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A Meta-Analysis of the Relationship between Customer Misbehavior and Emotional Labor  [PDF]
Hui Man, Feiyan Liu, Yutong Gao
Open Journal of Social Sciences (JSS) , 2017, DOI: 10.4236/jss.2017.56014
Abstract: A meta-analysis was used to aggregate results from studies examining the relationship between customer misbehavior and emotional labor. Analysis of 21 studies (N = 12,299) met the criteria for inclusion in the meta-analysis. The result of meta-analysis showed: customer misbehavior had significant effects on employee emotional labor. Specifically, customer misbehavior had a positive correlation to surface acting, and had a negative correlation to deep acting. Moderator analyses revealed that cultural difference has significant moderating effects on the relationship between customer misbehavior and emotional labor (including surface acting and deep acting). In addition, the correlation between customer misbehavior and surface acting in the context of China is less than it in the context of other countries.
Misbehavior in Mobile Application Markets  [PDF]
Steven Meyer
Computer Science , 2011,
Abstract: Mobile application markets facilitate the distribution of applications and thus help developers advertise their work and customers find useful applications. In addition, the operators of mobile application markets can control the quality and the content of the applications. These markets are growing rapidly with more than 300'000 application in the App Store of Apple and more than 100'000 in the Android Market of Google. This is not only a great opportunity for phone manufacturers to earn money but also for indie developers (single or small teams of developers with small financial support) who can thus have a great distribution channel. Steve Demeter, the Trim game developer for iPhone, became millionaire with a single puzzle game . Obviously, as new markets generate a lot of money, the temptation of misbehavior to steal part of the benefits is big. The first famous case was the one of Molinker who self-rated his applications with 5 stars to pump up his ranking in order to increase its revenue stream. In this report, we will consider the problem of misbehavior in mobile application markets. We will investigate multiple attacks by misbehaving developers, users or network operators that aim at breaking rules for their own benefit, managing to outwit the operators' control on which applications can be installed. We notably suggest novel attacks that may affect mobile markets in the future: in particular, we show that it is possible to get revenue for applications created by someone else, trick a user to download and buy an application and new ways to pump up an application's ranking. We will also discuss possible solutions against spyware applications and cheating developer
Data-centric Misbehavior Detection in VANETs  [PDF]
Sushmita Ruj,Marcos Antonio Cavenaghi,Zhen Huang,Amiya Nayak,Ivan Stojmenovic
Computer Science , 2011,
Abstract: Detecting misbehavior (such as transmissions of false information) in vehicular ad hoc networks (VANETs) is very important problem with wide range of implications including safety related and congestion avoidance applications. We discuss several limitations of existing misbehavior detection schemes (MDS) designed for VANETs. Most MDS are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners, e.g. for gaining access to a particular lane. Because of this (\emph{rational behavior}), it is more important to detect false information than to identify misbehaving nodes. We introduce the concept of data-centric misbehavior detection and propose algorithms which detect false alert messages and misbehaving nodes by observing their actions after sending out the alert messages. With the data-centric MDS, each node can independently decide whether an information received is correct or false. The decision is based on the consistency of recent messages and new alert with reported and estimated vehicle positions. No voting or majority decisions is needed, making our MDS resilient to Sybil attacks. Instead of revoking all the secret credentials of misbehaving nodes, as done in most schemes, we impose fines on misbehaving nodes (administered by the certification authority), discouraging them to act selfishly. This reduces the computation and communication costs involved in revoking all the secret credentials of misbehaving nodes.
