145 research outputs found

    LOCATION-BASED MARKETING: CONCEPTS, TECHNOLOGIES AND SERVICES

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    siirretty Doriast

    New Uses for Old Smartphones

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    Smartphones play an important role in our daily life. It is often the case, however, that they are replaced before they have been used to the full extent of their capacities. We investigate the feasibility of collecting old yet still very powerful smartphones and the potential societal impact of implementing some strategies for utilizing them in the fields of medicine, education and environmental observation. In our conclusions, we describe the expected impact of the many schemes and comment on which ideas we anticipate to be the most effective

    Towards Secure, Power-Efficient and Location-Aware Mobile Computing

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    In the post-PC era, mobile devices will replace desktops and become the main personal computer for many people. People rely on mobile devices such as smartphones and tablets for everything in their daily lives. A common requirement for mobile computing is wireless communication. It allows mobile devices to fetch remote resources easily. Unfortunately, the increasing demand of the mobility brings many new wireless management challenges such as security, energy-saving and location-awareness. These challenges have already impeded the advancement of mobile systems. In this dissertation we attempt to discover the guidelines of how to mitigate these problems through three general communication patterns in 802.11 wireless networks. We propose a cross-section of a few interesting and important enhancements to manage wireless connectivity. These enhancements provide useful primitives for the design of next-generation mobile systems in the future.;Specifically, we improve the association mechanism for wireless clients to defend against rogue wireless Access Points (APs) in Wireless LANs (WLANs) and vehicular networks. Real-world prototype systems confirm that our scheme can achieve high accuracy to detect even sophisticated rogue APs under various network conditions. We also develop a power-efficient system to reduce the energy consumption for mobile devices working as software-defined APs. Experimental results show that our system allows the Wi-Fi interface to sleep for up to 88% of the total time in several different applications and reduce the system energy by up to 33%. We achieve this while retaining comparable user experiences. Finally, we design a fine-grained scalable group localization algorithm to enable location-aware wireless communication. Our prototype implemented on commercial smartphones proves that our algorithm can quickly locate a group of mobile devices with centimeter-level accuracy

    Seamless Outdoors-Indoors Localization Solutions on Smartphones: Implementation and Challenges

