Mika Raento

Smartphones An Emerging Tool for Social Scientists

Recent developments in mobile technologies have produced a new kind of device: a programmable mobile phone, the smartphone. In this article, the authors argue that the technological and social characteristics of this device make it a useful tool in social sciences, particularly sociology, social psychology, urban studies, technology assessment, and media studies. The device is willingly carried by a large fraction of people in developed countries, integrates a number of technologies for automatic observation, can be programmed to interact with the user, and can communicate with remote researchers. This allows unobtrusive and cost-effective access to previously inaccessible sources of data on everyday social behavior, such as physical proximity of people, phone calls, and patterns of movement. The authors describe three studies in human behavior that have augmented existing methods with the smartphone, two of which the authors conducted themselves. Based on their experience, the authors critically evaluate the improvements and threats to validity and reliability of smartphone-augmented methods. These approaches are rapidly becoming feasible for the social scientist, since research software for smartphones have been published in open source, which lowers the technical and economic investment needed for their utilization in research.Recent developments in mobile technologies have produced a new kind of device: a programmable mobile phone, the smartphone. In this article, the authors argue that the technological and social char...

Adaptive on-device location recognition

Location-awareness is useful for mobile and pervasive computing. We present a novel adaptive framework for recognizing personally important locations in cellular networks, implementable on a mobile device and usable, e.g., in a presence service. In comparison, most previous work has used service infrastructure for location recognition and the few adaptive frameworks presented have used coordinate-based data. We construct a conceptual framework for the tasks of learning important locations and predicting the next location. We give algorithms for efficient approximation of the ideal concepts, and evaluate them experimentally with real data.

Evaluating Classifiers for Mobile-Masquerader Detection

As a result of the impersonation of a user of a mobile terminal, sensitive information kept locally or accessible over the network can be abused. The means of masquerader detection are therefore needed to detect the cases of impersonation. In this paper, the problem of mobile-masquerader detection is considered as a problem of classifying the user behaviour as originating from the legitimate user or someone else. Different behavioural characteristics are analysed by designated one-class classifiers whose classifications are combined. The paper focuses on selecting the classifiers for mobile-masquerader detection. The selection process is conducted in two phases. First, the classification accuracies of classifiers are empirically evaluated, and inaccurate classifiers are excluded. After that, the accuracies of different classifier combinations are explored, and the combination with the best classification accuracy is identified. The experimental results suggest that, in order to achieve better accuracy, the individual classifiers with both high classification accuracy and a small number of non-classifications need to be selected.

Estimating accuracy of mobile-masquerader detection using worst-case and best-case scenario

In order to resist an unauthorized use of the resources accessible through mobile terminals, masquerader detection means can be employed. In this paper, the problem of mobile-masquerader detection is approached as a classification problem, and the detection is performed by an ensemble of one-class classifiers. Each classifier compares a measure describing user behavior or environment with the profile accumulating the information about past behavior and environment. The accuracy of classification is empirically estimated by experimenting with a dataset describing the behavior and environment of two groups of mobile users, where the users within groups are affiliated with each other. It is assumed that users within a group have similarities in their behavior and environment and hence are more difficult to differentiate, as compared with distinguishing between the users of different groups. From the practical detection perspective, the former case corresponds to the “worst-case” scenario where the masquerader has a rich knowledge of the user behavior and environment and is able to mimic them, while the latter case corresponds to the “best-case” scenario, where the masquerader makes little or no attempt to mimic the behavior and environment of the user. The classification accuracies are also evaluated for different levels of false rejection errors. The obtained results indicate that, when smaller values of false rejection errors are required, ensembles of few best-performing classifiers are preferable, while a five-classifier ensemble achieves better accuracy when higher levels of false rejection errors are tolerated.

The Data Subject’s Right of Access and to be Informed in Finland: An Experimental Study

The EC Data Protection Directive 95/46/EC emphasises the role of transparency in fair and lawful processing of personal data. This study describes the results from sending forty requests for access to data held and information on processing to controllers of personal data in Finland. The results show that there are still difficulties in gaining access, in verifying the correctness of information provided and in the procedures controllers employ to provide information. These factors are discussed in light of Finnish and EC regulation, as well as information systems. Proposals are put forward as to how the difficulties might be addressed.

Mobile HCI 2004 Workshop on Location Systems Privacy and Control

People are increasingly carrying location-aware devices (i.e., able to determine their own location, and therefore that of the user, in physical space). A variety of such location systems are currently deployed or under development, from the global mobile telephony infrastructure [4] to schemes based on infrared badges, Bluetooth, GPS, or WiFi (802.11).