美国社区创客教育的载体  [PDF]
开放教育研究 , 2015,
Abstract: 美国推进全民创客行动的进程中,非常重视社区创客空间的建设,并积极动员全美各地区、各社区重视将创客行动纳入区域与社区的发展计划,众多社区创客空间明确提出自身所担负的教育责任。基于对美国若干社区创客空间建设目标与运行方式的分析,本文探析了作为社区创客教育主要载体的创客空间的发展动力、功用与应用。研究发现,技术与社会的发展是美国社区创客空间发展的根本动力,全美创客行动的深化实践则是美国社区创客空间发展的基本依托。在功用维度,美国社区创客空间具有培养社区成员创造创新能力、提升社区成员创业就业技能的教育功用,同时又具有创生就业创业机会、促进社区经济发展的经济功用;在应用维度,美国社区创客空间主要通过精心规划功能区支持多样化创客活动、采用适当的运行形式、多途径开展创客教育、多方位促进创客空间高效利用等实现并优化空间的应用。
Subsiding routing misbehavior in MANET using "Mirror Model"  [PDF]
Md. Amir Khusru Akhtar,G. Sahoo
Computer Science , 2013, DOI: 10.5121/csit.2013.3701
Abstract: Noncooperation or failure to work together is a big challenge that surely degrades the performance and reliability of Mobile Adhoc Networks. In MANETs, nodes have dual responsibilities of forwarding and routing, that's why it needs unison with nodes. To sort out non-cooperation a real life behavior should be implemented, so that misbehavior is nullified. In this paper, we present the "Mirror Model" that strictly enforces cooperation due to its punishment strategy. Node's behavior is watched by its neighbors in PON mode, to update the NPF, NPRF values for a threshold time. After the expiry of the threshold time each node calculates the PFR and broadcasts its neighbors. Similarly all neighbors broadcasted PFR is received and processed by the node to define the 'G' and 'BP' values. The G value is used to isolate selfish nodes from the routing paths and BP denotes the amount of packets to be dropped by an honest node against a selfish node in spite of its misbehavior/packet drops. Cooperation within the neighbors, certainly result in subsiding misbehavior of selfish nodes, therein enhancing cooperation of the whole MANET. This model ensures honesty and reliability in MANET because it does not eliminate a node, but it behaves in the same way as the node behaved. Therefore, it justifies its name, after all mirrors reflects the same. We have implemented the model in "GloMoSim" on top of the DSR protocol, resulting its effectiveness, as compared to the DSR protocol when the network is misconducting for its selfish needs.
An Immuno-Inspired Approach to Misbehavior Detection in Ad Hoc Wireless Networks  [PDF]
Martin Drozda,Sebastian Schildt,Sven Schaust,Helena Szczerbicka
Computer Science , 2010,
Abstract: We propose and evaluate an immuno-inspired approach to misbehavior detection in ad hoc wireless networks. Node misbehavior can be the result of an intrusion, or a software or hardware failure. Our approach is motivated by co-stimulatory signals present in the Biological immune system. The results show that co-stimulation in ad hoc wireless networks can both substantially improve energy efficiency of detection and, at the same time, help achieve low false positives rates. The energy efficiency improvement is almost two orders of magnitude, if compared to misbehavior detection based on watchdogs. We provide a characterization of the trade-offs between detection approaches executed by a single node and by several nodes in cooperation. Additionally, we investigate several feature sets for misbehavior detection. These feature sets impose different requirements on the detection system, most notably from the energy efficiency point of view.
Wireless Node Misbehavior Detection Using Genetic Algorithm  [PDF]
P.C. Kishore Raja,M. Suganthi,R. Sunder
Information Technology Journal , 2008,
Abstract: This study presents behavior-based wireless network intrusion detection using genetic algorithm that assumes misbehavior identification by observing a deviation from normal or expected behavior of wireless node. The feature set is constructed from MAC layer to profile the normal behavior of wireless node. The wireless node behavior is learned by using genetic algorithm and current wireless node behavior can be predicted by genetic algorithm based on the past behavior. A 3-tuple value i.e., entropy index, newness index, mismatch index is calculated for constructed feature set in a session. The 3-tuple value of a wireless node behavior in a session are compared with expected non-intrusive behavior 3-tuple value to find intrusions. The performance of wireless intrusion detection is evaluated using detection probability and false alarm probability.
