International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
SECRET LOCK – ANTI THEFT: INTEGRATION OF APP LOCKER & DETECTION OF THEFT USING USER PATTERN Kavitha.G1, KongaraDevipriya2, SivaSankari.S3, Deepa.J4 1Student,
Department of Computer Science, Panimalar Institute of Technology, Chennai, Tamil Nadu Student, Department of Computer Science, Panimalar Institute of Technology, Chennai, Tamil Nadu 3 Student, Department of Computer Science, Panimalar Institute of Technology, Chennai, Tamil Nadu 4Assistant Professor, Department of Computer Science, Panimalar Institute of Technology, Chennai, Tamil Nadu 2
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Abstract - This paper presents the various methods to
dependableness by asking participants to answer their own questions. Our experimental results affirm that the private queries associated with motion sensors, calendar, app instalment, and a part of legacy app usage history (e.g., phone calls) have the most effective memorability for users as well as the highest strength to attacks. This paper proposes a new approach to theft detection with the use of user patterns with a Global Positioning System (GPS) along with Short Message Service (SMS) properties which helps in tracking the snatched mobile. The method used is the SVM (Support Vector Machine) for User Identification property.
secure or lock the mobile using user authentication. User will add multiple apps into our application for the secured access. At the time of registration, our application can frame a group of normal queries along with the user runtime verification as per the planned system. If the mobile is robbed, there's only a pair of choices, either to alter the SIM card or to hold identical SIM card and check out to use the apps. If SIM card is modified then naturally GPS, Voice recorder & Camera are initiated, so Location and Audio uplink are sent as SMS to the backup number of the user, and photograph is mailed. If he tries to use the private apps then system can question the user with five random queries (three from traditional queries and a pair of from user runtime pattern). If not licensed then camera, GPS & Voice recorder is initiated and sent to the first user to track.
2. BACKGROUND AND RELATED WORK Cognitive passwords are based on personal facts, interests and opinions that are probably to be simply recalled by a user and suggests their use as a method to overcome the dilemma of passwords that are either difficult to remember or that can easily be guessed. Passwords are selected by users, giving them a higher degree of recall than traditional system generated or user-selected passwords. User authentication through cognitive passwords is an extension of traditional password usage. It suggests the use of fact and opinion-based cognitive data, that is known only to the user, as an authentication mechanism [1]. Recall and guessing rates for conventional, cognitive, and word association passwords were compared using 86 Massey University undergraduates. Respondents completed a questionnaire covering all three parole types, returning two weeks later for a recall test. Each respondent also nominated a “significant other” parent, partner, etc. who tried to predict the respondent’s answers. On average, cognitive items produced the highest recall rates (80%) but the guessing rate was also high (39.5%). Word associations produced low predicting rates (7%) but response words were poorly recalled (39%) Nevertheless, both cognitive items and word associations showed sufficient promise as password techniques to warrant further investigation [3]. They study was a partial replication and extension of earlier research [7,8] on two such techniques, using cognitive items and word associations. The cognitive items were similar to those used by Zviran and Haga [1].
Key Words: Authentication, SIM card, GPS, Location Tracing, Audio uplink, SMS, Runtime pattern, Track
1. INTRODUCTION Many net applications give secondary authentication strategies, i.e., secret queries (or parole recovery questions), to reset the account parole once a user’s login fails. However, the answers to several such secret queries will be simply guessed by a colleague or exposed to a trespasser that has access to public on-line tools (e.g., on-line social networks); furthermore, a user could forget her/his answers long when making the private queries. Today’s prevalence of smartphones has granted us new opportunities to watch and perceive however the private knowledge collected by smartphone sensors and apps will ease to produce personalized secret queries without violating the users’ privacy concerns. This paper present a Secret-Question based Authentication system, known as “Secret-QA”, that makes a collection of secret queries on basic of people’s smartphone usage. We expand a model on Android smartphones, and evaluate the safety of the private queries by asking the acquaintance/intruder who participates in our user study to guess the answers with and without the support of on-line tools; in the meantime, we observe the queries’
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