A Machine Learning-Based Attack Detection and Prevention System in Vehicular Named Data Networking

Named Data Networking(NDN)is gaining a significant attention in Vehicular Ad-hoc Networks(VANET)due to its in-network content caching,name-based routing,and mobility-supporting characteristics.Nevertheless,existing NDN faces three significant challenges,including security,privacy,and routing.In particular,security attacks,such as Content Poisoning Attacks(CPA),can jeopardize legitimate vehicles with malicious content.For instance,attacker host vehicles can serve consumers with invalid information,which has dire consequences,including road accidents.In such a situation,trust in the content-providing vehicles brings a new challenge.On the other hand,ensuring privacy and preventing unauthorized access in vehicular(VNDN)is another challenge.Moreover,NDN’s pull-based content retrieval mechanism is inefficient for delivering emergency messages in VNDN.In this connection,our contribution is threefold.Unlike existing rule-based reputation evaluation,we propose a Machine Learning(ML)-based reputation evaluation mechanism that identifies CPA attackers and legitimate nodes.Based on ML evaluation results,vehicles accept or discard served content.Secondly,we exploit a decentralized blockchain system to ensure vehicles’privacy by maintaining their information in a secure digital ledger.Finally,we improve the default routing mechanism of VNDN from pull to a push-based content dissemination using Publish-Subscribe(Pub-Sub)approach.We implemented and evaluated our ML-based classification model on a publicly accessible BurST-Asutralian dataset for Misbehavior Detection(BurST-ADMA).We used five(05)hybrid ML classifiers,including Logistic Regression,Decision Tree,K-Nearest Neighbors,Random Forest,and Gaussian Naive Bayes.The qualitative results indicate that Random Forest has achieved the highest average accuracy rate of 100%.Our proposed research offers the most accurate solution to detect CPA in VNDN for safe,secure,and reliable vehicle communication.

Push-Based Content Dissemination and Machine Learning-Oriented Illusion Attack Detection in Vehicular Named Data Networking

Recent advancements in the Vehicular Ad-hoc Network(VANET)have tremendously addressed road-related challenges.Specifically,Named Data Networking(NDN)in VANET has emerged as a vital technology due to its outstanding features.However,the NDN communication framework fails to address two important issues.The current NDN employs a pull-based content retrieval network,which is inefficient in disseminating crucial content in Vehicular Named Data Networking(VNDN).Additionally,VNDN is vulnerable to illusion attackers due to the administrative-less network of autonomous vehicles.Although various solutions have been proposed for detecting vehicles’behavior,they inadequately addressed the challenges specific to VNDN.To deal with these two issues,we propose a novel push-based crucial content dissemination scheme that extends the scope of VNDN from pullbased content retrieval to a push-based content forwarding mechanism.In addition,we exploitMachine Learning(ML)techniques within VNDN to detect the behavior of vehicles and classify them as attackers or legitimate.We trained and tested our system on the publicly accessible dataset Vehicular Reference Misbehavior(VeReMi).We employed fiveML classification algorithms and constructed the bestmodel for illusion attack detection.Our results indicate that RandomForest(RF)achieved excellent accuracy in detecting all illusion attack types in VeReMi,with an accuracy rate of 100%for type 1 and type 2,96%for type 4 and type 16,and 95%for type 8.Thus,RF can effectively evaluate the behavior of vehicles and identify attacker vehicles with high accuracy.The ultimate goal of our research is to improve content exchange and secureVNDNfromattackers.Thus,ourML-based attack detection and preventionmechanismensures trustworthy content dissemination and prevents attacker vehicles from sharing misleading information in VNDN.

Secure vehicular data communication in Named Data Networking

Vehicular data misuse may lead to traffic accidents and even loss of life,so it is crucial to achieve secure vehicular data communications.This paper focuses on secure vehicular data communications in the Named Data Networking(NDN).In NDN,names,provider IDs and data are transmitted in plaintext,which exposes vehicular data to security threats and leads to considerable data communication costs and failure rates.This paper proposes a Secure vehicular Data Communication(SDC)approach in NDN to supress data communication costs and failure rates.SCD constructs a vehicular backbone to reduce the number of authenticated nodes involved in reverse paths.Only the ciphtertext of the name and data is included in the signed Interest and Data and transmitted along the backbone,so the secure data communications are achieved.SCD is evaluated,and the data results demonstrate that SCD achieves the above objectives.

