Thesis (MTech (Business Administration))--Cape Peninsula University of Technology, 2018. / The key objective of this study is to determine the effectiveness of social media as a banking communication tool for a selected commercial bank in the Western Cape, South Africa. A secondary objective is to measure bank users’ perceptions regarding the use of social media to market various banking products and portfolios. The study employs a confusion matrix design to collect and analyse data, combining quantitative and qualitative research methods to understand and address the research problem. An emerging understanding of integrated banking communication is the foundation on which this research is built. It provides a context for the study, and highlights the effectiveness and limitations of social media in banking. A review of the relevant SMBA affirmed the importance of the social media in banking, and provided the basis for a framework and approach to interactive banking. A comprehensive social media banking application (SMBa) could be designed in line with banking practices to create an enabling business environment. This could reinforce banking communication for South African banks and enable a tailor-made banking communication model aligned to social media, in order to develop a sharing-culture.

University of Macau / Faculty of Science and Technology. / Department of Computer and Information Science

University of Macau / Faculty of Science and Technology. / Department of Computer and Information Science

University of Macau / Faculty of Social Sciences. / Department of Communication

University of Macau / Faculty of Social Sciences. / Department of Communication

A social network is a structure of individuals and organizations, which are connected by one or more types of interdependency, such as friendship, affinity, common interests or knowledge. Social networks use Web 2.0 technology, which is mostly based on a service-oriented architecture. We are studying patterns for social networks in this environment. A pattern is an encapsulated solution to a software problem in a given context, secure threats are possible in this context. We present a collection of patterns associated with the most important aspects of social networks, with emphasis on controlling the actions of the users of these networks. / by Carolina Marina. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2012. Mode of access: World Wide Web.

This research examines how incorporating interactivity into online video advertisements effects the following key marketing dependent variables: a) Involvement with the Advertisement, b) Ad Recall, c) Attitude towards the website, d) Attitude towards the Advertisement, e) Attitude towards the Brand, and f) Purchase Intention. Deriving from past Interactivity research, three important facets of interactivity are identified; User Control, Two-way Communication and Synchronicity. In order to test an Internet based 2 (User Control: high or low) X 2 (two-way communication: high or low) X 2 (synchronicity: high or low) between subjects experimental design, 8 different online video platforms were created. The online video experiment was administered to approximately 400 students in a large South-Eastern school. Overall the findings regarding interactivity in online video advertising found no significant effect of synchronicity on the dependent variables. There was however a significant interaction effect of user control and two-way communication on the dependent variables. These interaction effects were examined further with a cell means multiple comparison analysis. User control and two-way communication were found to have a significant interaction effect on ad recall, purchase intention and attitude towards the brand. User control had a significant effect on involvement and two-way communication had a significant effect on attitude towards the website. There was no effect of UC or TWC on attitude towards the ad. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

