Forwarding Behavior Research Articles

A Study on the Effectiveness of Rumor Control via Social Media Networks to Alleviate Public Panic About COVID-19.

The COVID-19 outbreak triggered a massive spread of unverified news on social media and has become a source of rumors. This paper studies the impact of a virtual rumor control center (RCC) on Weibo user behavior. The collected COVID-19 breaking news stories were divided into positive, negative, and neutral categories, while the moderating effect model was used to analyze the influence of anti-rumor on user behavior (forwarding, liking, and commenting). Our research found that rumor refuting does not directly affect user behavior but does have an indirect moderating effect. Rumor refuting has a profound impact on user forwarding behavior in cases of positive and negative news. Specifically, when the epidemic becomes more serious, the role of rumor refuting becomes critical, and vice versa. Refuting rumors reduces user willingness to forward positive or negative news, with more impact on negative news. Time lag analysis shows a significant moderation of unverified news within 72 h of refuting rumors but indicated an apparent weakening trend over time. Furthermore, we discovered non-linear feature and counter-cyclical phenomena in the moderating effect of rumor refutation.

Growing through Giving: The Role of Paying it Forward in Business-to-Business Marketing

ABSTRACT Purpose Providing B2B marketing with insights into the nascently explored generalized social exchange dimension paying it forward. Marketing is an ongoing exchange relationship of particular significance in the B2B context, where exchanges often are indirect. Therefore, understanding the generalized exchange mechanism paying it forward is important in order to derive value from it, both as a manager of marketing teams (intra-firm) and as a participant in inter-firm exchange relationships. Methodology/Approach By reviewing extant research, this conceptual paper provides a synthesis of paying it forward exchange, how it occurs and can be encouraged in the inter- and intra-firm B2B marketing contexts and proposes a researchable and practically applicable framework, as well as a series of researchable propositions. Findings Founded on the understanding that paying it forward is an extra-role behavior (i.e., not defined by a job description or contract) that occurs both within and between firms, this work presents a conceptual framework as well as a series of researchable propositions with regard to the benefits that can be derived from paying it forward behavior. The framework proposes four different modes (peer, partner, affiliation, and alliance) under which marketers can facilitate or participate in the paying it forward type of exchange. The dimensions of the framework are relational interdependence and the intra-and inter-firm settings. These different modes emerge naturally based on the type of interaction. Depending on the circumstances, an individual could operate in any of the four modes, however depending on mode they operate in there are different key considerations to focus on. Originality/value Makes contributions to literature by providing a synthesis of the generalized social exchange dimension paying it forward, drawing conclusions, and developing a comprehensive framework and researchable propositions for marketing related intra- and inter-firm paying it forward exchange behavior. Academics and practitioners benefit from understanding the value paying it forward may provide and improve the role marketers play in both facilitating and participating in this type of exchange, yet to date this behavior has received scant attention. Practical implications Provides practitioners a synthesis of paying it forward exchange and outlines why and how it is relevant in a B2B marketing context, how it can be encouraged and what managers need to know to make use of its advantages and avoid its pitfalls.

SDN Spotlight: A real-time OpenFlow troubleshooting framework

Troubleshooting in SDN-based networks is still a cumbersome task that can overwhelm human attention. Various anomalies, such as installation failure, disordered rules, and loops, remain unnoticed even when the most recent detection methods are used. In this paper, we address the issue of verifying SDN policies by actively probing the data plane. SDN Spotlight is presented as an anomaly detection framework that tries to detect installation failures, rule conflicts, and loops. In contrast to recent work, such as Monocle and Pronto, SDN Spotlight verifies a chain of rules using a single probing packet. This approach also reduces the number of monitoring rules, which has a direct effect on saving TCAM memory usage and minimizing the packet matching time. SDN Spotlight addresses two problems: verifying rule installation and forwarding behavior verification. Within the SDN Spotlight framework, we introduce two different approaches for forwarding anomaly detection: Hedge-SDN Spotlight and Open-SDN Spotlight. Furthermore, we devise an efficient and fast probe generation algorithm that generates one single probing packet per chain of rules. As opposed to other related work, Hedge-SDN Spotlight does not yield false positives and false negatives when detecting loops and forwarding failures. The results of the experiment demonstrate that SDN Spotlight is much faster than the SDNProbe and SDN traceroute method, in some cases by a factor of up to seven times as fast.

