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Travel Offline Virtual Support Through Locational Reminder and Suggestions Using Data Analytics
Volume 3, Issue 1, January– 2018 International Journal of Innovative Science and Research Technology ISSN No:-2456 –2165 Travel Offline Virtual Support Through Locational Reminder and Suggestions using Data Analytics Shaikh Farhan Firoz ahmed Khan Mahir Ali Department of Computer Engineering, Department of Computer Engineering, Anjuman-I-Islam’s Kalsekar Technical Campus, Anjuman-I_Islam’s Kalsekar Technical Campus, New Panvel, India New Panvel, India Shaikh Arfat Izharul haq Kalpana Bodke Department of Computer Engineering, Department of Computer Engineering, Anjuman-I-Islam’s Kalsekar Technical Campus, Anjuman-I-Islam’s Kalsekar Technical Campus, New Panvel, India New Panvel, India Abstract:-The combination of smart phone and web I. INTRODUCTION service is that the trend of the longer term data development and software applications. As the tourists are While travelling tourists expect to get personalized access to provided with printed guide booklet to find out interesting tourism information at anytime, from anywhere through any places during the visit. As the tourists are unaware of up to internet enabled device. Mobile applications can provide the date information and proper navigation, tourists are not user with such a general access. With the evolution of able to visit all the destinations. Mobile phones were technology, internet enabled devices have made it effortless to normally used for communication purpose. Travel offline access information anywhere, anytime. virtual support through vocational reminder and suggestions using data analytics. The web and Android The task is to replace the hard copy tour guides books with application developed to show how the architecture works mobile applications. We will also provide E-books to our and has a lot of important features for tourists such as customers. -
Measuring the Insecurity of Mobile Deep Links of Android
Measuring the Insecurity of Mobile Deep Links of Android Fang Liu, Chun Wang, Andres Pico, Danfeng Yao, and Gang Wang, Virginia Tech https://www.usenix.org/conference/usenixsecurity17/technical-sessions/presentation/liu This paper is included in the Proceedings of the 26th USENIX Security Symposium August 16–18, 2017 • Vancouver, BC, Canada ISBN 978-1-931971-40-9 Open access to the Proceedings of the 26th USENIX Security Symposium is sponsored by USENIX Measuring the Insecurity of Mobile Deep Links of Android Fang Liu, Chun Wang, Andres Pico, Danfeng Yao, Gang Wang Department of Computer Science, Virginia Tech ffbeyond, wchun, andres, danfeng, [email protected] Abstract launch apps from websites with preloaded context, which becomes instrumental to many key user experiences. For Mobile deep links are URIs that point to specific loca- instance, from a restaurant’s home page, users can tap a tions within apps, which are instrumental to web-to-app hyperlink to launch the phone app and call the restaurant, communications. Existing “scheme URLs” are known to or launch Google Maps for navigation. Recently, users have hijacking vulnerabilities where one app can freely can even search in-app content with a web-based search register another app’s schemes to hijack the communi- engine (e.g., Google) and directly launch the target app cation. Recently, Android introduced two new meth- by clicking the search result [5]. ods “App links” and “Intent URLs” which were designed with security features, to replace scheme URLs. While The key enabler of web-to-mobile communication is the new mechanisms are secure in theory, little is known mobile deep links. -
Harvesting Developer Credentials in Android Apps
Harvesting Developer Credentials in Android Apps Yajin Zhouy, Lei Wuy, Zhi Wangz, Xuxian Jiang? yNorth Carolina State University zFlorida State University ?Qihoo 360 {yajin_zhou, lwu4}@ncsu.edu, [email protected], [email protected] ABSTRACT 1 .method public static SendMailInBackground 2 new-instance v3, Lcom/pompeiicity/funpic/Email; Developers often integrate third-party services into their apps. To 3 const-string v7, "fitt*****@126.com" access a service, an app must authenticate itself to the service with 4 const-string v8, "jed****" a credential. However, credentials in apps are often not properly or 5 invoke-direct {v3,v7,v8},Lcom/pompeiicity/funpic/Email;-> 6 <init>(Ljava/lang/String;Ljava/lang/String;)V adequately protected, and might be easily extracted by attackers. A 7 ... leaked credential could pose serious privacy and security threats to 8 .end method both the app developer and app users. In this paper, we propose