In the Industrial Internet of Things, it is necessary to reserve enough bandwidth resources according to the maximum traffic peak. However, bandwidth reservation based on the maximum traffic peak leads to low resource utilization. In this paper, we propose a data transfer optimization solution, based on the cooperation of different entities in the local area, which strives to deliver data acquired by sensors to the cloud in a reliable manner and improve bandwidth utilization to save limited network resources. In our solution, the data transfers from the sensors in a local network are controlled by a local controller and some edge gateways with acceptable cost such that no congestion occurs in the path to the cloud and the bandwidth requirement of each flow can be met. To obtain a tradeoff between resource utilization and transfer delay, we study the problem of minimizing the maximum rate peak of periodic real-time traffic from distributed sensors and propose an algorithm to solve this problem with a desirable lower boundary of the performance. In addition, we design an application-level forwarding method that significantly improves resource utilization and a method of implementing reliable sampling instant adjustment. The experimental results show that our solution significantly improves resource utilization without producing network congestion.

User clustering presents a significant design challenge when implementing non-orthogonal multiple access (NOMA) in multiple-input multiple-output (MIMO) systems. To fully exploit the potential of power domain multiplexing and achieve better performance of NOMA, users must possess significant variations in their channel gains. Consequently, it becomes necessary to cluster users based on their distinct channel gain characteristics. However, using random user clustering often leads to suboptimal outcomes, while the exhaustive search method is burdened with exorbitant complexity. To achieve the balance between system performance and complexity, this paper proposes a user clustering scheme that relies on Jaccard coefficient, which is a measure of differences in user channels, ranging from 0 to 1. A value of 0 indicates complete dissimilarity, while a value of 1 indicates complete similarity. By calculating the Jaccard coefficient, we can identify users who are dissimilar to the centroid as a cluster. Additionally, a new power allocation algorithm is developed to maximize the sum spectral efficiency by employing successive convex approximations (SCA), taking into account both spectral efficiency and user quality of service. The simulation results demonstrate that the algorithm proposed for maximizing the sum spectral efficiency exhibits a higher convergence rate and can substantially enhance the sum spectral efficiency in comparison to the full power control (FPC) scheme.

Networks and industrial systems play a pivotal role in modern society, and their security has garnered increasing attention. Anomalies within industrial equipment may propagate through fault transmission, leading to a cascade of failures. Additionally, cyberattacks on equipment can result in significant losses. Therefore, in the realm of industrial and cyberspace domains, an effective multivariate time series anomaly detection system for monitoring equipment is instrumental in ensuring the healthy operation of the machinery. Nevertheless, detecting anomalies in numerous time series remains challenging, stemming from the absence of anomaly labels and the complexity of the data patterns. Existing algorithms predominantly concentrate on modeling within the time domain, falling short in fully leveraging the informative features present in frequency domain data, resulting in diminished detection performance. This paper introduces STFT-TCAN, a model for anomaly detection in time series that seamlessly integrates information from both time and frequency domains for extracting data features. Sliding windows and the Short Time Fourier Transform (STFT) are utilized to construct a frequency matrix, effectively amalgamating the characteristics of both time and frequency domains within the time series. Furthermore, the model employs Temporal Convolutional Networks (TCN) and Transformer attention mechanisms (which combined to form the TCAN module) to capture the features of multivariate time series, thereby resulting in heightened detection accuracy. The proposed model undergoes validation on six publicly available datasets, showcasing the superior performance of the STFT-TCAN model in comparison to current baseline methods. It adeptly extracts features from both frequency and time domains in sequential data, thereby achieving state-of-the-art performance in tasks related to anomaly detection in multivariate time series.

This paper proposes an innovative approach that employs multi-qubit Bacterial Foraging Optimization (mQBFO) algorithm to solve the pilot assignment and Access Point (AP) selection problems in cell-free massive Multi-Input Multi-Output (MIMO) communication systems. It uses multi qubits to indicate a bacterium, and uses an adaptive quantum rotation gate to simulate the chemotaxis phenomenon in the classical bacterial algorithm to achieve bacterial state update. It also introduces the bacterial health degree, which is used to record the cumulative sum of fitness of each bacterium. To avoid falling into local optimal solutions, the elimination-dispersal operation is considered. Finally, the quantum bacterial population is collapsed into a ground state population by measurement to get the solution of the optimization problem. The numerical results prove that the proposed scheme outperforms the traditional schemes in pilot assignment and AP selection, and can effectively improve the average downlink throughput of the system.