A Proposed Method for Predicting User Disinformation Forwarding Behavior

At present, social network sites (SNSs) have become the major channels by which disinformation is released and disseminated. Without the effective control of disinformation on social media, a serious threat to social stability may occur. Different from traditional media, forwarding has become the key approach to propagating information on social media. Therefore, if the users who will forward the disinformation are identified in advance, they can be prevented from forwarding the disinformation and the harmful effects of disinformation will be minimized. To identify the users who will forward the disinformation, we should predict the probability of an individual forwarding disinformation. We propose a novel method to predict the disinformation forwarding probability of individuals on a social network. The proposed method extracts the features that affect individual disinformation forwarding, especially extracting features related to the susceptibility of users to disinformation. With combining bootstrap sampling and expectation-maximization (EM) algorithm to learn unobserved features, the proposed method utilizes both observed and unobserved features to predict the disinformation forwarding probability of individuals. Using data from “Weibo,” which is the largest social media platform in China, we demonstrate the effectiveness of the proposed method.

On the Ricci flow of homogeneous metrics on spheres

We study the Ricci flow of the four-parameter family of Sp $$(n+1)$$ -invariant metrics on spheres. We determine their forward behaviour and also classify ancient solutions. In doing so, we exhibit a new one-parameter family of ancient solutions on spheres. This completes the classification of homogeneous ancient solutions on spheres.

BlockREV: Blockchain-Enabled Multi-Controller Rule Enforcement Verification in SDN

Compared with the classical structure with only one controller in software-defined networking (SDN), multi-controller topology structure in SDN provides a new type of cross-domain forwarding network architecture with multiple centralized controllers and distributed forwarding devices. However, when the network includes multiple domains, lack of trust among the controllers remains a challenge how to verify the correctness of cross-domain forwarding behaviors in different domains. In this paper, we propose a novel secure multi-controller rule enforcement verification (BlockREV) mechanism in SDN to guarantee the correctness of cross-domain forwarding. We first adopt blockchain technology to provide the immutability and privacy protection for forwarding behaviors. Furthermore, we present an address-based aggregate signature scheme with appropriate cryptographic primitives, which is provably secure in the random oracle model. Moreover, we design a verification algorithm based on hash values of forwarding paths to check the consistency of forwarding order. Finally, experimental results demonstrate that the proposed BlockREV mechanism is effective and suitable for multi-controller scenarios in SDN.

Security in IoT Mesh Networks Based on Trust Similarity

Internet of Things (IoT) Mesh networks are becoming very popular to enable IoT devices to communicate without relying on dedicated PC services. Internet of Things (IoT) implicitly uses mesh networks. IoT connectivity to cloud and edge computing is in vogue. A Wireless Mesh Network (WMN) is a multi-hop and distributed wireless network with mesh routers and mesh clients. Data originating from mesh clients are forwarded to destinations through mesh routers. In IoT Mesh networks, mesh clients are IoT devices. The crucial security issue with these networks is the lack of a trusted third party for validation. However, trust between nodes is required for the proper functioning of the network. WMNs are particularly vulnerable as they rely upon cooperative forwarding. In this research work, a secure and sustainable novel trust mechanism framework is proposed. This framework identifies the malicious nodes in WMNs and improves the nodes’ cooperation. The proposed framework or model differentiates between legitimate and malicious nodes using direct trust and indirect trust. Direct trust is computed based on the packet-forwarding behavior of a node. Mesh routers have multi radios, so the promiscuous mode may not work. A new two-hop mechanism is proposed to observe the neighbors’ packet forwarding behavior. Indirect trust is computed by aggregating the recommendations using the weighted D-S theory, where weight is computed using a novel similarity mechanism that correlates the recommendations received from different neighbors. Dynamic weight computation calculates the overall trust by using several interactions. We present the evaluations to show the effectiveness of the proposed approach in the presence of packet drop/modification attacks, bad-mouthing attacks, on-off attacks, and collusion attacks by using the ns-2 simulator.

A Node Confident based IDS to Avoid Packet Drop Attacks for Wireless Sensor Network

