GPS based Bluetooth Broadcasting – Long Range Solution

In this paper, GPS based Bluetooth broadcasting for long range is proposed. System model for Long range broadcasting of messages with multiple piconets and dynamically created threshold devices, based on GPS information is presented. Our simulation results have shown that, message can be received by those devices which are out of the initial Bluetooth range in reasonable time. Flooding of multiple messages could be avoided by applying hash function. With this solution, long range data and voice communication could be done with free of cost also can be used for commercial advertising purpose

A Contribution to Theory Building for Mobile Marketing: Categorizing Mobile Marketing Campaigns through Case Study Research

Marketing experts consider the mobile device as an extremely promising marketing tool as it supports them to cope with their major challenge: getting time and attention from customers. Current mobile marketing research mostly covers success factors and acceptance analysis. Categorization, when addressed, lacks in appropriate foundation and is not linked to objectives at all. In this article we examine 55 case studies in order to identify relevant characteristics of mobile marketing campaigns. The outcome of the paper is the derivation of four mobile marketing standard types and an examination of campaign objectives that can be addressed by mobile marketing. The proposed scheme allows to unambiguously characterize any given mobile marketing campaign and to identify the respective objectives.

Influencing factors on user acceptance of location-based advertising outside and inside retail stores

JEL -M31 Marketing M37 AdvertisingDe 2013 a 2014, a penetração do smartphone a nível mundial aumentou 25%, até 1.6 biliões de usuários. Até ao ano de 2018, são esperadas que mais de 2.5 biliões de pessoas usem smartphones, com o tempo médio de uso a ser atualmente já maior do que o da televisão. Com o crescente aumento do tempo que as pessoas gastam no uso dos seus smartphones, cresce também o impacto destes dispositivos no comportamento das pessoas. Já hoje, os smartphones são vistos como pessoais e, muitas vezes, confiáveis como primeira fonte para informação necessária. Em concordância com estes desenvolvimentos, partes significativas de orçamentos de marketing são deslocadas dos canais tradicionais para os canais móveis e os profissionais de marketing procuram por novas oportunidades para entregar mensagens de publicidade a potenciais clientes. Com a publicidade baseada em localização, os profissionais de marketing têm um instrumento que é capaz de facultar informação em relação direta com a localização geográfica de um usuário, num momento em que o usuário a vê como relevante e é mais provável que aja em resultado. Graças a uma nova tecnologia designada de Beacon, o rastreamento de localização é agora possível mesmo dentro de edifícios fechados e preciso até menos de um metro. De forma a que os profissionais de marketing usem essa informação, os consumidores têm de dar o seu consentimento e instalar um aplicativo dedicado nos seus smartphones. Dentro desta tese, foram analisados os fatores que influenciam o consentimento da publicidade baseada em localização por parte dos usuários. A aplicação da pesquisa estatística dos dados, coletados num estudo com 109 usuários internacionais de smartphones, levou às conclusões de que a utilidade percebida desta tecnologia de publicidade é o que influencia mais os usuários, seguido da facilidade de uso e da atitude geral para com a publicidade. Os resultados podem contribuir para o futuro desenvolvimento de campanhas de publicidade baseadas em localização, fornecendo aos profissionais de marketing perceções substanciais em fatores-chave para campanhas bem sucedidas.From 2013 to 2014, smartphone penetration worldwide rose by 25% up to 1.6 billion users. By the year 2018 even more than 2.5 billion people are expected to use smartphones, with the average use time being already today higher than the one of television. With the increasing time people spend using their smartphones, also the impact of this devices on people’s behavior grows. Already today, smartphones are perceived as personal and often trusted as the first source for necessary information. In accordance with these developments, significant shares of marketing budgets are shifted from traditional media to the mobile channel and marketers look for new possibilities to deliver advertising messages to potential customers. With location-based advertising, marketers have an instrument, which is capable of delivering information in direct relation to a user’s geo-location at the time when a user perceives them as relevant and is most likely to react upon it. Thanks to a new technology called Beacon, location tracking is now possible even inside closed buildings and accurate up to less than one meter. In order for marketers to use this technology, customers need to give their approval and install a dedicated app on their smartphones. Within this thesis, factors that influence users’ acceptance of location-based advertising were analyzed. Application of statistical research on the data, collected in a study with 109 international smartphone users, led to the conclusions that the perceived usefulness of this advertising technology influences user’s acceptance the most, followed by the ease of use and the overall attitude toward advertising. The results can contribute to future development of location-based advertising campaigns, providing marketers with substantial insights on key factors for successful campaigns. Keywords:; beacon