A Cache Replacement Policy Based on Multi-Factors for Named Data Networking

Named Data Networking(NDN)is one of the most excellent future Internet architectures and every router in NDN has the capacity of caching contents passing by.It greatly reduces network traffic and improves the speed of content distribution and retrieval.In order to make full use of the limited caching space in routers,it is an urgent challenge to make an efficient cache replacement policy.However,the existing cache replacement policies only consider very few factors that affect the cache performance.In this paper,we present a cache replacement policy based on multi-factors for NDN(CRPM),in which the content with the least cache value is evicted from the caching space.CRPM fully analyzes multi-factors that affect the caching performance,puts forward the corresponding calculation methods,and utilize the multi-factors to measure the cache value of contents.Furthermore,a new cache value function is constructed,which makes the content with high value be stored in the router as long as possible,so as to ensure the efficient use of cache resources.The simulation results show that CPRM can effectively improve cache hit ratio,enhance cache resource utilization,reduce energy consumption and decrease hit distance of content acquisition.

Research on the Method of Implementing Named Data Network Interconnection Based on IP Network

In order to extend the application scope of NDN and realize the transmission of different NDNs across IP networks,a method for interconnecting NDN networks distributed in different areas with IP networks is proposed.Firstly,the NDN data resource is located by means of the DNS mechanism,and the gateway IP address of the NDN network where the data resource is located is found.Then,the transmission between different NDNs across the IP network is implemented based on the tunnel technology.In addition,in order to achieve efficient and fast NDN data forwarding,we have added a small number of NDN service nodes in the IP network,and proposed an adaptive probabilistic forwarding strategy and a link cost function-based forwarding strategy to make NDN data obtaining the cache service provided by the NDN service node as much as possible.The results of analysis and simulation experiments show that,the interconnectionmethod of NDN across IP network proposed is generally effective and feasible,and the link cost function forwarding strategy is better than the adaptive probability forwarding strategy.

A Dataflow-Oriented Programming Interface for Named Data Networking

Inheriting from a data-driven communication pattern other than a location-driven pattern, named data net- working （NDN） offers better support to network-layer dataflow. However, the application developers have to handle complex tasks, such as data segmentation, packet verification, and flow control, due to the lack of proper transport-layer protocols over the network layer. In this study, we design a dataflow-oriented programming interface to provide transport strategies for NDN, which greatly improves the efficiency in developing applications. This interface presents two application data unit; （ADU） retrieval strategies according to different data publishing patterns, in which it adopts an adaptive ADU pipelining algorithm to control the dataflow based on the current network status and data generation rate. The interface also offers network measurement strategies to monitor an abundance of critical metrics infuencing the application performance. We verify the functionality and performance of our interface by implementing a video streaming application spanning 11 time zones over the worldwide NDN testbed. Our experiments show that the interface can efficiently support developing high-performance and dataflow-driven NDN applications.

Security Attacks in Named Data Networking: A Review and Research Directions

Contents such as audios,videos,and images,contribute most of the Internet traffic in the current paradigm.Secure content sharing is a tedious issue.The existing security solutions do not secure data but secure the communicating endpoints.Named data networking(NDN)secures the data by enforcing the data publisher to sign the data.Any user can verify the data by using the public key of the publisher.NDN is resilient to most of the probable security attacks in the TCP/IP model due to its new architecture.However,new types of attacks are possible in NDN.This article surveys the most significant security attacks in NDN such as interest flooding attacks,cache privacy attacks,cache pollution attacks,and content poisoning attacks.Each attack is classified according to their behavior and discussed for their detection techniques,countermeasures,and the affected parameters.The article is an attempt to help new researchers in this area to gather the domain knowledge of NDN.The article also provides open research issues that could be addressed by researchers.

SAFT-VNDN: A Socially-Aware Forwarding Technique in Vehicular Named Data Detworking

Vehicular Social Networks(VSNs)is the bridge of social networks and Vehicular Ad-Hoc Networks(VANETs).VSNs are promising as they allow the exchange of various types of contents in large-scale through Vehicle-to-Vehicle(V2V)and Vehicle-to-Infrastructure(V2I)communication protocols.Vehicular Named Data Networking(VNDN)is an auspicious communication paradigm for the challenging VSN environment since it can optimize content dissemination by decoupling contents from their physical locations.However,content dissemination and caching represent crucial challenges in VSNs due to short link lifetime and intermittent connectivity caused by vehicles’high mobility.Our aim with this paper is to improve content delivery and cache hit ratio,as well as decrease the transmission delay between end-users.In this regard,we propose a novel hybrid VNDN-VSN forwarding technique based on social communities,which allows requester vehicles to easily find the most suitable forwarder or producer among the community members in their neighborhood area.Furthermore,we introduce an effective caching mechanism by dividing the content store into two parts,one for community private contents and the second one for public contents.Simulation results show that our proposed forwarding technique can achieve a favorable performance compared with traditional VNDN,in terms of data delivery ratio,average data delivery delay,and cache hit ratio.

