The Places of Our Lives: Visiting Patterns and Automatic Labeling from Longitudinal Smartphone Data ABSTRACT: The location tracking functionality of modern mobile devices provides unprecedented opportunity to the understanding of individual mobility in daily life. Instead of studying raw geographic coordinates, we are interested in understanding human mobility patterns based on sequences of place visits which encode, at a coarse resolution, most daily activities. This paper presents a study on place characterization in people’s everyday life based on data recorded continuously by smartphones. First, we study human mobility from sequences of place visits, including visiting patterns on different place categories. Second, we address the problem of automatic place labeling from smartphone data without using any geo-location information. Our study on a large-scale data collected from 114 smartphone users over 18 months confirm many intuitions, and also reveals findings regarding both regularly and novelty trends in visiting patterns. Considering the problem of place labeling with 10 place categories, we show that frequently visited places can be recognized reliably (over 80 percent) while it is much more challenging to recognize infrequent places.

1. Security Threats to Mobile Multimedia Applications:
Camera-Based Attacks on Mobile Phones
ABSTRACT:
Today’s mobile smartphones are very power ful, and many smartphone
applications use wireless multimedia communications. Mobile phone security has
become an important aspect of security issues in wireless multimedia
communications. As the most popular mobile operating system, Android security
has been extensively studied by researchers. However, few works have studied
mobile phone multimedia security. In this article, we focus on security issues
related to mobile phone cameras. Specifically, we discover several new attacks that
are based on the use of phone cameras. We implement the attacks on real phones,
and demonstrate the feasibility and effectiveness of the attacks. Furthermore, we
propose a lightweight defense scheme that can effectively detect these attacks.
EXISTING SYSTEM:
Several video-based attacks targeted at keystrokes have been proposed. The attacks
can obtain user input on touch screen smartphones. Maggi et al. [4] implement an

2. automatic shoulder surfing attack against modern touch-enabled smartphones. The
attacker deploys a video camera that can record the target screen while the victim
is entering text. Then user input can be reconstructed solely based on the keystroke
feedback displayed on the screen. However, this attack requires an additional
camera device, and issues like how to place the camera near the victim without
catching an alert must be considered carefully.
DISADVANTAGES OF EXISTING SYSTEM:
Moreover, it works only when visual feedback such as magnified keys are
available.
PROPOSED SYSTEM:
In this article, we first conduct a survey on the threats and benefits of spy cameras.
Then we present the basic attack model and two camera-based attacks: the remote-controlled
real-time monitoring attack and the passcode inference attack. We run
these attacks along with popular antivirus software to test their stealthiness, and
conduct experiments to evaluate both types of attacks. The results demonstrate the
feasibility and effectiveness of these attacks. Finally, we propose a lightweight

3. defense scheme.In this work, we are able to hide the whole camera app in Android.
Moreover, we implement advanced forms of attacks such as remote-controlled and
real-time monitoring attacks. We also utilize computer vision techniques to analyze
recorded videos and infer passcodes from users’ eye movements.
ADVANTAGES OF PROPOSED SYSTEM:
The main challenge is to make the attacks run stealthily and silently so that they do
not cause a user alert.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
 System : Pentium IV 2.4 GHz.
 Hard Disk : 40 GB.
 Floppy Drive : 1.44 Mb.
 Monitor : 15 VGA Colour.
 Mouse : Logitech.
 Ram : 512 Mb.
 MOBILE : ANDROID

4. SOFTWARE REQUIREMENTS:
 Operating system : Windows XP/7.
 Coding Language : Java 1.7
 Tool Kit : Android 2.3 ABOVE
 IDE : Eclipse
REFERENCE:
Longfei Wu and Xiaojiang Du, Temple University Xinwen Fu, University of
Massachusetts Lowell, “Security Threats to Mobile Multimedia Applications:
Camera-Based Attacks on Mobile Phones,” IEEE Communications Magazine,
March 2014