CredMiner to systematically study the Figure 1: An Example of Embedded Plaintext Credential prevalence of unsafe developer credential uses in Android apps. CredMiner can programmatically identify and recover (obfuscated) S3 (Simple Storage Service) is a popular cloud storage solution for developer credentials unsafely embedded in Android apps. Specif- developers to store user data in the cloud without maintaining their ically, it leverages data flow analysis to identify the raw form of the own infrastructures. In addition, free email services are frequently embedded credential, and selectively executes the part of the pro- used to send crash reports or customer feedback to app developers. gram that builds the credential to recover it. We applied CredMiner To facilitate the integration, these services conveniently provide de- to 36;561 apps collected from various Android markets to study the velopers with free SDKs [5] and ready-to-use libraries [10], as well use of free email services and Amazon AWS. -
A Tourist Guide with a Recommender System and Social
Available online at www.sciencedirect.com ScienceDirect Procedia Technology 17 ( 2014 ) 407 – 414 Conference on Electronics, Telecommunications and Computers – CETC 2013 GuideMe-ATourist Guide with a Recommender System and Social Interaction Artem Umanetsa, Artur Ferreiraa,1, Nuno Leitea aInstituto Superior de Engenharia de Lisboa, Rua Conselheiro Em´ıdio Navarro, n.° 1, 1959-007 Lisboa, Portugal Abstract In the past few years, with the proliferation of mobile devices people are experiencing frequent communication and information exchange. For instance, in the context of tourist visits, it is often the case that each person carries out a smartphone, to get information about touristic places. When one visits some location, a tourist guide application will recommend useful information, according to its current location, preferences, and past visits. Afterwards, the tourist guide allows for the user to provide feedback about each visit. In this paper, we address the development and the key features of a tourist guide, named GuideMe. Its mobile and Web applications provide consultation, publication, and recommendation of touristic locations. Each user may consult places of touristic interest, receive suggestions of previously unseen touristic places according to other users recommendations, and to perform its own recommendations. The recommendations are carried out using the well-known Mahout library. As compared to previous recommender based tourist guides, the key novelties of GuideMe are its integration with social networks and the unique set of options offered in the application. The usability and load tests performed to evaluate the service, including its recommendation engine, have shown both the adequacy of the designed interfaces as well as good response times. -
July 2012 Investment Summary
Marketing, Media, Technology, and Service Industries M&A & July 2012 Investment Summary Expertise. Commitment. Results. TABLE OF CONTENTS Overview of Monthly M&A and Investment Activity 3 Monthly M&A and Investment Activity by Industry Segment 7 Additional Monthly M&A and Investment Activity Data 24 About Petsky Prunier 35 M&A & INVESTMENT SUMMARY JULY 2012 2 MARKETING, MEDIA, TECHNOLOGY, AND SERVICE INDUSTRIES Transaction Distribution • A to ta l of 255 deal s worth approximat el y $16 billion were announced in Jul y 2012 • Digital Media/Commerce was the most active segment with 83 transactions • Software & Information was the highest value segment worth approximately $7.2 billion • Strategic buyers announced 92 deals for approximately $11.4 billion (36% of total volume) • VC/Growth Capital investors announced 152 deals for approximately $1.6 billion • Buyout investors announced 11 deals for approximately $2.9 billion JULY 2012 BUYER/INVESTOR BREAKDOWN Transactions Est. Value Strategic Buyout Venture/Growth Capital # % $MM % # $MM # $MM # $MM Digital Media/Commerce 83 33% 1,527.5 10% 26 774.6 0 0.0 57 752.9 Marketing Technology 77 30% 973.6 6% 25 603.0 1 8.0 51 362.6 Software & Information 42 16% 7,216.0 45% 10 4,219.9 5 2,733.1 27 263.0 Agency/Consulting 18 7% 5,134.1 32% 17 5,117.1 0 0.0 1 17.0 Digital Advertising 15 6% 262.1 2% 3 45.0 1 98.0 11 119.1 Marketing Services 11 4% 171.1 1% 4 80.0 3 65.0 4 26.1 Out-of-Home & Specialty Media 9 4% 727.4 5% 7 702.4 1 10.0 1 15.0 Total 255 100% 16,011.8 100% 92 11,542.0 11 2,914.1 152 1,555.6 Marketing, Media, Technology, and Service Industries M&A and Investment Volume - Last 13 Months 27.0 $25.1 $23.3 24.0 21.0 $10.3 18.0 HPQ/ $16.0 AU $14.6 15.0 $13.4 $11.5 12.0 $11.2 $11.0 $10.8 $10.4 $8.8 $9.9 9.0 e ($ in in billions) ($ e uu 606.0 $4.