A Hierarchal Clustered Based Proactive Caching in NDN-Based Vehicular Network

An Information-Centric Network(ICN)provides a promising paradigm for the upcoming internet architecture,which will struggle with steady growth in data and changes in accessmodels.Various ICN architectures have been designed,including Named Data Networking(NDN),which is designed around content delivery instead of hosts.As data is the central part of the network.Therefore,NDN was developed to get rid of the dependency on IP addresses and provide content effectively.Mobility is one of the major research dimensions for this upcoming internet architecture.Some research has been carried out to solve the mobility issues,but it still has problems like handover delay and packet loss ratio during real-time video streaming in the case of consumer and producer mobility.To solve this issue,an efficient hierarchical Cluster Base Proactive Caching for Device Mobility Management(CB-PC-DMM)in NDN Vehicular Networks(NDN-VN)is proposed,through which the consumer receives the contents proactively after handover during the mobility of the consumer.When a consumer moves to the next destination,a handover interest is sent to the connected router,then the router multicasts the consumer’s desired data packet to the next hop of neighboring routers.Thus,once the handover process is completed,consumers can easily get the content to the newly connected router.A CB-PCDMM in NDN-VN is proposed that improves the packet delivery ratio and reduces the handover delay aswell as cluster overhead.Moreover,the intra and inter-domain handover handling procedures in CB-PC-DMM for NDN-VN have been described.For the validation of our proposed scheme,MATLAB simulations are conducted.The simulation results show that our proposed scheme reduces the handover delay and increases the consumer’s interest satisfaction ratio.The proposed scheme is compared with the existing stateof-the-art schemes,and the total percentage of handover delays is decreased by up to 0.1632%,0.3267%,2.3437%,2.3255%,and 3.7313%at the mobility speeds of 5 m/s,10 m/s,15 m/s,20 m/s,and 25 m/s,and the efficiency of the packet delivery ratio is improved by up to 1.2048%,5.0632%,6.4935%,6.943%,and 8.4507%.Furthermore,the simulation results of our proposed scheme show better efficiency in terms of Packet Delivery Ratio(PDR)from 0.071 to 0.077 and a decrease in the handover delay from 0.1334 to 0.129.

NDN Content Poisoning Mitigation Using Bird Swarm Optimization and Trust Value

Information-Centric Networking(ICN)is considered a viable strategy for regulating Internet consumption using the Internet’s underlying architecture.Although Named Data Networking(NDN)and its reference-based implementa-tion,the NDN Forwarding Daemon(NFD),are the most established ICN solu-tions,their vulnerability to the Content Poisoning Attack(CPA)is regarded as a severe threat that might dramatically impact this architecture.Content Poisoning can significantly minimize the impact of NDN’s universal data caching.Using verification signatures to protect against content poisoning attacks may be imprac-tical due to the associated costs and the volume of messages sent across the net-work,resulting in high computational costs.Therefore,in this research,we designed a method in NDN called Bird Swarm Optimization Algorithm-Based Content Poisoning Mitigation(BSO-Content Poisoning Mitigation Scheme).By aggregating the security information of entire routers along the full path,this sys-tem introduces the BSO to explore the secure transmission path and alter the con-tent retrieval procedure.Meanwhile,based on the determined trustworthy value of each node,the BSO-Content Poisoning Mitigation Scheme can bypass malicious routers,preventing them from disseminating illicit content in the future.Addition-ally,the suggested technique can minimize content poisoning utilizing removing erroneous Data packets from the cache-store during the pathfinding process.The proposed method has been subjected to extensive analysis compared with the ROM scheme and improved performance justified in several metrics.BSO-Con-tent Poisoning Mitigation Scheme is more efficient and faster than the ROM tech-nique in obtaining valid Data packets and resulting in a higher good cache hit ratio in a comparatively less amount of time.