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    © ACM, 2016. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in http://doi.org/10.1145/2871166[EN] The demand for more sophisticated Location-Based Services (LBS) in terms of applications variety and accuracy is tripling every year since the emergence of the smartphone a few years ago. Equally, smartphone manufacturers are mounting several wireless communication and localization technologies, inertial sensors as well as powerful processing capability, to cater to such LBS applications. A hybrid of wireless technologies is needed to provide seamless localization solutions and to improve accuracy, to reduce time to fix, and to reduce power consumption. The review of localization techniques/technologies of this emerging field is therefore important. This article reviews the recent research-oriented and commercial localization solutions on smartphones. The focus of this article is on the implementation challenges associated with utilizing these positioning solutions on Android-based smartphones. Furthermore, the taxonomy of smartphone-location techniques is highlighted with a special focus on the detail of each technique and its hybridization. The article compares the indoor localization techniques based on accuracy, utilized wireless technology, overhead, and localization technique used. The pursuit of achieving ubiquitous localization outdoors and indoors for critical LBS applications such as security and safety shall dominate future research efforts.This research was sponsored by Koya University, Kurdistan Region-Iraq. The authors also would like to thank Dr. Ali Al-Sherbaz (from the University of Northampton-UK) and Dr. Naseer Al-Jawad (from the University of Buckingham-UK) for providing and improving the quality of this article in terms of academic and technical writing.Maghdid, HS.; Lami, IA.; Ghafoor, KZ.; Lloret, J. (2016). Seamless Outdoors-Indoors Localization Solutions on Smartphones: Implementation and Challenges. ACM Computing Surveys. 48(4):1-34. https://doi.org/10.1145/2871166S134484I. Adusei, K. Kyamakya, and K. Jobmann. 2002. Mobile positioning technologies in cellular networks: An evaluation of their performance metrics. Proceedings of MILCOM 2002. 2, 1239--1244.Faiz Anuar and Ulrike Gretzel. 2011. Privacy concerns in the context of location-based services for tourism. In ENTER 2011 Conference, Innsbruck, Austria.A. Bensky. 2008. Wireless Positioning Technologies and Applications. Artech House, Inc. Norwood, MA.Azzedine Boukerche, Horacio A. B. F. Oliveira, Eduardo F. Nakamura, and Antonio A. F. Loureiro. 2007. Localization systems for wireless sensor networks. IEEE Wireless Communications 14, 6, 6--12.Azzedine Boukerche, Horacio A. B. F. Oliveira, Eduardo F. Nakamura, and Antonio A. F. Loureiro. 2008. Secure localization algorithms for wireless sensor networks. IEEE Communications Magazine 46, 4, 96--101.Azzedine Boukerche, Horacio A. B. F. Oliveira, Eduardo F. Nakamura, and Antonio A. F. Loureiro. 2008. Vehicular ad hoc networks: A new challenge for localization-based systems. Computer Communications 31, 12, 2838--2849.M. Butler. 2011. Android: Changing the Mobile Landscape. PERVASIVE Computing 10, 1, 4--7.J. Caffery and G. Stuber. 1998. Overview of radiolocation in CDMA cellular systems. IEEE Communications Magazine 36, 4, 38--45.Suma S. Cherian and Ashok N. Rudrapatna. 2013. LTE location technologies and delivery solutions. Bell Labs Technical Journal 18, 2, 175--194.M. Ciurana, D. Lopez, and F. Barcelo-Arroyo. 2009. SofTOA: Software ranging for TOA-based positioning of WLAN terminals. Location and Context Awareness 207--221.Paul Craven, Ronald Wong, Neal Fedora, and Paul Crampton. 2013. Studying the Effects of Interference on GNSS Signals. International Technical Meeting. San Diego, California: The Institute of Navigation, 893--186.D. Dardari, P. Closas, and P. M. Djuric. 2015. Indoor tracking: Theory, methods, and technologies. IEEE Transactions on Vehicular Technology 64, 4, 1263--1278.Guido De Angelis, Giuseppe Baruffa, and Saverio Cacopardi. 2012. GNSS/Cellular hybrid positioning system for mobile users in urban scenarios. IEEE Transactions on Intelligent Transportation Systems 14, 1, 313--321.Horacio Antonio Braga Fernandes De Oliveira, Azzedine Boukerche, Eduardo Freire Nakamura, and Antonio Alfredo Ferreira Loureiro. 2009. An efficient directed localization recursion protocol for wireless sensor networks. IEEE Transactions on Computers 58, 5, 677--691.Francescantonio Della Rosa, Mauro Pelosi, and Jari Nurmi. 2012. Human-induced effects on RSS ranging measurements for cooperative positioning. International Journal of Navigation and Observation 13.Zhongliang Deng, Yanpei Yu, Xie Yuan, Neng Wan, and Lei Yang. 2013. Situation and development tendency of indoor positioning. China Communications 10, 3, 42--55.Mohammed Elbes, Ala Al-Fuqaha, and Muhammad Anan. 2013. A precise indoor localization approach based on particle filter and dynamic exclusion techniques. Network Protocols and Algorithms 5, 2, 50--71.R. Faragher and R. Harle. 