4,759 research outputs found

    Design and implement of robotic arm and control of moving via IoT with Arduino ESP32

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    Every day, the technologies are expanding and developed with extra things to them. A cloud computing (CC) and Internet of things (IoT) became deeply associated with technologies of the internet of future with one supply the other a way helping it for the successful. Arduino microcontroller is used to design robotic arm to pick and place the objects by the web page commands that can be used in many industrials. It can pick and place an object from source to destination and drive the screws in into its position safely. The robot arm is controlled using web page designed by (html) language which contain the dashboard that give the commands to move the servos in the desired angle to get the aimed direction accordingly. At the receiver end there are four servo motors which are made to be interfaced with the micro controller (Arduino) which is connected to the wireless network router. One of these is for the arm horizontally movement and two for arm knee, while the fourth is for catch tings or tight movement. Two ultra-sonic sensors are used for limiting the operation area of the robotic arm. Finally, Proteus program is used for the simulation the controlling of robot before the hardware installatio

    Continuous and transparent multimodal authentication: reviewing the state of the art

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    Individuals, businesses and governments undertake an ever-growing range of activities online and via various Internet-enabled digital devices. Unfortunately, these activities, services, information and devices are the targets of cybercrimes. Verifying the user legitimacy to use/access a digital device or service has become of the utmost importance. Authentication is the frontline countermeasure of ensuring only the authorized user is granted access; however, it has historically suffered from a range of issues related to the security and usability of the approaches. They are also still mostly functioning at the point of entry and those performing sort of re-authentication executing it in an intrusive manner. Thus, it is apparent that a more innovative, convenient and secure user authentication solution is vital. This paper reviews the authentication methods along with the current use of authentication technologies, aiming at developing a current state-of-the-art and identifying the open problems to be tackled and available solutions to be adopted. It also investigates whether these authentication technologies have the capability to fill the gap between high security and user satisfaction. This is followed by a literature review of the existing research on continuous and transparent multimodal authentication. It concludes that providing users with adequate protection and convenience requires innovative robust authentication mechanisms to be utilized in a universal level. Ultimately, a potential federated biometric authentication solution is presented; however it needs to be developed and extensively evaluated, thus operating in a transparent, continuous and user-friendly manner

    Strong authentication based on mobile application

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    The user authentication in online services has evolved over time from the old username and password-based approaches to current strong authentication methodologies. Especially, the smartphone app has become one of the most important forms to perform the authentication. This thesis describes various authentication methods used previously and discusses about possible factors that generated the demand for the current strong authentication approach. We present the concepts and architectures of mobile application based authentication systems. Furthermore, we take closer look into the security of the mobile application based authentication approach. Mobile apps have various attack vectors that need to be taken under consideration when designing an authentication system. Fortunately, various generic software protection mechanisms have been developed during the last decades. We discuss how these mechanisms can be utilized in mobile app environment and in the authentication context. The main idea of this thesis is to gather relevant information about the authentication history and to be able to build a view of strong authentication evolution. This history and the aspects of the evolution are used to state hypothesis about the future research and development. We predict that the authentication systems in the future may be based on a holistic view of the behavioral patterns and physical properties of the user. Machine learning may be used in the future to implement an autonomous authentication concept that enables users to be authenticated with minimal physical or cognitive effort

    Implicit Smartphone User Authentication with Sensors and Contextual Machine Learning

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    Authentication of smartphone users is important because a lot of sensitive data is stored in the smartphone and the smartphone is also used to access various cloud data and services. However, smartphones are easily stolen or co-opted by an attacker. Beyond the initial login, it is highly desirable to re-authenticate end-users who are continuing to access security-critical services and data. Hence, this paper proposes a novel authentication system for implicit, continuous authentication of the smartphone user based on behavioral characteristics, by leveraging the sensors already ubiquitously built into smartphones. We propose novel context-based authentication models to differentiate the legitimate smartphone owner versus other users. We systematically show how to achieve high authentication accuracy with different design alternatives in sensor and feature selection, machine learning techniques, context detection and multiple devices. Our system can achieve excellent authentication performance with 98.1% accuracy with negligible system overhead and less than 2.4% battery consumption.Comment: Published on the IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) 2017. arXiv admin note: substantial text overlap with arXiv:1703.0352

    Storage systems for mobile-cloud applications

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    Mobile devices have become the major computing platform in todays world. However, some apps on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud. This dissertation aims to ensure that the tasks in a mobile app that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. Existing distributed file systems and network file systems do not satisfy these requirements. Furthermore, current offloading platforms either do not support efficient file access for offloaded tasks or do not offload tasks with file accesses. The first part of the dissertation addresses this issue by designing and implementing an application-level file system named Overlay File System (OFS). OFS assumes a cloud surrogate is paired with each mobile device for task and storage offloading. To achieve high efficiency, OFS maintains and buffers local copies of data sets on both the surrogate and the mobile device. OFS ensures consistency and guarantees that all the reads get the latest data. To effectively reduce the network traffic and the execution delay, OFS uses a delayed-update mechanism, which combines write-invalidate and write-update policies. To guarantee location transparency, OFS creates a unified view of file data. The research tests OFS on Android OS with a real mobile application and real mobile user traces. Extensive experiments show that OFS can effectively support consistent file accesses from computation tasks, no matter where they run. In addition, OFS can effectively reduce both file access latency and network traffic incurred by file accesses. While OFS allows offloaded tasks to access the required files in a consistent and transparent manner, file accesses by offloaded tasks can be further improved. Instead of retrieving the required files from its associated mobile device, a surrogate can discover and retrieve identical or similar file(s) from the surrogates belonging to other users to meet its needs. This is based on two observations: 1) multiple users have the same or similar files, e.g., shared files or images/videos of same object; 2) the need for a certain file content in mobile apps can usually be described by context features of the content, e.g., location, objects in an image, etc.; thus, any file with the required context features can be used to satisfy the need. Since files may be retrieved from surrogates, this solution improves latency and saves wireless bandwidth and power on mobile devices. The second part of the dissertation proposes and develops a Context-Aware File Discovery Service (CAFDS) that implements the idea described above. CAFDS uses a self-organizing map and k-means clustering to classify files into file groups based on file contexts. It then uses an enhanced decision tree to locate and retrieve files based on the file contexts defined by apps. To support diverse file discovery demands from various mobile apps, CAFDS allows apps to add new file contexts and to update existing file contexts dynamically, without affecting the discovery process. To evaluate the effectiveness of CAFDS, the research has implemented a prototype on Android and Linux. The performance of CAFDS was tested against Chord, a DHT based lookup scheme, and SPOON, a P2P file sharing system. The experiments show that CAFDS provides lower end-to-end latency for file search than Chord and SPOON, while providing similar scalability to Chord