Algebraic Watchdog: Mitigating Misbehavior in Wireless Network Coding  [PDF]
MinJi Kim,Muriel Medard,Joao Barros
Mathematics , 2010,
Abstract: We propose a secure scheme for wireless network coding, called the algebraic watchdog. By enabling nodes to detect malicious behaviors probabilistically and use overheard messages to police their downstream neighbors locally, the algebraic watchdog delivers a secure global self-checking network. Unlike traditional Byzantine detection protocols which are receiver-based, this protocol gives the senders an active role in checking the node downstream. The key idea is inspired by Marti et al.'s watchdog-pathrater, which attempts to detect and mitigate the effects of routing misbehavior. As an initial building block of a such system, we first focus on a two-hop network. We present a graphical model to understand the inference process nodes execute to police their downstream neighbors; as well as to compute, analyze, and approximate the probabilities of misdetection and false detection. In addition, we present an algebraic analysis of the performance using an hypothesis testing framework that provides exact formulae for probabilities of false detection and misdetection. We then extend the algebraic watchdog to a more general network setting, and propose a protocol in which we can establish trust in coded systems in a distributed manner. We develop a graphical model to detect the presence of an adversarial node downstream within a general multi-hop network. The structure of the graphical model (a trellis) lends itself to well-known algorithms, such as the Viterbi algorithm, which can compute the probabilities of misdetection and false detection. We show analytically that as long as the min-cut is not dominated by the Byzantine adversaries, upstream nodes can monitor downstream neighbors and allow reliable communication with certain probability. Finally, we present simulation results that support our analysis.
Modeling Misbehavior in Cooperative Diversity: A Dynamic Game Approach  [cached]
Sintayehu Dehnie,Nasir Memon
EURASIP Journal on Advances in Signal Processing , 2009, DOI: 10.1155/2009/927140
Abstract: Cooperative diversity protocols are designed with the assumption that terminals always help each other in a socially efficient manner. This assumption may not be valid in commercial wireless networks where terminals may misbehave for selfish or malicious intentions. The presence of misbehaving terminals creates a social-dilemma where terminals exhibit uncertainty about the cooperative behavior of other terminals in the network. Cooperation in social-dilemma is characterized by a suboptimal Nash equilibrium where wireless terminals opt out of cooperation. Hence, without establishing a mechanism to detect and mitigate effects of misbehavior, it is difficult to maintain a socially optimal cooperation. In this paper, we first examine effects of misbehavior assuming static game model and show that cooperation under existing cooperative protocols is characterized by a noncooperative Nash equilibrium. Using evolutionary game dynamics we show that a small number of mutants can successfully invade a population of cooperators, which indicates that misbehavior is an evolutionary stable strategy (ESS). Our main goal is to design a mechanism that would enable wireless terminals to select reliable partners in the presence of uncertainty. To this end, we formulate cooperative diversity as a dynamic game with incomplete information. We show that the proposed dynamic game formulation satisfied the conditions for the existence of perfect Bayesian equilibrium.
A Novel Methodology to Overcome Routing Misbehavior in MANET using Retaliation Model  [PDF]
Md. Amir Khusru Akhtar,G. Sahoo
Computer Science , 2013, DOI: 10.5121/ijwmn.2013.5414
Abstract: MANET is a cooperative network in which nodes are responsible for forwarding as well as routing. Noncooperation is still a big challenge that certainly degrades the performance and reliability of a MANET. This paper presents a novel methodology to overcome routing misbehavior in MANET using Retaliation Model. In this model node misbehavior is watched and an equivalent misbehavior is given in return. This model employs several parameters such as number of packets forwarded, number of packets received for forwarding, packet forwarding ratio etc. to calculate Grade and Bonus Points. The Grade is used to isolate selfish nodes from the routing paths and the Bonus Points defines the number of packets dropped by an honest node in retaliation over its misconducts. The implementation is done in "GloMoSim" on top of the DSR protocol. We obtained up to 40% packet delivery ratio with a cost of a minimum of 7.5% overhead compared to DSR. To minimize total control traffic overhead we have included the FG Model with our model and it reduces the overhead up to 75%. This model enforces cooperation due to its stricter punishment strategy and justifies its name.
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