2013. SmartSLAM--an efficient smartphone indoor positioning system exploiting machine learning and opportunistic sensing. In ION GNSS.Zahid Farid, Rosdiadee Nordin, and Mahamod Ismail. 2013. Recent advances in wireless indoor localization techniques and system. Journal of Computer Networks and Communications 12.S. A. Fayaz. 2013. Location service for wireless network using improved RSS-based cellular localisation. International Journal of Electronics 1--16.C. Feng, W. Au, S. Valaee, and Z. Tan. 2010. Compressive sensing based positioning using RSS of WLAN access points. In 2010 Proceedings of IEEE INFOCOM, 1--9.Ruijun Fu, Yunxing Ye, and K. Pahlavan. 2012. Heterogeneous cooperative localization for social networks with mobile devices. In IEEE 23rd International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC’12).T. Gallagher, B. Li, A. Kealy, and A. Dempster. 2009. Trials of commercial Wi-Fi positioning systems for indoor and urban canyons. In IGNSS 2009 Symposium on GPS/GNSS.T. Gallagher, E. Wise, B. Li, A. Dempster, C. Rizos, and E. Ramsey-Stewart. 2012. Indoor positioning system based on sensor fusion for the blind and visually impaired. In 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN’12), 1--9.Miguel Garcia, Diana Bri, Jesus Tomas, and Jaime Lloret. 2013. A cooperative decision making algorithm for wireless location systems using interlinking data. In 10th International Conference on Cooperative Design, Visualization and Engineering (CDVE’13). Mallorca, Spain.Miguel Garcia, Fernando Boronat, Jesus Tomás, and Jaime Lloret. 2009. The development of two systems for indoor wireless sensors self-location. Ad Hoc & Sensor Wireless Networks 8, 3--4, 235--258.A. Günther and C. Hoene. 2005. Measuring round trip times to determine the distance between wlan nodes. In Proceedings of Networking 2005. Springer, 768--779.R. Hansen, R. Wind, C. Jensen, and B. Thomsen. 2009. Seamless indoor/outdoor positioning handover for location-based services in streamspin. In 10th International Conference on Mobile Data Management: Systems, Services and Middleware (MDM’09), 267--272.R. Harle. 2013. A survey of indoor inertial positioning systems for pedestrians. In IEEE Communications Surveys Tutorials 15, 3, 1281--1293.A. Hassan and S. Khairulmizam. 2009. Integration of global positioning system and inertial navigation system with different sampling rate using adaptive neuro fuzzy inference system. Science Journal 7, 98--106.J. Hightower and G. Borriello. 2001. Location systems for ubiquitous computing. Computer 34, 8, 57--66.C. Hoene and J. Willmann. 2008. Four-way TOA and software-based trilateration of IEEE 802.11 devices. In IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’08), 1--6.J. Huang, D. Millman, M. Quigley, D. Stavens, S. Thrun, and A. Aggarwal. 2011. Efficient, generalized indoor WiFi GRAPHSLAM. In 2011 IEEE International Conference on Robotics and Automation (ICRA’11), 1038--1043.L. Hui, Y. Lei, and W. Yuanfei. 2010. UWB, Multi-sensors and WiFi-mesh based precision positioning for urban rail traffic. In Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS’10), 1--8.Ihsan Alshahib Lami, S. Halgurd Maghdid, and Torben Kuseler. 2014. SILS: A smart indoors localization scheme based on on-the-go cooperative smartphones networks using onboard bluetooth, WiFi and GNSS. In Proceedings of the 27th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+’14). Tampa, FL.T. Iwase and R. Shibasaki. 2013. Infra-free indoor positioning using only smartphone sensors. In 2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN’13).S. Jin. 2012. Global Navigation Satellite Systems: Signal, Theory and Applications. In Tech. 438 pages.K. Kalliola. 2008. Bringing navigation indoors. The Way We Live Next. Nokia.J. Kim, J. Lee, and C. Park. 2008. A mitigation of line-of-sight by TDOA error modeling in wireless communication system. In International Conference on Control, Automation and Systems (ICCAS’08), 1601--1605.S. Koenig, M. Schmidt, and C. Hoene. 2011. Multipath mitigation for indoor localization based on IEEE 802.11 time-of-flight measurements. In 2011 IEEE International Symposium on World of Wireless, Mobile and Multimedia Networks (WoWMoM’11), 1--8.N. Kohtake, S. Morimoto, S. Kogure, and D. Manandhar. 2011. Indoor and outdoor seamless positioning using indoor messaging system and GPS. In International Conference on Indoor Positioning and Indoor Navigation (IPIN’11).A. LaMarca, Y. Chawathe, S. Consolvo, J. Hightower, I. Smith, J. Scott, et al. 2005. Place lab: Device positioning using radio beacons in the wild. Pervasive Computing 301--306.J. Lee, Z. Lin, P. Chin, and K. Yar. 2010. One way ranging time drift compensation for both synchronized and non-synchronized clocks. In 2010 International Conference on System Science and Engineering (ICSSE’10), 327--331.Jae-Eun Lee and Sanguk Lee. 2010. Indoor initial positioning using single clock pseudolite system. In 2010 International Conference on Information and Communication Technology Convergence (ICTC’10), 575--578.B. Li, A. G. Dempster, and C. Rizos. 