Caching Strategies in NDN Based Wireless Ad Hoc Network:A Survey

Wireless Ad Hoc Networks consist of devices that are wirelessly connected.Mobile Ad Hoc Networks(MANETs),Internet of Things(IoT),and Vehicular Ad Hoc Networks(VANETs)are the main domains of wireless ad hoc network.Internet is used in wireless ad hoc network.Internet is based on Transmission Control Protocol(TCP)/Internet Protocol(IP)network where clients and servers interact with each other with the help of IP in a pre-defined environment.Internet fetches data from a fixed location.Data redundancy,mobility,and location dependency are the main issues of the IP network paradigm.All these factors result in poor performance of wireless ad hoc networks.The main disadvantage of IP is that,it does not provide in-network caching.Therefore,there is a need to move towards a new network that overcomes these limitations.Named Data Network(NDN)is a network that overcomes these limitations.NDN is a project of Information-centric Network(ICN).NDN provides in-network caching which helps in fast response to user queries.Implementing NDN in wireless ad hoc network provides many benefits such as caching,mobility,scalability,security,and privacy.By considering the certainty,in this survey paper,we present a comprehensive survey on Caching Strategies in NDN-based Wireless AdHocNetwork.Various cachingmechanism-based results are also described.In the last,we also shed light on the challenges and future directions of this promising field to provide a clear understanding of what caching-related problems exist in NDN-based wireless ad hoc networks.

A Secure NDN Framework for Internet of Things Enabled Healthcare

Healthcare is a binding domain for the Internet of Things(IoT)to automate healthcare services for sharing and accumulation patient records at anytime from anywhere through the Internet.The current IP-based Internet architecture suffers from latency,mobility,location dependency,and security.The Named Data Networking(NDN)has been projected as a future internet architecture to cope with the limitations of IP-based Internet.However,the NDN infrastructure does not have a secure framework for IoT healthcare information.In this paper,we proposed a secure NDN framework for IoTenabled Healthcare(IoTEH).In the proposed work,we adopt the services of Identity-Based Signcryption(IBS)cryptography under the security hardness Hyperelliptic Curve Cryptosystem(HCC)to secure the IoTEH information in NDN.The HCC provides the corresponding level of security using minimal computational and communicational resources as compared to bilinear pairing and Elliptic Curve Cryptosystem(ECC).For the efficiency of the proposed scheme,we simulated the security of the proposed solution using Automated Validation of Internet Security Protocols and Applications(AVISPA).Besides,we deployed the proposed scheme on the IoTEH in NDN infrastructure and compared it with the recent IBS schemes in terms of computation and communication overheads.The simulation results showed the superiority and improvement of the proposed framework against contemporary related works.

A Lightweight Anonymous Device Authentication Scheme for Information-Centric Distribution Feeder Microgrid

Distribution feeder microgrid(DFM)built based on existing distributed feeder(DF),is a promising solution for modern microgrid.DFM contains a large number of heterogeneous devices that generate heavy network traffice and require a low data delivery latency.The information-centric networking(ICN)paradigm has shown a great potential to address the communication requirements of smart grid.However,the integration of advanced information and communication technologies with DFM make it vulnerable to cyber attacks.Adequate authentication of grid devices is essential for preventing unauthorized accesses to the grid network and defending against cyber attacks.In this paper,we propose a new lightweight anonymous device authentication scheme for DFM supported by named data networking(NDN),a representative implementation of ICN.We perform a security analysis to show that the proposed scheme can provide security features such as mutual authentication,session key agreement,defending against various cyber attacks,anonymity,and resilience against device capture attack.The security of the proposed scheme is also formally verified using the popular AVISPA(Automated Validation of Internet Security Protocols and Applications)tool.The computational and communication costs of the proposed scheme are evaluated.Our results demonstrate that the proposed scheme achieves significantly lower computational,communication and energy costs than other state-of-the-art schemes.

A Cost-Effective Approach for NDN-Based Internet of Medical Things Deployment

Nowadays,healthcare has become an important area for the Internet of Things(IoT)to automate healthcare facilities to share and use patient data anytime and anywhere with Internet services.At present,the host-based Internet paradigm is used for sharing and accessing healthcare-related data.However,due to the location-dependent nature,it suffers from latency,mobility,and security.For this purpose,Named Data Networking(NDN)has been recommended as the future Internet paradigm to cover the shortcomings of the traditional host-based Internet paradigm.Unfortunately,the novel breed lacks a secure framework for healthcare.This article constructs an NDN-Based Internet of Medical Things(NDN-IoMT)framework using a lightweight certificateless(CLC)signature.We adopt the Hyperelliptic Curve Cryptosystem(HCC)to reduce cost,which provides strong security using a smaller key size compared to Elliptic Curve Cryptosystem(ECC).Furthermore,we validate the safety of the proposed scheme through AVISPA.For cost-efficiency,we compare the designed scheme with relevant certificateless signature schemes.The final result shows that our proposed scheme uses minimal network resources.Lastly,we deploy the given framework on NDN-IoMT.