BLEWhisperer: Exploiting BLE Advertisements for Data Exfiltration

Bluetooth technology has enabled short-range wireless communication for billions of devices. Bluetooth Low-Energy (BLE) variant aims at improving power consumption on battery-constrained devices. BLE-enabled devices broadcast information (e.g., as beacons) to nearby devices via advertisements. Unfortunately, such functionality can become a double-edged sword at the hands of attackers. In this paper, we primarily show how an attacker can exploit BLE advertisements to exfiltrate information from BLE-enable devices. In particular, our attack establishes a communication medium between two devices without requiring any prior authentication or pairing. We develop a proof-of-concept attack framework on the Android ecosystem and assess its performance via a thorough set of experiments. Our results indicate that such an exfiltration attack is indeed possible though with a low data rate. Nevertheless, we also demonstrate potential use cases and enhancements to our attack that can further its severeness. Finally, we discuss possible countermeasures to prevent such an attack.Comment: 20 pages, 6 figure

A COMPARATIVE ANALYSIS OF DEVICES VIA THE BLUETOOTH PROTOCOL IN A TIME SERIES ANALYSIS

The utilization of the Bluetooth protocol has provided many with the seamless transmission of data to multiple devices. Given its versatility and being an efficient process of connectivity, it has become one of the preferred methods of wireless connections. Despite this, an aspect of the Bluetooth function is still vulnerable to being exploited by having the data transmission stolen. This project answered the following questions: “How does one reduce the vulnerability by comparing normal and abnormal Bluetooth data?”, “How does one identify outlying variables within the data?” and “How can we improve the Bluetooth function?”. This project relied on previous research based on establishing patterns of life in Bluetooth devices in order to categorize such devices using their data. By applying a similar approach, this research is focused on creating a methodology of capturing, detecting, and analyzing normal and abnormal Bluetooth data. By creating two scenarios involving Bluetooth devices, one where a normal transmission happens and another where a Bluetooth Hijacking occurs, comparable scans were made and then compared. The findings were as follows: The analysis shows it is possible to categorize the Bluetooth devices and attribute their data to create a pattern of life. By comparing normal and abnormal Bluetooth data, vulnerability can be reduced by detecting abnormal data much sooner and thus alerting the user of any attacks. To identify the outlying variables, certain characteristics within the Bluetooth packet in Wireshark can be selected and shown in the RStudio graph. Having these variables displayed creates a better visual to further analyze the data captured and identify any outlying variables. This project also introduced methods that the Bluetooth function can be improved on by including the introduction of more pin inputs when entering Bluetooth networks, as well as the idea to introduce a feature that authenticates the termination of a Bluetooth connection. The conclusion of this project revealed that these captures and analysis allow for establishing a pattern of life of what would be considered normal and abnormal data within the Bluetooth IoT and can be expanded into other Bluetooth devices

Enhancing Mobile Data Collection Applications with Sensing Capabilities

Over the past years, using smart mobile devices for data collection purposes has become ubiquitous in many application domains, replacing traditional pen-and-paper based data collection approaches. However, in many cases, modern approaches only aim to replicate traditional data collection instruments (e.g., paper-based questionnaires) in a digital from (e.g., smartphone surveys). Thereby, the full potential of smart mobile devices is often not fully exploited. Most modern smart mobile devices comprise a variety of sensing capabilities, which may provide valuable data, and thus insights. In addition, external sensors and devices may be easily connected to become part of the overall data collection process. In order to integrate sensing functionality into existing data collection applications, one has to address each desired sensor manually from within the application, which may cause severe development effort. Alternatively one can fall back on dedicated sensing frameworks to perform sensing operations. However, the latter are often targeted towards one specific mobile platform (e.g., iOS or Android) or lack required functionality, which may also lead to unnecessary development overhead when implementing mobile data collection applications. To cope with these issues, a cross-platform mobile sensing framework that can be used within large-scale mobile data collection scenarios was developed in the context of this thesis. Thereby, an in-depth look at existing mobile sensing frameworks as well as common use case scenarios is taken. Further, requirements derived from the latter are explicitly stated and were taken into consideration in the course of the overall development process. The latter is documented and discussed in detail in the course of this thesis, including the design of a framework architecture, implementation details and the integration of the framework into mobile data collection applications