无线传感器网络安全数据融合算法研究

在无人监管和恶劣的环境下，节点被捕获对无线传感器网络的安全构成了极大的威胁，被捕获的节点能发送伪造的数据以改变整个融合结果，这样就为融合结果引入了不确定性，为了抵抗节点被捕获的攻击以及量化融合结果中的不确定性，文中提出了一种基于信任的融合构架解决了融合过程中存在的安全问题。     

建立质量信誉 树立企业形象

通过对“质量、市场、效益’三者关系的分析,说明企业建立质量信誉、树立企业形象的重要性。就如何实现“建立质量信誉、树立企业形象”,结合工作经验,阐述自己的观点。     

上海顾客满意指数测评模型研究

介绍了顾客满意指数的发展，研究了中国市场上的顾客满意行为，在此基础上提出上海顾客满意指数的测评模型和方法，并得出3个主要结论：（1）信息对于顾客满意水平存在显著影响；（2）从实证角度验证了价值是顾客满意的主要起因；（3）顾客满意水平的提高将会显著促进企业声誉的提高。     

Improving Resilience against DDoS Attack in Unstructured P2P Networks

In unstructured peer-to-peer （P2P） systems such as Gnutella, a general routing search algorithm is used to blindly flood a query through network among peers. But unfortunately, malicious nodes could easily make use of the search approach launching distributed denial of service （DDoS） attack which aims at the whole network. In order to alleviate or minimize the bad effect due to behavior of malicious nodes using the flooding search mechanism, the paper proposes a Markov-based evaluation model which exerts the trust and reputation mechanism to computing the level of trustworthy of nodes having the information requested by evaluation of the nodes＇ history behavior. Moreover, it can differentiate malicious nodes as early as possible for isolating and controlling the ones＇ message transmitted. The simulation results of the algorithm proposed show that it could effectively isolate malicious nodes, and hold back the transmission of vicious messages so that it could enhance tolerance of DDoS based on flooding in Guutella-like P2P network.     

The Effects of Overhearing Peers Discuss an Authority's Fairness Reputation on Reactions to Subsequent Treatment.

Fairness heuristic theory was used to examine how information from one's peers affects an individual's interpretation of, and reactions to, an authority's subsequent behavior. Participants (N=105) overheard their peers discuss an experimenter's reputation (fair, unfair, or absent) before interacting with the experimenter who behaved more versus less fairly. Results showed that the social cues biased participants' subsequent information processing: Controlling for the experimenter's behavior, interactional justice mediated the effect of social cues on retaliation. Social cues and the authority's behavior also interacted to predict retaliation. Participants who were treated less fairly retaliated more after being led to expect fair treatment than did participants who heard no prior information about the experimenter. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Dynamic Reputation–based Consensus Mechanism for Blockchain

In recent years, Blockchain is gaining prominence as a hot topic in academic research. However, the consensus mechanism of blockchain has been criticized in terms of energy consumption and performance. Although Proof-of-Authority (PoA) consensus mechanism, as a lightweight consensus mechanism, is more efficient than traditional Proof-of-Work (PoW) and Proof-of-Stake (PoS), it suffers from the problem of centralization. To this end, on account of analyzing the shortcomings of existing consensus mechanisms, this paper proposes a dynamic reputation-based consensus mechanism for blockchain. This scheme allows nodes with reputation value higher than a threshold apply to become a monitoring node, which can monitor the behavior of validators in case that validators with excessive power cause harm to the blockchain network. At the same time, the reputation evaluation algorithm is also introduced to select nodes with high reputation to become validators in the network, thus increasing the cost of malicious behavior. In each consensus cycle, validators and monitoring nodes are dynamically updated according to the reputation value. Through security analysis, it is demonstrated that the scheme can resist the attacks of malicious nodes in the blockchain network. By simulation experiments and analysis of the scheme, the result verifies that the mechanism can effectively improve the fault tolerance of the consensus mechanism, reduce the time of consensus to guarantee the security of the system.     