Broadband Communications for High-Speed Trains via NDN Wireless Mesh Network

With the increasing utilization of High-Speed Trains （HSTs）, the need for a reliable and high-bandwidth Internet access under high-speed mobility scenarios has become more demanding. In static, walking, and low mobility environments, TCP/IP （transmission control protocol/Internet protocol） can work well. However, TCP/IP cannot work well in high-speed scenarios because of reliability and handoff delay problems. This is mainly because the mobile node is required to maintain the connection to the corresponding node when it handovers to another access point node. In this paper, we propose a named data networking wireless mesh network architecture for HST wireless communication （NDN-Mesh-T）, which combines the advantages of Wireless Mesh Networks （WMNs） and NDN architectures. We attempt to solve the reliability and handoff delay problems to enable high bandwidth and low latency in Internet access in HST scenarios. To further improve reliability and bandwidth utilization, we propose a Direction-Aware Forwarding （DAF） strategy to forward Interest packet along the direction of the running train. The simulation results show that the proposed scheme can significantly reduce the packet loss rate by up to 51% compared to TCP/IP network architecture. Moreover, the proposed mechanism can reduce the network load, handoff delay, and data redundancy.

Toward long-range adaptive communication via information centric networking

As Internet of Things(IoT)applications become more prevalent and grow in their use,a limited number of wireless communication methods may be unable to enable dependable,robust delivery of information.It is necessary to enable adaptive communication and interoperability over a variety of wireless communication media to meet the requirements of large-scale IoT applications.This paper utilizes Named Data Networking(NDN),an up-and-coming Information-Centric Network architecture,to interconnect differing communication links via the network layer,and implements dynamic forwarding strategies and routing mechanisms which aid in the efficient dissemination of information.This work targets the creation of an interface technique to allow NDN to be transported via LoRa.This is acheived via the coupling of LoRa and WiFi using the NDN Forwarding Daemon(NFD)to create a universal ad hoc network.This network has the capacity for high range and multi-hop Device-to-Device(D2D)communication together with compatibility with other network communication media.Testing of the system in a real environment has shown that the newly created ad hoc network is capable of communicating over a several kilometer radius,while making use of the features provided by NDN to capitalize upon various links available to enable the efficient dissemination of data.Furthermore,the newly created network leverages NDN features to enable content-based routing within the LoRa network and utilize content-based routing techniques.

A Stochastic Optimization Approach for Dynamic Adaptive Streaming over NDN

Nowadays,video streaming counts for the major part of network traffic over the Internet.However,on account of the host-to-host mechanism of the traditional IP network,video distribution over IP-based Internet encounters bottlenecks.Fortunately,a new proposed future Internet architecture,named data networking(NDN)can improve the performance of video distribution by its features such as in-network storage,multi-path forwarding,etc.In this paper,we design an adaptive bitrate algorithm based on Lyapunov optimization theory over NDN to optimize the long-term quality-of-experience(QoE)of video distribution while ensuring the stability of the whole system.When the network condition is abundant and stable,the problem can be simplified by approximating to a fixed-slot queuing model,but the theoretical performance will degrade when the network status is poor and fluctuate fiercely.Therefore,we divide the problem into two models of fixed time slot and non-fixed time slot and design two Lyapunov optimization algorithms to adapt different network scenarios.The proposed algorithms do not require prior knowledge of the network bandwidth and are capable of running online with the client’s available information.Simulation and realistic experiment results demonstrate that our algorithms perform better than others in NDN.

Cache Pollution Prevention Mechanism Based on Deep Reinforcement Learning in NDN

As a representative architecture of contentcentric paradigms for the future Internet,named data networking(NDN)enables consumers to retrieve content duplicates from either the original server or intermediate routers.Each node of NDN is equipped with cache that buffers but not validates the data,making it vulnerable to various attacks.Cache pollution,one of the specific attacks in NDN,fraudulently alters the cached contents by excessively requesting worthless information,squeezing the space of real popular contents and thus degrading the experience of normal users.In order to address the issue,this paper proposes a defense scheme based on deep reinforcement learning(DRL)against cache pollution attack,in which whether a data packet is to be cached is decided by a trained intelligent agent,that is adaptive to dynamic network states and following long term rewards,the accumulative data-requesting delays.Finally,the DRL-based scheme is evaluated and compared to two other existing schemes.Experimental results show that the proposed defense mechanism outperforms the others significantly,and is proved to be effective against cache pollution attacks.