Serving as the global Internet’s phonebook, the Domain Name Service (DNS) is utilized for translating human-friendly domain names into machine-readable IP addresses, which makes DNS essential to the operation of the Internet and heavily relied on by today’s almost all various online services. Note that in some cases, DNS could be exploited maliciously and involved into some unexpected scenarios such as phishing, spamming, and harmful content distributing. We refer to these kinds of exploitation as DNS Abuse. Over the past years, DNS Abuse has been suffering an explosive growth, and thus DNS Abuse mitigation has been drawing more and more researchers’ attentions. In this paper, we reexamine some current major efforts made in this area, and find out some potential concerns or limitations which could bring negative impact to their usability and reliability for worldwide adoption or deployment. In this context, we further propose an incentive and decentralized procedure by introducing a trusted notifier reporting framework based on blockchain, which could guarantee the usability and reliability of DNS Abuse mitigation more significantly for worldwide deployment.

To facilitate their worldwide access, online resources such as websites, mobile apps as well as email addresses would generally utilize domain names to label their logical locations on the Internet. Meanwhile, people who want to visit somewhere over the Internet would also tend to resort to a specific domain name first. Therefore, domain names are virtually playing an essential role during the interacting procedure between humans and online resources. However, domain names could sometimes be exploited maliciously and involved into some unexpected scenarios such as phishing, spamming, and harmful content distributing. We refer to these kinds of exploitation here as domain name abuse. Due to the explosive growth over the past years, domain name abuse has been drawing plenty of attentions both from academic and industrial areas. However, we note that there still exist a range of fundamental yet vital issues that have not been well addressed so far. In this paper, we conduct a comprehensive reexamination towards some of these major issues as well as relevant approaches regarding domain name abuse handling, and try further to set forth some of our own responses and corresponding updates towards them. We believe that these issues and relevant approaches could lead to extensive impact towards further progress in this area, and our work would help the community to deal with domain name abuse in a more accountable and practical manner.

In generic object detection, detectors are often susceptible to foreground objects and background regions that share similar appearances. In this paper, we propose a novel discriminative region mining (DRM) module for object detection, which enables discriminative region localization and representation for accurate object identification. The DRM module is collaboratively optimized by an extra intramodule classification loss in addition to the usual detection loss, which ensures its adequate discriminative capability. Specifically, two derivatives of the DRM module, namely a local DRM module and a contextual DRM module are proposed to excavate local and contextual discriminative regions, respectively. Furthermore, we extend the local DRM module to capture multiple local discriminative regions with a diversity constraint. To explore informative local features, an image upsampling branch is introduced to generate fine-grained representation for the local DRM module. Extensive experiments on the PASCAL VOC and MS COCO datasets demonstrate the effectiveness of the proposed method. Simple baseline detectors with the built-in DRM can achieve state-of-the-art detection performance. For example, the proposed detector achieves a mean average precision of 81.0% on PASCAL VOC 2007 with an input size of$\text{300} \times \text{300}$using a ResNet-18 backbone, which runs at 24.2 fps on an Nvidia Titan X GPU.

As an instantiation of Information-centric Networking (ICN), Named Data Networking (NDN) was proposed. Since the Interests are recorded in the PITs of the intermediate routers until they receive corresponding Data packets or exceed the expiring time, the attackers can send excessive number of spoofed Interests to occupy the PITs, which is called Interest Flooding Attack (IFA), to degrade the network performance. In this paper, we propose an IFA detection mechanism based on Support Vector Machine (SVM), which can detect the IFA effectively. In order to improve the accuracy of the attack detection, we use the information entropy of the Interest names, the usage of PIT and the satisfaction rate of the Interests as the extracted features in the SVM classifier. In addition, we evaluate the performance of our mechanism. The simulation results validate that the mechanism can accurately and effectively detect the IFA.