2010. Positioning in environments where GPS fails. FIG Congress, Sydney, Australia, 1--18.D. Lim, S. Lee, and D. Cho. 2007. Design of an assisted GPS receiver and its performance analysis. In IEEE International Symposium on Circuits and Systems (ISCAS’0), 1742--1745.H. Liu, H. Darabi, P. Banerjee, and J. Liu. 2007. Survey of wireless indoor positioning techniques and systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 37, 6, 1067--1080.Kaikai Liu, Qiuyuan Huang, Wang Jiecong, Li Xiaolin, and D. O. Wu. 2013. Improving GPS service via social collaboration. In 2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS’13).X. Liu, S. Zhang, J. Quan, and X. Lin. 2010. The experimental analysis of outdoor positioning system based on fingerprint approach. In 2010 12th IEEE International Conference on Communication Technology (ICCT’13), 369--372.Jaime Lloret, Jesus Tomas, Alejandro Canovas, and Irene Bellver. 2011. A geopositioning system based on WiFi networks. In The 7th International Conference on Networking and Services (ICNS’11). Venice, Italy.Jaime Lloret, Jesus Tomás, Miguel Garcia, and Alejandro Cánovas. 2009. A hybrid stochastic approach for self-location of wireless sensors in indoor environments. Sensors 9, 5, 3695--3712.Diego Lopez-de-Ipina, Bernhard Klein, Christian Guggenmos, Jorge Perez, and Guillermo Gil. 2011. User-Aware semantic location models for service provision. International Symposium on Ubiquitous Computing and Ambient Intelligence, Riviera Maya, Mexico.Dimitrios Lymberopoulos, Jie Liu, Xue Yang, Romit Roy Choudhury, Vlado Handziski, and Souvik Sen. 2015. A realistic evaluation and comparison of indoor location technologies: Experiences and lessons learned. In Proceedings of the 14th International Conference on Information Processing in Sensor Networks. ACM, New York, NY.N. Mahiddin, N. Safie, E. Nadia, S. Safei, and E. Fadzli. 2012. Indoor position detection using WiFi and trilateration technique. The International Conference on Informatics and Applications (ICIA’12), 362--366.T. Manodham, L. Loyola, and T. Miki. 2008. A novel wireless positioning system for seamless internet connectivity based on the WLAN infrastructure. Wireless Personal Communications 44, 3, 295--309.Alex Mariakakis, Souvik Sen, Jeongkeun Lee, and Kyu-Han Kim. 2014. Single access point based indoor localization. In Proceedings of ACM MobiSys.R. Mautz. 2009. The challenges of indoor environments and specification on some alternative positioning systems. In 6th Workshop on Positioning, Navigation and Communication (WPNC’09), 29--36.M. Mock, R. Frings, E. Nett, and S. Trikaliotis. 2000. Clock synchronization for wireless local area networks. 12th Euromicro Conference on Real-Time Systems (Euromicro RTS’00), 183--189.E. Mok. 2010. Using outdoor public WiFi and GPS integrated method for position updating of knowledge-based logistics system in dense high rise urban environments. 8th International Conference on Supply Chain Management and Information Systems (SCMIS’10), 1--4.D. Niculescu and B. Nath. 2004. VOR base stations for indoor 802. 11 positioning. In Proceedings of the 10th Annual International Conference on Mobile Computing and Networking 26, 58--69.T. Oshin, S. Poslad, and A. Ma. 2012. Improving the energy-efficiency of GPS based location sensing smartphone applications. In IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom’12), 1698--1705.R. Padilla. 2013. Apple retail stores to integrate iBeacon systems to assist with sales and services. Retrieved January 19, 2016 from http://www.macrumors.com/2013/11/16/apple-retail-stores-to-integrate-ibeacon-systems-to-assist-with-sales-and-services/.D. Park and J. Park. 2011. An enhanced ranging scheme using WiFi RSSI measurements for ubiquitous location. In 1st ACIS/JNU International Conference on Computers, Networks, Systems and Industrial Engineering (CNSI’11), 296--301.J. Partyka. 2012. A look at small indoor location competitors. GPS world. Available at: http://gpsworld.com/wirelesslook-small-indoor-location-competitors-13229/ {Last access January 31, 2016}.L. Pei, R. Chen, J. Liu, Z. Liu, H. Kuusniemi, Y. Chen, et al. 2011. Sensor assisted 3D personal navigation on a smart phone in GPS degraded environments. In 19th International Conference on Geoinformatics, 1--6.R. G. Priyanka Shah. 2012, May 01. Location based reminder using GPS for mobile (Android). ARPN Journal of Science and Technology 2, 4, 377--380.C. Rizos, G. Roberts, J. Barnes, and N. Gambale. 