How to understand “salable fake goods” and “unsalable quality goods”? An insight from the view of quality responsibility and consumers’ brand loyalty

A body of theoretical and practical research suggests technology innovation is the driving force for enterprise survival and development and that maintaining business ethics is an important guarantee in sustaining these enterprises developments. Fulfilling the “hard responsibility” of product quality based on technical standards and the “soft responsibility” of product quality based on business ethics is an important principle stimulating the benign interaction and continuous progress of technological innovation and business ethics, and realizing a balanced development of enterprises and society, which could promote positive brand and enterprise image to both stakeholders and consumers, helping consumers choose high-quality products in the market and social competition. However, the strange marketing phenomena of “salable fake goods” and “unsalable quality goods” shows that no systematic marketing strategies have been identified to date, that enterprises could adopt to effectively promote the recognition of consumers and turn them into a loyal customer group and have a stable market share. Based on customer buying behavior theory, cognitive consistency theory, signal theory, and social identity theory, this study explored the influencing mechanism of quality responsibility on brand loyalty of consumers and the mediating role of corporate reputation and brand identification, using 224 valid questionnaires from 16 communities (residents) in Shanxi and Henan provinces of China tested by SPSS 20.0 and AMOS 25.0. Results show that quality responsibility has a significant positive influence on brand behavior loyalty and brand attitude loyalty, and both corporate emotional reputation and brand identification play mediating roles in the relationship between quality responsibility and brand behavior loyalty, and quality responsibility and brand attitude loyalty. Additionally, corporate cognitive reputation only plays a mediating role in the relationship between quality responsibility and brand behavior loyalty. Obtained conclusions in the study provide references for enterprise managers and government decision-makers in exploring management strategies of expediting future technological development and next-generation upgrades & transformations, improving quality and technology benchmarks, optimizing product quality responsibility system and promoting sustainable social development.     

Transaction attributes and software outsourcing success: an empirical investigation of transaction cost theory

Abstract. In recent years, an increasing amount of attention has been paid to information systems (IS) outsourcing by practitioners as well as academics. However, our understanding of the factors that affect outsourcing success is hardly complete. By adopting transaction cost theory (TCT) as the theoretical foundation, this study analyses the implications of transaction attributes on the consequences of customized software outsourcing practice. The research model includes three exogenous variables (contractor reputation, asset specificity and uncertainty) and two endogenous variables (post‐contractual opportunism and outsourcing success). The moderating effects of asset specificity on the relationships between uncertainty and the endogenous variables are also examined. Based on data collected in Taiwan, a research model is constructed to test the hypotheses derived from the theory. The empirical evidence is generally supportive of the theory but with some important exceptions. In particular, contractor reputation and uncertainty have the predicted effects on the contractor’s post‐contractual opportunism perceived by the client and outsourcing success, but asset specificity shows a negative effect on post‐contractual opportunism and a positive effect on outsourcing success, which are opposite to the typical predictions of TCT. Thus, in addition to the supportive findings of the theory, this study also raises an important research question regarding the effects of asset specificity on outsourcing for future research to explore.     

Reputation Formalization for an Information–Sharing Multi–Agent System

We propose that through the formalization of concepts related to trust, a more accurate model of trust can be implemented. This paper presents a new model of trust that is based on the formalization of reputation. A multidisciplinary approach is taken to understanding the nature of trust and its relation to reputation. Through this approach, a practical definition of reputation is adopted from sociological contexts and a model of reputation is designed and presented.
Reputation is defined as role fulfillment. To formalize reputation, it is necessary to formalize the expectations placed upon an agent within a particular multi–agent system (MAS). In this case, the agents are part of an information–sharing society. Five roles are defined along with the ways in which these roles are objectively fulfilled. Through the measurement of role fulfillment, a vector representing reputation can be developed. This vector embodies the magnitude of the reputation and describes the patterns of behavior associated with the direction of the vector.
Experiments are conducted to verify the sensibility of the proposed models for role fulfillment and overall reputation. The simulation results show that the roles, defined for building reputation in an information–sharing MAS environment, react to different agent and user actions in a manner consistent with the formal definitions.     

A Reputation–Oriented Reinforcement Learning Strategy for Agents in Electronic Marketplaces

In this paper, we propose a reputation–oriented reinforcement learning algorithm for buying and selling agents in electronic market environments. We take into account the fact that multiple selling agents may offer the same good with different qualities. In our approach, buying agents learn to avoid the risk of purchasing low–quality goods and to maximize their expected value of goods by dynamically maintaining sets of reputable sellers. Selling agents learn to maximize their expected profits by adjusting product prices and by optionally altering the quality of their goods. Modeling the reputation of sellers allows buying agents to focus on those sellers with whom a certain degree of trust has been established. We also include the ability for buying agents to optionally explore the marketplace in order to discover new reputable sellers. As detailed in the paper, we believe that our proposed strategy leads to improved satisfaction for buyers and sellers, reduced communication load, and robust systems. In addition, we present preliminary experimental results that confirm some potential advantages of the proposed algorithm, and outline planned future experimentation to continue the evaluation of the model.