Biblio
The development in the web technologies given growth to the new application that will make the voting process very easy and proficient. The E-voting helps in providing convenient, capture and count the votes in an election. This project provides the description about e-voting using an Android platform. The proposed e-voting system helps the user to cast the vote without visiting the polling booth. The application provides authentication measures in order to avoid fraud voters using the OTP. Once the voting process is finished the results will be available within a fraction of seconds. All the casted vote count is encrypted using AES256 algorithm and stored in the database in order to avoid any outbreaks and revelation of results by third person other than the administrator.
The growing use of smart phones has also given opportunity to the intruders to create malicious apps thereby the security and privacy concerns of a novice user has also grown. This research focuses on the privacy concerns of a user who unknowingly installs a malicious apps created by the programmer. In this paper we created an attack scenario and created an app capable of compromising the privacy of the users. After accepting all the permissions by the user while installing the app, the app allows us to track the live location of the Android device and continuously sends the GPS coordinates to the server. This spying app is also capable of sending the call log details of the user. This paper evaluates two leading smart phone operating systems- Android and IOS to find out the flexibility provided by the two operating systems to their programmers to create the malicious apps.
Two-factor authentication (2FA) popularly works by verifying something the user knows (a password) and something she possesses (a token, popularly instantiated with a smart phone). Conventional 2FA systems require extra interaction like typing a verification code, which is not very user-friendly. For improved user experience, recent work aims at zero-effort 2FA, in which a smart phone placed close to a computer (where the user enters her username/password into a browser to log into a server) automatically assists with the authentication. To prove her possession of the smart phone, the user needs to prove the phone is on the login spot, which reduces zero-effort 2FA to co-presence detection. In this paper, we propose SoundAuth, a secure zero-effort 2FA mechanism based on (two kinds of) ambient audio signals. SoundAuth looks for signs of proximity by having the browser and the smart phone compare both their surrounding sounds and certain unpredictable near-ultrasounds; if significant distinguishability is found, SoundAuth rejects the login request. For the ambient signals comparison, we regard it as a classification problem and employ a machine learning technique to analyze the audio signals. Experiments with real login attempts show that SoundAuth not only is comparable to existent schemes concerning utility, but also outperforms them in terms of resilience to attacks. SoundAuth can be easily deployed as it is readily supported by most smart phones and major browsers.
We propose $μ$Leech, a new embedded trusted platform module for next generation power scavenging devices. Such power scavenging devices are already widely deployed. For instance, the Square point-of-sale reader uses the microphone/speaker interface of a smartphone for communications and as power supply. While such devices are used as trusted devices in security critical applications in the wild, they have not been properly evaluated yet. $μ$Leech can securely store keys and provide cryptographic services to any connected smart phone. Our design also facilitates physical security analysis by providing interfaces to facilitate acquisition of power traces and clock manipulation attacks. Thus $μ$Leech empowers security researchers to analyze leakage in next generation embedded and IoT devices and to evaluate countermeasures before deployment.
In this paper, we consider side-channel mechanisms, specifically using smart device ambient light sensors, to capture information about user computing activity. We distinguish keyboard keystrokes using only the ambient light sensor readings from a smart watch worn on the user's non-dominant hand. Additionally, we investigate the feasibility of capturing screen emanations for determining user browser usage patterns. The experimental results expose privacy and security risks, as well as the potential for new mobile user interfaces and applications.
Mobile platform security solution has become especially important for mobile computing paradigms, due to the fact that increasing amounts of private and sensitive information are being stored on the smartphones' on-device memory or MicroSD/SD cards. This paper aims to consider a comparative approach to the security aspects of the current smartphone systems, including: iOS, Android, BlackBerry (QNX), and Windows Phone.