Flavio Bertini

Profile resolution across multilayer networks through smartphone camera fingerprint

In the last decade, various social platforms have been introduced on the web. Due to their specific orientation (friendship, professional connections, image sharing, etc.) users often join multiple networks. An important problem across these networks is the resolution of users profiles. That is, to identify if set of user profiles from different networks with different user ids or nicknames belong to the same user. The problem is more meaningful for resolving different profiles in digital forensic and criminal investigations. In this paper, we propose a method for profile resolution with the help of pictures being posted on different social platforms. We use the smartphone cameras which have become the source of instant image capturing and uploading process. In particular, we exploit the characteristic noise present in the images due to the manufacturing defects, to match user profiles across social platforms. To test our approach we select five different smartphones with two pairs of identical models, and three social platforms, namely Facebook, Google+ and WhatsApp. We evaluate our approach using real dataset of 1000 high-resolution pictures. The results indicate that even in the worst case our approach can provide profile matching upto 89.83%.

Content-preserving Text Watermarking through Unicode Homoglyph Substitution

Digital watermarking has become crucially important in authentication and copyright protection of the digital contents, since more and more data are daily generated and shared online through digital archives, blogs and social networks. Out of all, text watermarking is a more difficult task in comparison to other media watermarking. Text cannot be always converted into image, it accounts for a far smaller amount of data (eg. social network posts) and the changes in short texts would strongly affect the meaning or the overall visual form. In this paper we propose a text watermarking technique based on homoglyph characters substitution for latin symbols1. The proposed method is able to efficiently embed a password based watermark in short texts by strictly preserving the content. In particular, it uses alternative Unicode symbols to ensure visual indistinguishability and length preservation, namely content-preservation. To evaluate our method, we use a real dataset of 1.8 million New York articles. The results show the effectiveness of our approach providing an average length of 101 characters needed to embed a 64bit password based watermark.

A Cluster-based Approach of Smartphone Camera Fingerprint for User Profiles Resolution within Social Network

In the last decades, Social Networks (SNs) have deeply changed interactions and habits of the users that are also prone to create more than one profile on the same SN. On the flip side, fake profiles (i.e., impersonating profiles), have become a considerable problem in digital investigations. In this paper, we propose a method for user profiles resolution through a cluster-based approach of the smartphone fingerprints extracted from the images being posted on SNs. The proposed method is thus able to detect fake profiles. To evaluate our approach, we use a real dataset of 1,500 images from 10 different smartphone devices and Facebook and WhatsApp platforms. The results show that the average of sensitivity and specificity for user profiles resolution is about 98%.

Unraveling pedestrian mobility on a road network using ICTs data during great tourist events

Tourist flows in historical cities are continuously growing in a globalized world and adequate governance processes, politics and tools are necessary in order to reduce impacts on the urban livability and to guarantee the preservation of cultural heritage. The ICTs offer the possibility of collecting large amount of data that can point out and quantify some statistical and dynamic properties of human mobility emerging from the individual behavior and referring to a whole road network. In this paper we analyze a new dataset that has been collected by the Italian mobile phone company TIM, which contains the GPS positions of a relevant sample of mobile devices when they actively connected to the cell phone network. Our aim is to propose innovative tools allowing to study properties of pedestrian mobility on the whole road network. Venice is a paradigmatic example for the impact of tourist flows on the resident life quality and on the preservation of cultural heritage. The GPS data provide anonymized georeferenced information on the displacements of the devices. After a filtering procedure, we develop specific algorithms able to reconstruct the daily mobility paths on the whole Venice road network. The statistical analysis of the mobility paths suggests the existence of a travel time budget for the mobility and points out the role of the rest times in the empirical relation between the mobility time and the corresponding path length. We succeed to highlight two connected mobility subnetworks extracted from the whole road network, that are able to explain the majority of the observed mobility. Our approach shows the existence of characteristic mobility paths in Venice for the tourists and for the residents. Moreover the data analysis highlights the different mobility features of the considered case studies and it allows to detect the mobility paths associated to different points of interest. Finally we have disaggregated the Italian and foreigner categories to study their different mobility behaviors.

Text Authorship Verification through Watermarking

While a plethora of digital contents are daily generated and shared online, authorship verification has become an imperative task. In comparison to other media watermarking techniques, text watermarking is a more challenging task. The changes in text would strongly affect the visual form and the meaning, text might be very short (eg. social media posts) and it cannot be always converted into image. In this paper we propose a novel text watermarking method for authorship verification based on Unicode confusable substitution. The proposed method substitutes latin symbols with homoglyph characters. It ensures length preservation and visual indistinguishability among the original text and the watermarked one. We successfully evaluate our approach using a real dataset of 1.8 million of New York Times articles. The results show the effectiveness of our method providing an average length of 101 characters needed to embed a 64bit password based watermark.

Smartphone Verification and User Profiles Linking Across Social Networks by Camera Fingerprinting

In recent years, the spread of smartphones has attributed to changes in the user behaviour with respect to multimedia content sharing on online social networks (SNs). One noticeable behaviour is taking pictures using smartphone cameras and sharing them with friends through online social platforms. On the downside, this has contributed to the growth of the cyber crime through SNs. In this paper, we present a method to extract the characteristic fingerprint of the source camera from images being posted on SNs. We use this technique for two investigation activities (i) smartphone verification: correctly verifying if a given picture has been taken by a given smartphone and (ii) profile linking: matching user profiles belonging to different SNs. The method is robust enough to verify the smartphones in spite of the fact that the images get downgraded during the uploading/downloading process. Also, it is capable enough to compare different images belonging to different SNs without using the original images. We evaluate our process on real dataset using three different social networks and five different smartphones. The results, show smartphone verification and profile linking can provide 96.48 % and 99.49 % respectively, on an average of the three social networks, which shows the effectiveness of our approach.