2010. Locata: A new high accuracy indoor positioning system. In Proceedings of the International Conference on Indoor Positioning and Indoor Navigation, Zurich, Switzerland, 15--17.R. Rowe, P. Duffett-Smith, M. Jarvis, and N. Graube. 2008. Enhanced GPS: The tight integration of received cellular timing signals and GNSS receivers for ubiquitous positioning. In IEEE/ION Position, Location and Navigation Symposium, 838--845.A. Roxin, J. Gaber, M. Wack, and A. Nait-Sidi-Moh. 2007. Survey of wireless geolocation techniques. In IEEE Globecom Workshops, 1--9.J. Ryoo, H. Kim, and S. Das. 2012. Geo-fencing: Geographical-fencing based energy-aware proactive framework for mobile devices. In IEEE 20th International Workshop on Quality of Service (IWQoS’12), 1--9.Souvik Sen, Jeongkeun Lee, Kyu-Han Kim, and Paul Congdon. 2013. Avoiding multipath to revive inbuilding WiFi localization. In Proceeding of the 11th Annual International Conference on Mobile Systems, Applications, and Services. ACM, New York, NY.Sensewhere LTD. 2011. Geo-fence technology and applications. Indoor Location Technology Leaders. Available at: http://www.sensewhere.com/images/geowhereDatasheet_compressed.pdf {Last access January 31, 2016}.I. Shafer and M. Chang L. 2010. Movement detection for power-efficient smartphone WLAN localization. In Proceedings of the 13th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems, ACM, New York, NY, 81--90.Aaron Strout and Mike Schneider. 2011. Location Based Marketing For Dummies. John Wiley & Sons, Hoboken, NJ.Fazli Subhan, Halabi Hasbullah, Azat Rozyyev, and Sheikh Tahir Bakhsh. 2011. Indoor positioning in Bluetooth networks using fingerprinting and lateration approach. In 2011 International Conference on Information Science and Applications (ICISA).Daisuke Taniuchi, Xiaopeng Liu, Daisuke Nakai, and Takuya Maekawa. 2015. Spring model based collaborative indoor position estimation with neighbor mobile devices. IEEE Journal of Selected Topics in Signal Processing 9, 2, 268--277.CSRICIII Working Group 3. 2013. E9-1-1 Location Accuracy: Indoor Location Test Bed Report. San Jose CA: The Communications Security, Reliability and Interoperability Council III. https://transition.fcc.gov/bureaus/pshs/advisory/csric3/CSRIC_III_WG3_Report_March_%202013_ILTestBedReport.pdf {Last access January 31, 2016}.Agoston Torok, Akos Nagy, Laszlo Kovats, and Peter Pach. 2014. DREAR-towards infrastructure-free indoor localization via dead-reckoning enhanced with activity recognition. In 8th International Conference on. Next Generation Mobile Apps, Services and Technologies (NGMAST’14).D. McHoul. 2008. U-TDOA Enabling New Location-based Safety and Security Solutions. TruePosition-White Paper, USA, 1--10.A. Waadt, G. Bruck, and P. Jung. 2009. An overview of positioning systems and technologies. In 2nd International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL’09), 1--5.M. Weyn and F. Schrooyen. 2008. A Wi-Fi Assisted GPS Positioning Concept. ECUMICT, Ghent, Belgium.S. Wibowo, M. Klepal, and D. Pesch. 2009. Time of flight ranging using off-the-self IEEE802. 11 WiFi tags. In Proceedings of the International Conference on Positioning and Context-Awareness (PoCA’09).O. Woodman and R. Harle. 2008. Pedestrian localisation for indoor environments. In Proceedings of the 10th International Conference on Ubiquitous Computing, 114--123.Yinfeng Wu, Ligong Li, Yongji Ren, Kefu Yi, and Ning Yu. 2014. A RSSI localization algorithm and implementation for indoor wireless sensor networks. Adhoc & Sensor Wireless Networks 22, 2.Zhuoling Xiao, Hongkai Wen, Andrew Markham, and Niki Trigoni. 2015. Robust pedestrian dead reckoning (R-PDR) for arbitrary mobile device placement. In International Conference on Indoor Positioning and Indoor Navigation. IEEE.J. Xiong and K. Jamieson. 2011. ArrayTrack: A fine-grained indoor location system. RN 11, 19.Yi Sun, Yubin Zhao, and J. Schiller. 2014. An autonomic indoor positioning application based on smartphone. In IEEE Wireless Communications and Networking Conference (WCNC’14).M. Youssef, A. Youssef, C. Rieger, U. Shankar, and A. Agrawala. 2006. Pinpoint: An asynchronous time-based location determination system. In Proceedings of the 4th International Conference on Mobile Systems, Applications and Services,165--176.Haejung Yun, Dongho Han, and C. Choong Lee. 2013. Understanding the use of location-based service applications: Do privacy concerns matter? Journal of Electronic Commerce Research 14, 3, 215.P. Zandbergen. 2009. Accuracy of iPhone locations: A comparison of assisted GPS, WiFi and cellular positioning. Transactions in GIS 13, s1, 5--25.Y. Zhao, M. Li, and F. Shi. 2010. Indoor radio propagation model based on dominant path. International Journal of Communications, Network and System Sciences 3, 3, 330--337.S. Zirari, P. Canalda, and F. Spies. 2010. WiFi GPS based combined positioning algorithm. In IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS’10), 684--688