JavaScript can modify HyperText Markup Language(HTML) code.tag of HTML can load pages from other websites. These technologies are widely used nowadays for constructing flexible and robust web services. However, illegal websites also use these technologies to hide illegal contents. For traditional methods using web text to detect these illegal webpages (just getting initial source codes that aren't parsed by a browser), they can't give a precise judgment. In this paper, we solved the challenge and proposed a robust Internet abuse detection method. We get HTML codes that had been parsed by simulating the progress how browsers work in order to gather the necessary materials for text detection methods. Besides, we not only extracted the text features of HTML code, but also extracted structure features of HTML codes. With the experiments under detecting Internet abuse scenarios, we demonstrated that the proposal is efficient.

Phishing is increasingly severe in recent years, which seriously threatens the privacy and property security of netizens. Phishing is essentially a counterfeiting of brands. In order to effectively cheat the victim, phishing sites are visually and semantically highly similar to real sites. In recent years, anti-phishing methods based on machine learning are mainstream anti-phishing methods. The effectiveness of the machine learning models hinges on the extracted statistical features. However, the extracted statistical features mainly focus on visual similarity, stealing information and third-party services, which ignore the semantic information of web pages. Therefore, we extract a series of semantic features through word2vec to better describe the features of phishing sites, and further fuse them with other multi-scale statistical features to construct a more robust phishing detection model. The experimental results on the actual data sets show that the majority of phishing websites are effectively identified by only mining the semantic features of word embeddings. The phishing detection models based on fusion features obtained the best detection results, which shows that semantic features and other statistical features have good complementarity. The proposed method provides a promising way for phishing detection in actual Internet environment, which boosts the phishing detection performance effectively.

Serving as the global Internet's phonebook, the Domain Name Service (DNS) helps to translate human-friendly domain names into machine-readable IP addresses, which makes DNS of great importance to the operation of the Internet and virtually relied on by today's almost all kinds of Internet-based activities. As such, people whoever want to go anywhere over the Internet will need to refer to the DNS first. Therefore, it has become an ideal way to conduct online privacy exploitations through the DNS due to people's pervasive usage of the Internet. However, the current DNS doesn't provide any countermeasure against this kind of exploitation, and thus risks severe privacy disclosure problems. In this paper, we give a comprehensive empirical analysis of DNS privacy disclosure problems by exploring potential privacy leaking paths in the DNS. Then we further identify and describe multiple criterions of validity systematically that are obligated when considering DNS privacy preservation. Finally, we propose a simple DNS privacy preserving solution with significant deployment potential in the current DNS, which can only lead to a moderate level of extra query latency perceived by end users.

With the development of wireless communication technologies, the mobile terminal can be installed with more than one wireless interfaces to support its flexible roaming and vertical handover between heterogeneous access networks. Traditionally, the ongoing session has to be re-established when the multi-interface terminal hands over vertically while maintaining the Delay Tolerant Networking (DTN) communication. In this paper, a novel solution is proposed to efficiently support the on-demand DTN communication under the heterogeneous access networks based on Named Data Networking (NDN) architecture.

Phishing is a security attack that involves the creation of websites that mimic legitimate websites, and these fraud websites bring Internet users a lot of loss. Traditional anti-phishing methods usually worked in a passive way by receiving report data of user. Due to the growing shorter survival time of phishing, this kind of methods is not efficient enough to find and take down new phishing attacks. In this paper, we propose an Intelligent Phishing Detection (IPD) system to address phishing detection problem actively. Specially, IPD first generates the detection dataset from the global massive domain name registration data automatically; then it applies the Naïve Bayes algorithm which is optimized by position-based features to achieve the high precision detection; finally, in order to find more phishing websites, IPD expands detection dataset by generating Uniform Resource Locator (URL) templates based on the detection results. The experimental results of IPD demonstrate the effectiveness and timeliness in detection phishing websites.

Abstract The information‐centric networking concept was proposed to fulfill the scalability and efficiency requirements of the content‐centric Internet in the future. Among the multiple information‐centric networking proposals, Named Data Networking (NDN) is one of the most important representatives. NDN uses a hierarchical name to identify the data after which the on‐path cache can be deployed to improve the efficiency of data retrieval. However, with the development of mobile Internet, how to extend NDN in the mobile environment to enable efficient and scalable mobility management remains a challenge. We propose a distributed mobility management scheme for both the mobile receiver and the mobile publisher in NDN. Our proposed approach is based on the basic NDN naming and routing principles to select the branching node of the previous and new access locations of the mobile terminal after which the on‐path routing states are dynamically adjusted accordingly. Then we propose a novel analytical model to analyze the performance of the proposed scheme. The results demonstrate that the proposed scheme inherits the scalability and efficiency of NDN in the mobile Internet. Copyright © 2015 John Wiley & Sons, Ltd.