由於在線社交網絡的龐大用戶群和口碑效應的病毒式傳播特點，使用少量用戶吸引大量用戶的定向廣告策略在病毒營銷中是非常有效的。公司可以先提供免費商品給在線社交網絡上的小部份用戶，然後依靠這些用戶推薦此產品給他們的好友，從而達到提升產品整體銷售額的目的。在本文中，我們考慮如下在線社交網絡中廣告投放的問題:給定廣告投放資本，比如固定數目的免費產品，公司需要決定在線社交網絡中用戶會最終購買的概率。為了研究此問題，我們把在線社交網絡模擬成擁有或者沒有高聚合係數的無標度圖。我們使用多個影響機制來刻畫如此大規模網絡中的影響傳播，并且使用本地平均場技術來分析這些節點狀態會被影響機制所改變的網絡。我們運行了大量的仿真實驗來驗證我們的理論模型。這些模型能夠為設計在線社交網絡中的有效廣告投放策略提供認識和指導。 / 雖然口碑效應的病毒式傳播能有效地促進產品銷售，但是它同時也為惡意行為提供了機會:不誠實用戶會故意給他們的好友提供錯誤的推薦從而擾亂正常的市場份額分配。為了解決這個問題，我們提出了一個通用的檢測框架，并基於此檢測框架制定了一系列完全分佈式的檢測算法來識別在線社交網絡中的不誠實用戶。我們考慮了不誠實用戶採取基本策略和智能策略兩種情況。我們通過計算假陽性概率，假陰性概率和檢測不誠實用戶所需要的時間的分佈來度量檢測算法的性能。大量的仿真實驗不僅說明了不誠實推薦所造成的影響，也驗證了檢測算法的有效性。我們還應用前面提到的通用檢測框架來解決無線網格網絡(wireless mesh network)和點對點視頻直播網絡(peer-to-peer live streaming network)中的污染攻擊問題。在應用了網絡編碼的無線網格網絡中，污染攻擊是一個很嚴重的安全問題。惡意節點能夠輕易地發動污染攻擊，從而造成污染數據包的病毒式傳播進而消耗網絡資源。前面提到的通用檢測框架也能被用來解決此安全問題。明確地說，我們使用基於時間的校驗碼和批量驗證機制來決定污染數據包的存在與否，然後提出一系列完全分佈式的檢測算法。即使智能攻擊者存在時，此檢測算法仍然有效。這裡智能攻擊者指的是那些為了降低被檢測到的概率從而假裝合法節點傳輸有效數據包的節點。並且，為了解決攻擊者合作注入污染數據包的情形并加速檢測，我們還提出了一個增強的檢測算法。我們也給出了規範的分析來度量檢測算法的性能。最後，仿真實驗和系統原型驗證了我們的理論分析以及檢測算法的有效性。 / 污染攻擊還會對點對點視頻直播網絡基礎設施造成嚴重影響，比如說，它能夠減少網絡中的攻擊問題，我們仍然基於前面提到的通用檢測框架提出了分佈式的檢測算法來識別污染攻擊者。我們也提供了理論分析來度量檢測算法的性能從而證明了算法的有效性。 / Due to the large population in online social networks and the epidemic spreading of word-of-mouth effect, targeted advertisement which use a small fraction of buyers to attract a large population of buyers is very efficient in viral marketing, for example, companies can provide incentives (e.g., via free samples of a product) to a small group of users in an online social network, and these users can provide recommendations to their friends so as to increase the overall sales of the product. In particular, we consider the following advertisement problem in online social networks: given a fixed advertisement investment, e.g., a number of free samples, a company needs to determine the probability that users in the online social network will eventually purchase the product. To address this problem, we model online social networks as scale-free graphs with/without high clustering coefficient. We employ various influence mechanisms that govern the influence spreading in such large scale networks and use the local mean field technique to analyze them wherein states of nodes can be changed by various influence mechanisms. We carry out extensive simulations to validate our models which can provide insight on designing efficient advertising strategies in online social networks. / Although epidemic spreading of word-of-mouth effect can increase the sales of a product efficiently in viral marketing, it also opens doors for “malicious behaviors: dishonest users may intentionally give wrong recommendations to their friends so as to distort the normal sales distribution. To address this problem, we propose a general detection framework and develop a set of fully distributed detection algorithms to discover dishonest users in online social networks by applying the general detection framework. We consider both cases when dishonest users adopt (1) baseline strategy, and (2) intelligent strategy. We quantify the performance of the detection algorithms by deriving probability of false positive, probability of false negative and distribution function of time needed to detect dishonest users. Extensive simulations are carried out to illustrate the impact of dishonest recommendations and the effectiveness of the detection algorithms. / We also apply the general detection framework to address the problem of pollution attack in wireless mesh networks (WMNs) and peer-to-peer (P2P) streaming networks. Epidemic attack is a severe security problem in network-coding enabled wireless mesh networks, and malicious nodes can easily launch such form of attack to create an epidemic spreading of polluted packets and deplete network resources. The general detection framework can also be applied to address such security problem. Specifically, we employ the time-based checksum and batch verification to determine the existence of polluted packets, then propose a set of fully distributed detection algorithms. We also allow the presence of “smart attackers, i.e., they can pretend to be legitimate nodes to probabilistically transmit valid packets so as to reduce the chance of being detected. To address the case when attackers cooperatively inject polluted packets and speed up the detection, an enhanced detection algorithm is also developed. Furthermore, we provide formal analysis to quantify the performance of the detection algorithms. At last, simulations and system prototyping are also carried out to validate the theoretic analysis and show the effectiveness and efficiency of the detection algorithms. / To address the problem of pollution attack in P2P streaming networks, which is known to have a disastrous effect on existing P2P infrastructures, e.g., it can reduce the number of legitimate users by as much as 85%, we also propose distributed detection algorithms to identify pollution attackers by applying the general framework. Moreover, we provide theoretical analysis to quantify the performance of the detection algorithms so as to show their effectiveness and efficiency. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Li, Yongkun. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 148-157). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Influence Modeling in Online Social Networks --- p.7 / Chapter 2.1 --- Scale-free Graphs without High Clustering Coefficient --- p.8 / Chapter 2.1.1 --- Modeling Online Social Networks --- p.8 / Chapter 2.1.2 --- q-influence Model --- p.11 / Chapter 2.1.3 --- m-threshold Influence Model --- p.14 / Chapter 2.1.4 --- Majority Rule Influence Model --- p.16 / Chapter 2.2 --- Scale-free Graphs with High Clustering Coefficient --- p.19 / Chapter 2.3 --- Generalized Influence Models --- p.21 / Chapter 2.3.1 --- Deterministic Influence Model --- p.21 / Chapter 2.3.2 --- Probabilistic Influence Model --- p.25 / Chapter 2.4 --- Multi-state Model --- p.27 / Chapter 2.4.1 --- Example of 3-State Majority Rule --- p.32 / Chapter 3 --- Identifying Dishonest Recommenders in Online Social Networks --- p.35 / Chapter 3.1 --- General Detection Framework --- p.37 / Chapter 3.2 --- Modeling the Behaviors of Users --- p.41 / Chapter 3.2.1 --- Products and Recommendations --- p.41 / Chapter 3.2.2 --- Behaviors of Users --- p.43 / Chapter 3.3 --- Distributed Detection Algorithms --- p.45 / Chapter 3.3.1 --- Identifying Dishonest Recommenders when Baseline Strategy is Adopted --- p.46 / Chapter 3.3.2 --- Identifying Dishonest Recommenders when Intelligent Strategy is Adopted --- p.53 / Chapter 3.3.3 --- Complete Detection Algorithm --- p.57 / Chapter 3.4 --- Cooperative Algorithm to Speed up the Detection --- p.58 / Chapter 3.5 --- Algorithm Dealing with User Churn --- p.61 / Chapter 4 --- Identifying Pollution Attackers in Network Coding Enabled Wireless Mesh Networks --- p.64 / Chapter 4.1 --- Introduction on Wireless Mesh Networks and Pollution Attack --- p.64 / Chapter 4.2 --- Network Coding and Time-based Checksum Batch Verification --- p.66 / Chapter 4.3 --- Basic Detection Algorithms --- p.70 / Chapter 4.3.1 --- Core Idea of the Detection Algorithms --- p.71 / Chapter 4.3.2 --- Attackers with Imitation Probability δ = 0 --- p.74 / Chapter 4.3.3 --- Attackers with Imitation Probability δ > 0 --- p.78 / Chapter 4.3.4 --- Improvement on Probability of False Negative --- p.81 / Chapter 4.4 --- Enhanced Detection Algorithm --- p.82 / Chapter 4.4.1 --- Detection Algorithm --- p.82 / Chapter 4.4.2 --- Performance Analysis --- p.87 / Chapter 4.4.3 --- Detection Acceleration --- p.91 / Chapter 4.5 --- Alternative Detection Algorithms --- p.92 / Chapter 5 --- Identifying Pollution Attackers in Peer-to-Peer Live Streaming Systems --- p.95 / Chapter 5.1 --- Introduction on Peer-to-Peer Streaming Systems and the Problem of Pollution Attack --- p.95 / Chapter 5.2 --- Detection Algorithms --- p.97 / Chapter 5.2.1 --- Imitation Probability δ = 0 --- p.99 / Chapter 5.2.2 --- Imitation Probability δ > 0 --- p.102 / Chapter 5.2.3 --- Improvement on Probability of False Negative --- p.104 / Chapter 6 --- Performance Evaluation --- p.106 / Chapter 6.1 --- Influence Modeling in Online Social Networks --- p.107 / Chapter 6.1.1 --- Online Social Networks without High Clustering Coefficient --- p.107 / Chapter 6.1.2 --- Online Social Networks with High Clustering Coefficient --- p.113 / Chapter 6.1.3 --- Performance Evaluation of the Multi-state Model --- p.116 / Chapter 6.2 --- Performance Evaluation of the Detection Algorithms in Online Social Networks --- p.118 / Chapter 6.2.1 --- Synthesizing Dynamically Evolving Online Social Networks --- p.118 / Chapter 6.2.2 --- Impact of Wrong Recommendations --- p.120 / Chapter 6.2.3 --- Performance Evaluation of the Detection Algorithms --- p.121 / Chapter 6.3 --- Performance Evaluation of the Detection Algorithms in Wireless Mesh Networks --- p.126 / Chapter 6.3.1 --- Performance of the Basic Detection Algorithms --- p.126 / Chapter 6.3.2 --- Results from System Prototype --- p.131 / Chapter 6.3.3 --- Performance of the Enhanced Detection Algorithm --- p.132 / Chapter 6.4 --- Performance Evaluation of the Detection Algorithms in Peer-topeer Streaming Networks --- p.136 / Chapter 6.4.1 --- Performance of the Baseline Algorithm --- p.136 / Chapter 6.4.2 --- Performance of the Randomized Algorithm --- p.138 / Chapter 6.4.3 --- Derive Optimal Uploading Probability --- p.141 / Chapter 7 --- RelatedWork and Conclusion --- p.143

