A proposed marketing strategy for GO2HK.COM

Within these few years, the Internet becomes popular in the world. There are many well-known websites, such as the eBay, Amazon and Yahoo, etc.. In foreign countries, Web auction is very famous for the Internet users in foreign countries, while it is a new kind of electronic business in Hong Kong. The trend of web auction has penetrated into Hong Kong in this few years, but it is still at a growth stage of the industry life cycle. Web auction seems to be a new type of business in electronic commerce, thus it can attract the people to participate it in future. The potential market for web auction is quite large. In Hong Kong, there are four major companies that work on the business of web auction. They are the (1) Red-dots, (2) Go2hk, (3) Yahoo and (4) Clubciti. Whereas, go2hk is the smallest company in terms of company size, it is the second in terms of the number of registered users. The industry is growing rapidly and facing a keen competition. Therefore, the company needs to have good marketing mix strategies to establish its brand name. This project aims to purpose an appropriate marketing strategy of GO2HK.COM, which can allow the company to match the consumer needs with marketing strategy. Interviews are conducted and questionnaire surveys are initiated to look into the most preferable strategy for GO2HK. Before doing the questionnaire survey, we have interviewed the company, in order to identify the current marketing mix first. After that, questionnaire surveys are used to access the information about the procedure of non-users, sellers and bidders. Based on the findings, a proposed marketing strategy is recommended for go2hk. To conclude, security is the most critical aspect that both users and non-users are highly concerned

Lightweight Blockchain Framework for Location-aware Peer-to-Peer Energy Trading

Peer-to-Peer (P2P) energy trading can facilitate integration of a large number of small-scale producers and consumers into energy markets. Decentralized management of these new market participants is challenging in terms of market settlement, participant reputation and consideration of grid constraints. This paper proposes a blockchain-enabled framework for P2P energy trading among producer and consumer agents in a smart grid. A fully decentralized market settlement mechanism is designed, which does not rely on a centralized entity to settle the market and encourages producers and consumers to negotiate on energy trading with their nearby agents truthfully. To this end, the electrical distance of agents is considered in the pricing mechanism to encourage agents to trade with their neighboring agents. In addition, a reputation factor is considered for each agent, reflecting its past performance in delivering the committed energy. Before starting the negotiation, agents select their trading partners based on their preferences over the reputation and proximity of the trading partners. An Anonymous Proof of Location (A-PoL) algorithm is proposed that allows agents to prove their location without revealing their real identity. The practicality of the proposed framework is illustrated through several case studies, and its security and privacy are analyzed in detail

Online advertising: analysis of privacy threats and protection approaches

Online advertising, the pillar of the “free” content on the Web, has revolutionized the marketing business in recent years by creating a myriad of new opportunities for advertisers to reach potential customers. The current advertising model builds upon an intricate infrastructure composed of a variety of intermediary entities and technologies whose main aim is to deliver personalized ads. For this purpose, a wealth of user data is collected, aggregated, processed and traded behind the scenes at an unprecedented rate. Despite the enormous value of online advertising, however, the intrusiveness and ubiquity of these practices prompt serious privacy concerns. This article surveys the online advertising infrastructure and its supporting technologies, and presents a thorough overview of the underlying privacy risks and the solutions that may mitigate them. We first analyze the threats and potential privacy attackers in this scenario of online advertising. In particular, we examine the main components of the advertising infrastructure in terms of tracking capabilities, data collection, aggregation level and privacy risk, and overview the tracking and data-sharing technologies employed by these components. Then, we conduct a comprehensive survey of the most relevant privacy mechanisms, and classify and compare them on the basis of their privacy guarantees and impact on the Web.Peer ReviewedPostprint (author's final draft

A Theory of Pricing Private Data

Personal data has value to both its owner and to institutions who would like to analyze it. Privacy mechanisms protect the owner's data while releasing to analysts noisy versions of aggregate query results. But such strict protections of individual's data have not yet found wide use in practice. Instead, Internet companies, for example, commonly provide free services in return for valuable sensitive information from users, which they exploit and sometimes sell to third parties. As the awareness of the value of the personal data increases, so has the drive to compensate the end user for her private information. The idea of monetizing private data can improve over the narrower view of hiding private data, since it empowers individuals to control their data through financial means. In this paper we propose a theoretical framework for assigning prices to noisy query answers, as a function of their accuracy, and for dividing the price amongst data owners who deserve compensation for their loss of privacy. Our framework adopts and extends key principles from both differential privacy and query pricing in data markets. We identify essential properties of the price function and micro-payments, and characterize valid solutions.Comment: 25 pages, 2 figures. Best Paper Award, to appear in the 16th International Conference on Database Theory (ICDT), 201