Because of the great characteristics of Wireless Sensor Networks like easier to use and less cost of deployment, they have attracted the researchers to conduct the investigations and received the importance in various civilian and military applications. A number of security attacks have been involved due to the lack of centralized management in these networks. The packet drop attack is one of the attacks and it has a compromised node which drops the malicious packets. In WSNs, different techniques have been implemented to identify the packet drop attack but none of them provides the feasibility to stop or isolate their occurrence in the future. In recent times, the reputation systems provide the way to identify the trustworthy nodes for data forwarding. But the lack of data classification in the reputation systems affects the false positive rate. In this paper, a novel CONFIDENT SCORE based BAYESIAN FILTER NODE MONITORING AGENT (CFS-BFNMA) mechanism is introduced to identify & avoid the packet drop nodes and also to monitor the node behaviours to improve the false positive rate. The final CFS of a node is estimated based on the node past and threshold CFS values. The node monitoring agents (BFNMA) constantly monitors the forwarding behaviour of the nodes and assigns CFS based on the successful forwards. The NMA saves the copy of the data packets in their buffers before forwarding to the neighbour nodes to compare them. Also, this BFNMA analyses the traffic pattern of every round of transmission to improve the false positive rate. By comparing with other conventional security algorithms, the proposed mechanism has been improved the network security & false positive rate drastically based on the simulation results.

Topic-a cluster of relevant messages-propagation dynamics: A modeling study of the impact of user repeated forwarding behaviors

In this letter, a multiple-related susceptible-forwarding-immunized model (MR-SFI) is proposed to investigate the influence on topic propagation dynamics of users’ repeated forwarding behaviors in response to multiple messages sharing the same key words of a topic being posted successively. The model describes the evolution of three forwarding quantities (once-forward, twice-forward, and multi-forward), introduces three re-transmission probabilities (mild re-transmission, deep re-transmission, and severe re-transmission), and describes how these measures impact the propagation efficacy. Data fitting using the real data of Chinese Sina-microblog accurately parameterized the model, quantified the user’s behavior influence, and sensitivity analyses also suggest strategies for effective information dissemination.

Experimental and numerical studies on the formability of AA5754 and AA6082 thin sheets in nonisothermal warm redrawing process

The present work demonstrates a comparative investigation of the nonisothermal warm forward redrawing behavior of AA5754-H22 and AA6082-O sheets. The design and development of a new warm forward redrawing process was demonstrated. The complete redrawing was obtained by keeping the redrawing die and binder at 200 °C and cooling punch near to room temperature using water circulation. This process improved the thickness and surface strain distribution in redrawn cups without the onset of strain localization at the bottom corner. A thermomechanical finite element (FE) model of the nonisothermal warm redrawing process was developed applying the temperature-dependent Barlat-89 yield criterion and the Cowper–Symonds strain rate sensitive hardening model. The FE model reasonably predicted the part depth, earing development, thickness distribution, and surface strain evolution of the redrawn cups. The evolution of temperature distribution within the redrawing cup during the process was captured from FE simulations, and its role in the improvement in redrawing depth was demonstrated. Furthermore, the post-forming characterization of redrawn cup wall was also evaluated by microhardness and ring hoop tensile tests. It was found that the hardness, hoop tensile strength, and energy absorption capacity of AA5754-H22 cups were better than AA6082-O cups.

The Influence of Prosocial and Antisocial Emotions on the Spread of Weibo Posts: A Study of the COVID-19 Pandemic

This study investigates the influences of the prosocial and antisocial tendency of Weibo users on post transmission during the COVID-19 pandemic. To overcome the deficiency of existing research on prosocial and antisocial emotions, we employ a web crawler technology to obtain post data from Weibo and identify texts with prosocial or antisocial emotions. We use SnowNLP to construct semantic dictionaries and training models. Our major findings include the following. First, through correlation analysis and negative binomial regression, we find that user posts with high intensity and prosocial emotion can trigger comments or forwarding behaviour. Second, the influence of antisocial emotion on Weibo comments, likes, and retweets are insignificant. Third, the general emotion about prosocial comments in Weibo also shows the emotion trend of prosocial comments. Overall, a major contribution of this paper is our focus on prosocial and antisocial emotions in cyberspace, providing a new perspective on emotion communication.

Static Equivalence Checking for OpenFlow Networks

Software-defined networking (SDN) provides many advantages over traditional networking by separating the control and data planes. One of the advantages is to provide programmability, which allows administrators to control the behavior of the network. The network configuration may need to be changed for some reason. Whenever such changes are made, it can be required to verify that the forwarding behavior is preserved from the existing configuration, that is, whether the ruleset is properly reflected. In this paper, we propose the forwarding behavior based equivalence checking of OpenFlow networks. We present the formal definition of the network model and the forwarding behavior of the packet flow. Based on the definition, We present a method for checking the equivalence of OpenFlow network forwarding behaviors. Next, we present the implementation of the proposed method, using the constraint satisfaction method, which will be the basis for further extension.

The Study on Public-Interest Short Message Service (SMS) in China during the COVID-19 Pandemic: Mobile User Survey and Content Analysis.

