Abstract
Passwords have dominated the world of authentication. Their widespread use has made them a prized target for attackers. Various schemes have been employed to strengthen password security to resist such attacks. Numerous websites and applications use password meters to help users create a stronger password. The objective of having a password meter is to provide visual feedback to users on their choice of a password by labeling it as weak, medium, or strong, for example. In this paper, we incorporated social influence, which is the effect others have on an individual's attitude and behavior. This social influence, commonly known as peer feedback, was incorporated in the design of a peer feedback password meter. When participants were given explicit instructions to create a unique password, those that were provided with the peer feedback meter created stronger passwords when compared to those that had the traditional meter.
Highlights
According to some estimates, online users are expected to reach 4 billion by 2019, generating around 44 zettabytes of data by 2020 [1]
Recent data breaches suffered by Yahoo!, Dropbox, and LinkedIn had exposed up to 732 million user details [2]
The data stored for the study was the user’s email address, degree program, their IP address and location, the meter type they were exposed to, their password strength calculated using the algorithm discussed in 3.1, the characteristics of the passwords, hashed password using “bcrypt” algorithm and salted with a random cryptographic salt, and the number of unique password tries along with their score
Summary
Online users are expected to reach 4 billion by 2019, generating around 44 zettabytes of data by 2020 [1]. All of this data is valuable for the individual, the institution, and any malicious actor. The exposure of personally identifiable information (PII) includes information such as email addresses, passwords, secret questions, and their answers It has compromised the confidentiality and integrity of information and risked the privacy and security of the user. Institutions suffering these attacks face economic loss as well as loss of reputation. Around 62% of the data breaches that occurred in 2016 were as a result of hacking, and out of those a staggering 81% leveraged the use of either prior stolen information or leveraged weak passwords [4]
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