近年來，網絡的犯罪數量一直在迅速增加。現在，惡意軟件作者編寫惡意程序竊取用戶的個人信息，或提供基於垃圾郵件的營銷服務為利潤的地方。為了更有效地傳播惡意軟件，黑客已經開始瞄準流行的在線社交網絡服務（SNS）的 SNS用戶和服務的互動性之間固有的信任關係。一種常見的攻擊方法是惡意軟件自動登錄使用偷來的 SNS用戶憑據，然後提供接觸/被盜的用戶帳戶的朋友名單，他們通過在一些短消息嵌入惡意 URL（鏈接）。受害人然後認為是他們的朋友提供的鏈接，按一下被感染。然而，這種方法是有效的，惡意軟件來模仿人類類似的行為，它可以超越任何一個/兩個班輪對話。在這篇論文中，我們首先介紹一個新類型的攻擊，提供惡意網址 SNS用戶之間的合法對話。為了證明其概念，我們設計和實施名為 Hitchbot惡意軟件[1]，其中包括多個攻擊源，為實現我們所提出的攻擊。特別是，當一個 SNS用戶發送一個鏈接/ URL到他/她的朋友，Hitchbot悄悄地取代類似，但惡意攔截在幾個可能的點之一，互動式輸入/輸出鏈接系統。由於惡意鏈接在一些適當的對話上下文之間的合法用戶交付，這使得它更難以對受害者（以及吊具）來實現攻擊，從而可以大幅增加轉換率。這方法也使 Hitchbot的繞過大多數現有的防禦計劃，主要是靠對用戶的行為或流量異常檢測。 Hitchbot是基於客戶端模塊的形式可以順利上常見的社交網絡服務，包括雅虎和微軟的郵件客戶端和其他基於 Web瀏覽器，如 Facebook和 MySpace的社交網絡服務的加息。為量化 Hitchbot的效力，我們已經研究，交換和處理對 URL操作時用戶的行為。最後，我們研究通過自動在線分類 /識別惡意網址的可行性。尤其是不同類型的屬性/惡意 URL分類功能的有效性進行量化，從不同的惡意網址數據庫中獲得數據的基礎上，我們也考慮實時的準確性，嚴格的延遲要求影響和權衡需求的惡意網址分類。 / The number of cyber crimes has continued to increase rapidly in the recent years. It is now commonplace for malware authors to write malicious programs for prot by stealing user personal information or providing spam-based marketing services. In order to spread malware more effectively, hackers have started to target popular online social networking services (SNS) due to the inherent trust-relationship between the SNS users and the interactive nature of the services. A common attacking approach is for a malware to automatically login using stolen SNS user cre¬dentials and then deliver malicious URLs (links) to the people on the contact/friend-list of the stolen user account by embedding them in some short messages. The victim then gets infected by clicking on the links thought to be delivered by their friends. However, for this approach to be effective, the malware has to mimic human-like behavior which can be quite challenging for anything beyond one/two-liner conversations. In this thesis, we first introduce a new type of attacks called the social hitch-hiking attacks which use a stealthier way to deliver malicious URLs by hitch-hiking on legitimate conversations among SNS users. As a proof-of-concept, we have designed and implemented a malware named Hitchbot [1] which incorporates multiple attack vectors for the realization of our proposed social hitch-hiking attacks. In particular, when a SNS user sends a link/URL to his/her friends, Hitchbot quietly replaces it with a similar-looking, but malicious one by intercepting the link at one of the several pos¬sible points along the interactive-input/output chain of the system. Since the malicious link is delivered within some proper conversation context between the legitimate users, this makes it much more difficult for the victim (which is also the spreader) to realize the attack and thus can increase the conversion rate substantially. The hitch-hiking approach also enables Hitchbot to bypass most existing defense schemes which mainly rely on user-behavior or traffic anomaly detection. Hitchbot is in form of a client-based module which can hitch-hike on common social networking services including the Yahoo and Microsoft Messaging clients and other web-browser-based social-networking services such as Facebook and Myspace. To quantify the effectiveness of Hitchbot, we have studied the