    A survey on android security: development and deployment hindrance and best practices

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    Android OS is the most popular mobile OS for the past few years. Vulnerabilities arise with respect to the increasing functionality of Android OS, impolitic app development practices of developers, end-user incautious and interestingly remediation for the vulnerabilities has been introduced frequently as well. To mitigate security risk factor Google has been updated, deprecated and restricted many system level APIs for 3rd party developers. Considering the consequences, this paper provides a wide overview of Android’s system level app development, privacy issues, and guideline for the developers about what measure they should consider while developing apps. We also discussed the historical development of Android OS and the end-users role to maintain privacy and to minimize security risks

    Code offloading in opportunistic computing

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    With the advent of cloud computing, applications are no longer tied to a single device, but they can be migrated to a high-performance machine located in a distant data center. The key advantage is the enhancement of performance and consequently, the users experience. This activity is commonly referred computational offloading and it has been strenuously investigated in the past years. The natural candidate for computational offloading is the cloud, but recent results point out the hidden costs of cloud reliance in terms of latency and energy; Cuervo et. al. illustrates the limitations on cloud-based computational offloading based on WANs latency times. The dissertation confirms the results of Cuervo et. al. and illustrates more use cases where the cloud may not be the right choice. This dissertation addresses the following question: is it possible to build a novel approach for offloading the computation that overcomes the limitations of the state-of-the-art? In other words, is it possible to create a computational offloading solution that is able to use local resources when the Cloud is not usable, and remove the strong bond with the local infrastructure? To this extent, I propose a novel paradigm for computation offloading named anyrun computing, whose goal is to use any piece of higher-end hardware (locally or remotely accessible) to offloading a portion of the application. With anyrun computing I removed the boundaries that tie the solution to an infrastructure by adding locally available devices to augment the chances to succeed in offloading. To achieve the goals of the dissertation it is fundamental to have a clear view of all the steps that take part in the offloading process. To this extent, I firstly provided a categorization of such activities combined with their interactions and assessed the impact on the system. The outcome of the analysis is the mapping to the problem to a combinatorial optimization problem that is notoriously known to be NP-Hard. There are a set of well-known approaches to solving such kind of problems, but in this scenario, they cannot be used because they require a global view that can be only maintained by a centralized infrastructure. Thus, local solutions are needed. Moving further, to empirically tackle the anyrun computing paradigm, I propose the anyrun computing framework (ARC), a novel software framework whose objective is to decide whether to offload or not to any resource-rich device willing to lend assistance is advantageous compared to local execution with respect to a rich array of performance dimensions. The core of ARC is the nference nodel which receives a rich set of information about the available remote devices from the SCAMPI opportunistic computing framework developed within the European project SCAMPI, and employs the information to profile a given device, in other words, it decides whether offloading is advantageous compared to local execution, i.e. whether it can reduce the local footprint compared to local execution in the dimensions of interest (CPU and RAM usage, execution time, and energy consumption). To empirically evaluate ARC I presented a set of experimental results on the cloud, cloudlet, and opportunistic domain. In the cloud domain, I used the state of the art in cloud solutions over a set of significant benchmark problems and with three WANs access technologies (i.e. 3G, 4G, and high-speed WAN). The main outcome is that the cloud is an appealing solution for a wide variety of problems, but there is a set of circumstances where the cloud performs poorly. Moreover, I have empirically shown the limitations of cloud-based approaches, specifically, In some circumstances, problems with high transmission costs tend to perform poorly, unless they have high computational needs. The second part of the evaluation is done in opportunistic/cloudlet scenarios where I used my custom-made testbed to compare ARC and MAUI, the state of the art in computation offloading. To this extent, I have performed two distinct experiments: the first with a cloudlet environment and the second with an opportunistic environment. The key outcome is that ARC virtually matches the performances of MAUI (in terms of energy savings) in cloudlet environment, but it improves them by a 50% to 60% in the opportunistic domain

    Development of an integrated web-based indoor parking system with sensors

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    Growing number of vehicles in recent years has an impact to road capacity and parking spaces. Even with support of an efficient public transport, some users prefer to use their personal vehicles. Hence, it resulted in lack of parking space in public areas. Looking for parking spaces is time, money and fuel consuming and causes unnecessary stress to drivers. This work will design and develop the sensing infrastructure which will be used as a part of an integrated smart parking system that integrates the sensing capability with wireless transmission to the central web portal. Then, the central web portal will provide a platform for vehicle parking reservation system made online through a computer. This system also permits drivers to make a reservation on available parking slots utilizing ID code keyed in for authentication and several indicators to denote availability, non-availability and reservation status at the parking slot. The communication technologies used has to upload and download information to and from the web. This work has shown that the development was successful for a single floor parking system and can be upgraded to multi-storey parking complex
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