    Security and Privacy for IoT Ecosystems

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    Smart devices have become an integral part of our everyday life. In contrast to smartphones and laptops, Internet of Things (IoT) devices are typically managed by the vendor. They allow little or no user-driven customization. Users need to use and trust IoT devices as they are, including the ecosystems involved in the processing and sharing of personal data. Ensuring that an IoT device does not leak private data is imperative. This thesis analyzes security practices in popular IoT ecosystems across several price segments. Our results show a gap between real-world implementations and state-of-the-art security measures. The process of responsible disclosure with the vendors revealed further practical challenges. Do they want to support backward compatibility with the same app and infrastructure over multiple IoT device generations? To which extent can they trust their supply chains in rolling out keys? Mature vendors have a budget for security and are aware of its demands. Despite this goodwill, developers sometimes fail at securing the concrete implementations in those complex ecosystems. Our analysis of real-world products reveals the actual efforts made by vendors to secure their products. Our responsible disclosure processes and publications of design recommendations not only increase security in existing products but also help connected ecosystem manufacturers to develop secure products. Moreover, we enable users to take control of their connected devices with firmware binary patching. If a vendor decides to no longer offer cloud services, bootstrapping a vendor-independent ecosystem is the only way to revive bricked devices. Binary patching is not only useful in the IoT context but also opens up these devices as research platforms. We are the first to publish tools for Bluetooth firmware and lower-layer analysis and uncover a security issue in Broadcom chips affecting hundreds of millions of devices manufactured by Apple, Samsung, Google, and more. Although we informed Broadcom and customers of their technologies of the weaknesses identified, some of these devices no longer receive official updates. For these, our binary patching framework is capable of building vendor-independent patches and retrofit security. Connected device vendors depend on standards; they rarely implement lower-layer communication schemes from scratch. Standards enable communication between devices of different vendors, which is crucial in many IoT setups. Secure standards help making products secure by design and, thus, need to be analyzed as early as possible. One possibility to integrate security into a lower-layer standard is Physical-Layer Security (PLS). PLS establishes security on the Physical Layer (PHY) of wireless transmissions. With new wireless technologies emerging, physical properties change. We analyze how suitable PLS techniques are in the domain of mmWave and Visible Light Communication (VLC). Despite VLC being commonly believed to be very secure due to its limited range, we show that using VLC instead for PLS is less secure than using it with Radio Frequency (RF) communication. The work in this thesis is applied to mature products as well as upcoming standards. We consider security for the whole product life cycle to make connected devices and IoT ecosystems more secure in the long term

    ACUTA Journal of Telecommunications in Higher Education

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    In This Issue The Future of the University Telephone System Two Approaches to Communications in the Desert Dual-Mode Smartphones Are Shaping the Future for VolP ADVERTORIAL: The Future of the Managed Emergency Communications System Penn State\u27s Voice Services: Roadmap to the Clouds Where Are We Now...Where Are We Going? Preparing for the Future as an ICT Professional Videoconferencing Goes Mobile President\u27s Message From the Executive Director Q&A with the CI

    UTILIZING AUTOMATIC IDENTIFICATION TRACKING SYSTEMS TO COMPILE OPERATIONAL FIELD AND STRUCTURE DATA

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    The Maryland State Highway Administration (SHA) and its Office of Materials Technology (OMT) is responsible for ensuring the materials used on its roadway system are properly designed, produced, and built to the approved standards. Each technology subdivision is responsible for the quality assurance of the materials used in transportation facility construction. The management of these materials relies on a series of intensive human processes involving sample collection and delivery. As the materials travel throughout the OMT, associated material information is manually recorded into a localized network database and the Material Management System (MMS) separately. The current large amount of human involvement necessary in the material clearance process can be streamlined with the integration of automatic identification technology (AIT). This study utilizes past implementations of AIT into civil engineering and construction applications to provide the SHA with AIT system hardware recommendations, software development considerations, estimated investment costs, and return on investment
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