The outbreak of coronavirus disease 2019 (COVID-19) has greatly threatened the global health system and triggered the public health emergency. In order to manage the COVID-19 pandemic, healthcare and prevention information have been delivered through omni-media channels (e.g., television, radio, social platform, etc.). As a traditional outlet, the short message service (SMS) can timely provide abundant anti-epidemic alerts to mobile users. In this paper, we aim to investigate mobile users’ attitudes toward COVID-19 public-interest SMS sent from government authorities and then explore the insight from messaging texts collected between January and April 2020 in China. In general, respondents show a positive attitude towards content and the necessity of public-interest SMS during the pandemic. However, we find that gender and age differences not only affect content evaluation, but also influence reading and forwarding behaviors. For the necessity of SMS, it shows significant difference between the 18–25-year-old and over 40-year-old group, with the middle and elder group showing serious attitudes and giving higher remarks than the youth due to the habits of media usage. However no significant difference is presented between females and males. In terms of content, the category of topics and releasing institutions are analyzed, respectively. Due to the centralized responses and coordination of prevention and control in China, the messages from COVID-19 disposal organizations (e.g., municipal steering group and provincial CDC) account for more than 70% among four cities.

ICS-SVM: A user retweet prediction method for hot topics based on improved SVM

In social networks, many complex factors affect the prediction of user forwarding behavior. This paper proposes an improved SVM prediction method for user forwarding behavior of hot topics to improve prediction accuracy. Firstly, we consider that the improved Cuckoo Search algorithm can select the optimal penalty parameters and kernel function parameters to optimize the SVM and thus predict the user's forwarding behavior. Secondly, this paper considers the factors that affect the user forwarding behavior comprehensively from the user's own factors and external factors. Finally, based on the characteristics of the user's forwarding behavior changing over time, the time-slicing method is used to predict the trend of hot topics. Experiments show that the method can accurately predict the user's forwarding behavior and can sense the trend of hot topics.

P4-KBR: A Key-Based Routing System for P4-Programmable Networks

Software-defined networking (SDN) architecture has provided well-known advantages in terms of network programmability, initially offering a standard, open, and vendor-agnostic interface (e.g., OpenFlow) to instruct the forwarding behavior of network devices from different vendors. However, in the last few years, data plane programmability has emerged as a promising approach to extend the network management allowing the definition and programming of customized and non-standardized protocols, as well as specific packet processing pipelines. In this paper, we propose an in-network key-based routing protocol called P4-KBR, in which end-points (hosts, contents or services) are identified by virtual identifiers (keys) instead of IP addresses, and where P4 network elements are programmed to be able to route the packets adequately. The proposal was implemented and evaluated using bmv2 P4 switches, verifying how data plane programmability offers a powerful tool to overcome continuing challenges that appear in SDN networks.

EFFICIENT TRUST BASED SCHEMES FOR QUALITY OF SERVICE IN MANET

Security is another crucial aspect of providing QoS since the existence of malicious nodes present all kinds of threats to MANETs. Although a number of mechanisms have been proposed for protecting MANETs, most of the solutions are only effective for a particular kind of attacks or provide security at the cost of sacrificing QoS. In this paper, we propose a trust-based secure QoS routing scheme by combining social and QoS trust. The primary approach of the proposed scheme relies on mitigating nodes that exhibit various packet forwarding misbehavior and on discovering the path that ensures reliable communication through the trust mechanism. The scheme would select the best forwarding node based on packet forwarding behavior as well as capability in terms of QoS parameters, such as residual energy, channel quality, link quality, etc. Simulation experiment using Network Simulator-2 (NS2) and under various network conditions show that mixing social and QoS trust parameters can greatly improve security and quality of service routing in terms of overhead, packet delivery ratio and energy consumption.

Understanding people's participation in online charities: a dual-process approach of trust and empathic concern

PurposeThe rapid development of the Internet in China has profoundly affected the country's charities, which many people support through online donations (e.g. providing financial help) and charity information forwarding (a new behavior of participating in online charities via social media). However, the development of online charities has been accompanied by many problems, such as donation fraud and fake charity information, which adversely affect social kindness. The purpose of this paper is to understand people's online donation and forwarding behaviors and to explore the mechanisms of such behaviors from the perspectives of cognitive-based trust and emotional-based empathic concern.Design/methodology/approachThis study developed a research model based on the elaboration likelihood model (ELM) and stimulus–organism–response (SOR) model. The researchers obtained 287 valid samples via a scenario-based experimental survey and conducted partial least squares structural equation modeling (PLS-SEM) to test the model.FindingsThe results indicated that (1) online donation intention is motivated by rational-based trust and emotional-based empathic concern; (2) online charity information forwarding is triggered only when trust is built, and there is no significant correlation between empathic concern and forwarding intention; and (3) content quality, initiator credibility, and platform reputation are three critical paths to promote trust; in addition, an individual's empathic concern can be motivated by the emotional appeal.Originality/valueThis study highlights the different mechanisms of donation and forwarding behaviors and provided theoretical measures for motiving trust and empathic concern in the online context to promote people's participation in online charity.