behavior of users in exchanging, handling and operating on URLs. Lastly, we study the feasibility of defending hitching-hiking attacks via automated online classification/identification of malicious URLs. In particular, the effectiveness of different types of attributes/features used in malicious URL classification are quantified based on a data obtained from various malicious URL databases. We also consider the implications and trade-offis of stringent latency requirement on the accuracy of real-time, on-demand malicious URL classifications. / Detailed summary in vernacular field only. / Lam, Ka Chun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 43-48). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Organization --- p.4 / Chapter 2 --- Related Work --- p.6 / Chapter 2.1 --- Exploiting Social Networking Services --- p.6 / Chapter 2.1.1 --- Malware Spreading Channels in SNS --- p.7 / Chapter 2.1.2 --- Common Exploits on SNS platforms --- p.10 / Chapter 2.2 --- Recent defense mechanisms of Malware --- p.12 / Chapter 3 --- A New Class of Attacks via Social Hitch-hiking --- p.14 / Chapter 3.1 --- The Social Hitch-hiking Attack --- p.14 / Chapter 3.1.1 --- The Interactive User Input/Output Chain --- p.16 / Chapter 3.1.2 --- Four Attack Vectors --- p.17 / Chapter 4 --- Attack Evaluation and Measurement --- p.26 / Chapter 4.1 --- Comparison of Attack Vectors --- p.26 / Chapter 4.2 --- Attack Measurement --- p.27 / Chapter 4.3 --- Defense against Hitch-hiking Attacks --- p.29 / Chapter 5 --- Defense via Malicious URL Classification --- p.31 / Chapter 5.1 --- Methodology --- p.31 / Chapter 5.2 --- Attributes --- p.33 / Chapter 5.2.1 --- Lexical attributes --- p.34 / Chapter 5.2.2 --- Webpage content attributes --- p.34 / Chapter 5.2.3 --- Network attributes --- p.34 / Chapter 5.2.4 --- Host-based attributes --- p.35 / Chapter 5.2.5 --- Link popularity attributes --- p.36 / Chapter 5.3 --- Performance Evaluation and Discussions --- p.36 / Chapter 6 --- Conclusion and Future work --- p.41

This dissertation analyzes transformation in early 21st century educational practice through the lens of information technology (IT) use at a private, women's university in Jeddah, Saudi Arabia. Academic and extracurricular Internet use, which is enabled through ubiquitous mobile devices, students' attitudes toward information and communication technology (ICT), and the nature and purpose of their activities in social network sites (SNS) will be discussed alongside critical analysis of peer-to-peer teaching and learning in relation to knowledge production and educational practice. Richly ethnographic discussion delves into emerging global education paradigms that are (re)configuring the experience of women's higher education in Saudi Arabia and influencing women's participation in public, economic, and political spheres from which they might have been previously excluded. This dissertation also seeks to engage bigger questions about young people's intimate relationships with ICTs and the nuances of the networked spaces in which they experience life online as students and citizens coming of age as members of the digital generation.