IEEE 802.16 network introduces a multimedia data scheduling service with different quality of service QoS requirements. The scheduling service manages transmission resources according to data types, satisfying the requirements of different connections or users. On the basis of the data types defined in the service, we discuss a normalized QoS metric for the multimedia connections in the paper. The QoS value of a connection can be determined just by three components: the data type of the connection, its desired resources, and its allocated resources. Then, we propose an optimum bandwidth allocation solution, which can maximize the utility of base station. Next, we propose a call admission control scheme utilizing the bandwidth allocation solution. In the scheme, the occupied resource of ongoing connections will be regulated for the entry admission of a new connection, without degrading the network performance and the QoS of ongoing connections. Finally, the simulation results confirm that the proposed scheme with the normalized QoS can achieve better trade-off between ongoing connections and new connections.Copyright ©2012 John Wiley & Sons, Ltd.

Hierarchical Mobile IPv6 (HMIPv6) is designed to reduce the handover latency and signaling load of Mobile IPv6 (MIPv6). However, HMIPv6 only improves local mobility performance while the handover latency in the inter-Mobility Anchor Point (MAP) handover is still long and packet transmission cost is still heavy due to the overlapped tunnels. In this paper, we propose a cascaded tunnel scheme in HMIPv6 to reduce its handover latency and signaling cost. In the proposed scheme, the home registration of Mobile Node (MN) is conducted by the MAP in a network-based manner and the global tunnel is established between MAP and Home Agent (HA), which allows the MN to originate only the local registration signaling even during its inter-MAP handover. The improvements contributed by the proposed scheme over the basic HMIPv6 are shown to be significant from the analyzing results.

Vehicular information network and Internet of Things (IoT) technologies have been receiving a lot of attention in recent years. As one of the most important and promising IoT areas, a vehicular information network aims to implement a myriad of applications related to vehicles, traffic information, drivers, passengers, and pedestrians. However, intervehicular communication (IVC) in a vehicular information network is still based on the TCP/IP protocol stack which is not efficient and scalable. To address the efficiency and scalability issues of the IVC, we leverage the named data networking (NDN) paradigm where the end user only cares about the needed content and pays no attention to the actual location of the content. The NDN model is highly suitable for the IVC scenario with its hierarchical content naming scheme and flexible content retrieval and caching support. We design a novel vehicular information network architecture based on the basic communication principle of NDN. Our proposed architecture aims to improve content naming, addressing, data aggregation, and mobility for IVC in the vehicular information network. In addition, the key parameter settings of the proposed schemes are analyzed in order to help guide their actual deployment.

The world is entering a post-PC era in which more real-time entertainment traffic is delivered to mobile devices than to PCs. The unprecedented expansion of mobile Internet traffic has resulted in the development of distributed mobility management (DMM) at the IETF. In this paper, we introduce a dynamic tunneling scheme for network-based DMM, in which mobility anchors are distributed at an access network level while tunnels for data packets are dynamically configured taking into account of both session and mobility status. We illustrate the proposed scheme's initial attachment and handover procedures step-by-step in an environment where network-based DMM is coexisted with Proxy Mobile IPv6. To justify the effectiveness of the proposed scheme, we develop an analytical cost model that is used to compare the performance of the proposed scheme with existing ones in terms of signaling and packet delivery costs. Our analysis shows that the proposed scheme optimizes packet delivery paths and thus provides a cost reduction during the packet delivery compared to the existing schemes. We also describe possible performance extensions to the proposed scheme.