Virtual Queues for P4: A Poor Man’s Programmable Traffic Manager

The advent of programmable network switch ASICs and recent developments on other programmable data planes (NPUs, FPGAs) drive the renewed interest in network data plane programmability. The P4 language has emerged as a strong candidate to describe a protocol independent datapath pipeline. With its supported architectures, the P4 language provides an excellent way to define the packet processing and forwarding behavior, while leaving other networking components such as the traffic management engine, to non-programmable fixed function elements, based on the capabilities of most programmable devices. However, network flexibility is essential to meet the Quality of Service (QoS) requirements of traffic flows. Thus, enabling programmable control for fixed-function elements like traffic management is crucial. Towards that end we propose the use of virtual queues in the P4 pipeline, investigate the application of virtual queue-based traffic management, and portability of the approach using different P4 programmable targets. Specifically, we focus on virtual queue based Active Queue Management (AQM) for congestion policing and meeting the latency targets of distinct network slices. The solution is compared to P4 built-in functionality for bandwidth management using meters, proving also that the additional dimensions of control are achieved without compromising the processing complexity of the solution.

Name Space Analysis: Verification of Named Data Network Data Planes

Named Data Networking (NDN) has many forwarding behaviors, strategies, and protocols to enable the benefits of Information-Centric Networking. This additional functionality introduces complexity, motivating the need for a tool to help reason about and verify that basic properties of an NDN data plane are guaranteed. This paper proposes Name Space Analysis (NSA), a network verification framework to model and analyze NDN data planes. NSA can take as input one or more snapshots, each representing a state of the data plane. It then provides the verification result against specified properties. NSA builds on the theory of Header Space Analysis, and extends it in a number of ways, e.g., supporting variable-sized headers with flexible formats, introduction of name space functions, allowing for name-based properties such as content reachability and name leakage-freedom, and multi-snapshot verification such as equivalence checks. These important additions reflect the behavior and requirements of NDN, requiring modeling and verification foundations fundamentally different from those of traditional host-centric networks. As a case study, we show how NSA can detect name space conflicts in NDN, which can be often hard to catch. Leveraging the learning from this study, we outline a conflict detection and resolution protocol and a name space registry to avoid such conflicts. We have implemented NSA and identified a number of optimizations to enhance the efficiency of verification. Results from our evaluations, using snapshots from various synthetic test cases and the real-world NDN testbed, show how NSA is effective, in finding errors, has good performance, and is scalable.

CTrust‐RPL: A control layer‐based trust mechanism for supporting secure routing in routing protocol for low power and lossy networks‐based Internet of Things applications

AbstractInternet of Things (IoT) fostered a new epoch of innovation by interconnecting digital devices to make human life more convenient and attractive. These smart objects are largely deployed as low power and lossy networks (LLNs) and use routing protocol for LLNs (RPL) for routing. Unfortunately, it is extremely vulnerable to a large variety of external and internal attacks to cause devastating and calamitous effects. However, this article's scope revolves around internal attacks only, where nodes are already part of a legitimate network. Various trust‐based mechanisms have been proposed to secure the RPL protocol from insider attackers. Existing trust mechanisms cause high energy depletion due to complex computation on the node level, which consequently decreases the performance of LLNs. Therefore, this article presents a novel hierarchical trust‐based mechanism “CTrust‐RPL” by assessing the trust of nodes based on their forwarding behaviors. This study ships complex trust‐related computations to the higher layer, known as the controller, to save computational, storage, and energy resources at the node level. We also compare the proposed mechanism with a state‐of‐the‐art technique calledSec‐trust. Our mechanism demonstrates superior performance in detecting and isolating blackhole attacks. The results depict thatCTrust‐RPLdetects and isolates 10% more malicious nodes thanSec‐trustin the same time‐lapse. The average packet loss ratio difference is less for our proposed mechanism, with 35% more energy efficiency.