient routing in LLNs is a major challenge nowadays. This challenge is addressed by Routing Protocol for Low-power Lossy Networks (RPL), which is specified in RFC 6550 as a “Proposed Standard” at present. In RPL, a client node uses Destination Advertisement Object (DAO) control messages to pass on the destination information towards the root node. An attacker may exploit the DAO sending mechanism of RPL to perform a DAO Insider attack in LLNs. In this paper, it is shown that an aggressive attacker can drastically degrade the network performance. To address DAO Insider attack, a lightweight defense solution is proposed. The proposed solution uses an early blacklisting strategy to significantly mitigate the attack and restore RPL performance. The proposed solution is implemented and tested on Cooja Simulator.

The Internet of Things (IoT) is a technology that has evolved to make day-to-day life faster and easier. But with the increase in the number of users, the IoT network is prone to various security and privacy issues. And most of these issues/attacks occur during the routing of the data in the IoT network. Therefore, for secure routing among resource-constrained nodes of IoT, the RPL protocol has been standardized by IETF. But the RPL protocol is also vulnerable to attacks based on resources, topology formation and traffic flow between nodes. The attacks like DoS, Blackhole, eavesdropping, flood attacks and so on cannot be efficiently defended using RPL protocol for routing data in IoT networks. So, defense mechanisms are used to protect networks from routing attacks. And are classified into Secure Routing Protocols (SRPs) and Intrusion Detection systems (IDs). This paper gives an overview of the RPL attacks and the defense mechanisms used to detect or mitigate the RPL routing attacks in IoT networks.

The most widely used protocol for routing across the 6LoWPAN stack is the Routing Protocol for Low Power and Lossy (RPL) Network. However, the RPL lacks adequate security solutions, resulting in numerous internal and external security vulnerabilities. There is still much research work left to uncover RPL's shortcomings. As a result, we first implement the worst parent selection (WPS) attack in this paper. Second, we offer an intrusion detection system (IDS) to identify the WPS attack. The WPS attack modifies the victim node's objective function, causing it to choose the worst node as its preferred parent. Consequently, the network does not achieve optimal convergence, and nodes form the loop; a lower rank node selects a higher rank node as a parent, effectively isolating many nodes from the network. In addition, we propose DWA-IDS as an IDS for detecting WPS attacks. We use the Contiki-cooja simulator for simulation purposes. According to the simulation results, the WPS attack reduces system performance by increasing packet transmission time. The DWA-IDS simulation results show that our IDS detects all malicious nodes that launch the WPS attack. The true positive rate of the proposed DWA-IDS is more than 95%, and the detection rate is 100%. We also deliberate the theoretical proof for the false-positive case as our DWA-IDS do not have any false-positive case. The overhead of DWA-IDS is modest enough to be set up with low-power and memory-constrained devices.

The “Internet of Things” (IoT) is internetworking of physical devices known as 'things', algorithms, equipment and techniques that allow communication with another device, equipment and software over the network. And with the advancement in data communication, every device must be connected via the Internet. For this purpose, we use resource-constrained sensor nodes for collecting data from homes, offices, hospitals, industries and data centers. But various vulnerabilities may ruin the functioning of the sensor nodes. Routing Protocol for Low Power and Lossy Networks (RPL) is a standardized, secure routing protocol designed for the 6LoWPAN IoT network. It's a proactive routing protocol that works on the destination-oriented topology to perform safe routing. The Sinkhole is a networking attack that destroys the topology of the RPL protocol as the attacker node changes the route of all the traffic in the IoT network. In this paper, we have given a survey of Sinkhole attacks in IoT and proposed different methods for preventing and detecting these attacks in a low-power-based IoT network.

The “Internet of Things (IoT)” is a term that describes physical sensors, processing software, power and other technologies to connect or interchange information between systems and devices through the Internet and other forms of communication. RPL protocol can efficiently establish network routes, communicate routing information, and adjust the topology. The 6LoWPAN concept was born out of the belief that IP should protect even the tiniest devices, and for low-power devices, minimal computational capabilities should be permitted to join IoT. The DIS-Flooding against RPL-based IoT with its mitigation techniques are discussed in this paper.

As a large number of sensor nodes as well as limited resources such as energy, memory, computing power, as well as bandwidth. Lossy linkages connect these nodes together. In early 2008,IETF working group looked into using current routing protocols for LLNs. Routing Over minimum power and Lossy networksROLL standardizes an IPv6 routing solution for LLNs because of the importance of LLNs in IoT.IPv6 Routing Protocol is based on the 6LoWPAN standard. RPL has matured significantly. The research community is becoming increasingly interested in it. The topology of RPL can be built in a variety of ways. It creates a topology in advance. Due to the lack of a complete review of RPL, in this paper a mobility management framework has been proposed along with experimental evaluation by applying parameters likePacket Delivery Ratio, throughput, end to end delay, consumed energy on the basis of the various parameters and its analysis done accurately. Finally, this paper can help academics better understand the RPL and engage in future research projects to improve it.

The aim of this paper is to describe the battery lifetime estimation and energy consumption model of the sensor nodes in TDMA wireless mesh sensor using merged data collecting (MDC) methods based on lithium thionyl chloride batteries. Defining the energy consumption of the nodes in wireless mesh networks is crucial for battery lifetime estimation. In this paper, we describe the timing, energy consumption, and battery lifetime estimation of the MDC method in the TDMA mesh sensor networks using flooding routing. For the battery life estimation, we made a semiempirical model that describes the energy consumption of the nodes with a real battery model. In this model, the low-level constraints are based on the measured energy consumption of the sensor nodes in different operation phases.