In this paper, we introduce a deployment strategy to support large scale mobility management based on Proxy Mobile IPv6 (PMIPv6). As a centralized mobility management protocol, PMIPv6 employs a single-handed mobility anchor, Local Mobility Anchor (LMA), to maintain the mobility context and routing status of all registered mobile nodes in a localized domain. However, this single-handed mobility anchor will suffer with ever-increasing mobile Internet traffic. We propose a distributed local mobility anchor architecture with new prefix and address management schemes and then present a mobility management procedure with operational aspects. In the proposed architecture, the registration message is always routed to the closest LMA thanks to the anycast routing. The other LMAs create the direct host route to the serving Mobility Anchor Gateway (MAG) for the optimized packet transmission. We also analyze the proposed architecture's performance in terms of scalability, robustness, and efficiency. The results demonstrate that the state synchronization of the proposed architecture induces extra signaling cost during the handover, however, the optimized route established by it can save more cost when the PMIPv6 service is adopted in the large-scale environment.

To cope with challenging problems faced by traditional multicast routing protocols, many branching-router (BR)-based multicast routing schemes with desirable features have been proposed. However, the current BR-based methods still lack efficient multicast management and suffer from a long join latency, leading to a disappointing mobility performance. In this paper, we propose a novel BR-based multicast architecture with a corresponding multicast routing protocol supporting multicast receiver mobility. In the proposed multicast architecture, a new management entity called multicast controller (MC) is used to handle most of the multicast management-related tasks, while other routers in the network construct a multicast tree according to the proposed Branching-Router-based Multicast routing protocol with Mobility support (BRMM). Besides, the fast handover of multicast service can be supported by BRMM through the pre-establishment of temporary multicast paths. Through extensive simulation and analysis, we show that BRMM outperforms existing protocols and has many other attractive features.

Abstract Mobile IPv6 (MIPv6) is a host‐based mobility support specification which has been approved by the IETF as the standardized solution of global mobility management in IPv6 network for Mobile Node (MN). However, MIPv6 handover procedure results in a large handover delay. To improve its performance, some MIPv6 variants such as Fast Handover for MIPv6 (FMIPv6) and Hierarchical MIPv6 (HMIPv6) were proposed. However, they all require the MN to support the mobility management protocols which increase the difficulty of management and deployment. Recently, IETF NETLMM workgroup published the Proxy Mobile IPv6 (PMIPv6) which is a network‐based localized mobility management to provide the mobility support for mobile host without the involvement of the mobility signaling. In this paper, we analyze the singling cost of PMIPv6 and implement it in our test‐bed to evaluate its performance. The results show that the PMIPv6 has lower signaling cost and packet delivery cost, and it can improve the handover performance of UDP and TCP than the other mobility management protocols under low‐delay networks, as for the wide area networks, it needs to introduce some mechanism like fast handover to further improve its performance. Copyright © 2009 John Wiley & Sons, Ltd.

In this paper, we propose a mobile multicast architecture with management support. In this architecture, a powerful entity called Multicast Controller (MC) is deployed which handles most of the multicast management-related tasks. Based on this architecture, the mobile multicast routing protocol called Fast Chain Mobile Multicast (FCMM) is proposed, which processes the handover in advance and spans the multicast tree using the forwarding chain. Our analysis demonstrates that the FCMM protocol outperforms other related protocols and is a promising alternative for providing efficient and flexible mobile multicast services.

In this paper, we propose a network mobility supporting scheme (N-NEMO) in Proxy Mobile IPv6 (PMIPv6) network, which is an issue still up in the air for the PMIPv6. In the N-NEMO, a tunnel splitting scheme is used to differentiate the inter-Mobility Access Gateway (MAG) and intra-MAG mobility. The performance analysis and comparison between other related schemes show that N-NEMO reduces the signaling cost significantly. Besides, it enhances the efficiency and scalability to provide the comprehensive network mobility in the PMIPv6 context.

The next generation of mobile/wireless communication system is expected to include heterogeneous broadband wireless networks that will coexist and use a common IP core to offer a diverse range of high data rate multimedia services to end users with contemporary mobile devices. The mobile devices will be equipped with multiple network interfaces since the networks have characteristics that complement each other. This requires the provision of seamless vertical handover. In this paper, a probability driven handover scheme which uses the mobile's speed (SPHO) is developed to support seamless and adaptive handover management between WLAN and UMTS. Extensive simulation experiments show that this scheme effectively achieves seamless handover between heterogeneous networks and guarantees quality of communication during handover.