197,134 research outputs found
We Can Hear Your PIN Drop: An Acoustic Side-Channel Attack on ATM PIN Pads
No full textPersonal Identification Numbers (PINs) are the most common user authentication method for in-person banking transactions at ATMs. The US Federal Reserve reported that, in 2018, PINs secured 31.4 billion transactions in the US, with an overall worth of US$ 1.19 trillion. One well-known attack type involves the use of cameras to spy on the ATM PIN pad during PIN entry. Countermeasures include covering the PIN pad with a shield or with the other hand while typing. Although this protects PINs from visual attacks, acoustic emanations from the PIN pad itself open the door for another attack type. In this paper, we show the feasibility of an acoustic side-channel attack (called PinDrop ) to reconstruct PINs by profiling acoustic signatures of individual keys of a PIN pad. We demonstrate the practicality of PinDrop via two sets of data collection experiments involving two commercially available metal PIN pad models and 58 participants who entered a total of 5,800 5-digit PINs. We simulated two realistic attack scenarios: (1) a microphone placed near the ATM (0.3 m away) and (2) a real-time attacker (with a microphone) standing in the queue at a common courtesy distance of 2 m. In the former case, we show that PinDrop recovers 96% of 4-digit, and up to 94% of 5-digits, PINs. Whereas, at 2 m away, it recovers up to 57% of 4-digit, and up to 39% of 5-digit PINs in three attempts. We believe that these results are both significant and worrisome
Lo sguardo e il gioco. Linee per una educazione al consumo di televisione
No full textLo sguardo e il gioco. Linee per una educazione al consumo di television
Socialità, comunicazione, educazione. Per un'analisi del movimento mondiale della Media Education
No full textSocialità, comunicazione, educazione. Per un’analisi del movimento mondiale della Media Educatio
Toward the specificity of bare nanomaterial surfaces for protein corona formation
No full textAiming at creating smart nanomaterials for biomedical applications, nanotechnology aspires to develop a new generation of nanomaterials with the ability to recognize different biological components in a complex environment. It is common opinion that nanomaterials must be coated with organic or inorganic layers as a mandatory prerequisite for applications in biological systems. Thus, it is the nanomaterial surface coating that predominantly controls the nanomaterial fate in the biological environment. In the last decades, interdisciplinary studies involving not only life sciences, but all branches of scientific research, provided hints for obtaining uncoated inorganic materials able to interact with biological systems with high complexity and selectivity. Herein, the fragmentary literature on the interactions between bare abiotic materials and biological components is reviewed. Moreover, the most relevant examples of selective binding and the conceptualization of the general principles behind recognition mechanisms were provided. Nanoparticle features, such as crystalline facets, density and distribution of surface chemical groups, and surface roughness and topography were encompassed for deepening the comprehension of the general concept of recognition patterns
Socialità, comunicazione, educazione. Per un'analisi del movimento mondiale della Media Education
No full textSocialità, comunicazione, educazione. Per un’analisi del movimento mondiale della Media Educatio
Lo sguardo e il gioco. Linee per una educazione al consumo di televisione
No full textLo sguardo e il gioco. Linee per una educazione al consumo di television
Parole ingombranti. Quando la pubblicità si serve dei cartoon
No full textParole ingombranti. Quando la pubblicità si serve dei cartoo
Fake News Spreaders Profiling through Behavioural Analysis Notebook for PAN at CLEF 2020
No full textThe growth of social media and the people interconnection led to the digitalization of communication. Nowadays the most influential politicians or scientific communicators use the media to disseminate news or decisions. However, such communications media can be used maliciously to spread the so-called fake-news in order to polarise public opinion or to deny scientific theories. It is therefore important to develop intelligent and accurate techniques in order to identify the spreading of fake-news. In this paper, we describes the methodology regarding our participation in the PAN@CLEF Profiling Fake News Spreaders on Twitter competition. We propose a supervised Machine-Learning (ML) based framework to profile fake-news spreaders. Our method relies on the combination of Big Five personality and stylometric features. Finally, we evaluate our framework detection capabilities and performance with different ML models on a tweeter dataset in both English and Spanish languages
Parole ingombranti. Quando la pubblicità si serve dei cartoon
No full textParole ingombranti. Quando la pubblicità si serve dei cartoo
Skype & type: Keyboard eavesdropping in voice-over-IP
No full textVoice-over-IP (VoIP) software are among the most widely spread and pervasive software, counting millions of monthly users. However, we argue that people ignore the drawbacks of transmitting information along with their voice, such as keystroke sounds-as such sound can reveal what someone is typing on a keyboard. In this article, we present and assess a new keyboard acoustic eavesdropping attack that involves VoIP, called Skype & Type (S&T). Unlike previous attacks, S&T assumes a weak adversary model that is very practical in many real-world settings. Indeed, S&T is very feasible, as it does not require (i) the attacker to be physically close to the victim (either in person or with a recording device) and (ii) precise profiling of the victim's typing style and keyboard; moreover, it can work with a very small amount of leaked keystrokes. We observe that leakage of keystrokes during a VoIP call is likely, as people often "multi-task" during such calls. As expected, VoIP software acquires and faithfully transmits all sounds, including emanations of pressed keystrokes, which can include passwords and other sensitive information. We show that one very popular VoIP software (Skype) conveys enough audio information to reconstruct the victim's input-keystrokes typed on the remote keyboard. Our results demonstrate that, given some knowledge on the victim's typing style and keyboard model, the attacker attains top-5 accuracy of 91.7% in guessing a random key pressed by the victim. This work extends previous results on S&T, demonstrating that our attack is effective with many different recording devices (such as laptop microphones, headset microphones, and smartphones located in proximity of the target keyboard), diverse typing styles and speed, and is particularly threatening when the victim is typing in a known language
- …
