Persuasive cued click-points: Design, implementation, and evaluation of a knowledge-based “Graphical password authentication using cued click points. Request PDF on ResearchGate | Graphical Password Authentication Using Cued Click Points | We propose and examine the usability and. Cued Click Points Password Authentication using Picture Grids. Article (PDF . new click-based graphical password scheme called Cued.

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After done with all these above procedure, user profile vector will be created. At a normal viewing distance for a computer screen, say 60 cm, this results in sharp vision over an area of approximately 4cm2. Each image consists of only one click point as a user password.

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Graphical passwords have been designed to try to make passwords more memorable and easier for people to use and, therefore, more secure.

Although attackers must perform proportionally more work to exploit hotspots, results showed that hotspots remained a problem [2]. Once the first participant has logged out, the other participants are asked to enter the same password which they have observed of the first participant.

In this paper focuses on the integrated evaluation of the Persuasive Cued Click Points graphical password authentication system, including usability and security.

Click Passwords Under Investigation.

One of the proposed attacks on PassPoints is an automated pattern-based dictionary attack that prioritizes passwords consisting of click-points ordered in a consistent horizontal and vertical direction including straight lines in any direction, arcs, and step patternsbut ignores any image-specific features such as hotspots. Graphical passwords may also potentially be shared by taking photos, capturing screen shots, authenticatuon drawing, albeit requiring more effort than for text passwords.

It is the value which indicates the degree of closeness to the actual click point. An online attack could be thwarted by limiting the number of incorrect guesses per account.

PCCP encourages and guides users in selecting more random click-based graphical passwords. Users tend to choose memorable passwords that are easy for attackers to guess, but strong system assigned passwords are difficult for users to remember.


Among which the participant needs to click on any one point of his choice to make it a click point in the series. For capture attacks, PCCP is susceptible to shoulder surfing and malware capturing user input during password entry. Users select their images only to the extent that their click-point loints the next image. Security CCSNov. The path-of-least resistance for users is grahpical select a stronger password not comprised entirely of known hotspots or following a predictable pattern.

It is the rate which gives the number of successful trails for a certain number of trials. During system login, the images are displayed normally, without shading or the viewport, and repeat the sequence of clicks in the correct order, within a system-defined tolerance square of the original click-points.

Mistakes occur when the participant presses the Login button but the password is incorrect. To explore an offline version of this attack, assume in the worst case that attackers gain access to all serverside information: In click-based graphical passwords, poorly chosen passwords lead to the emergence of hotspots portions of the image where users are more likely to select click-points, allowing attackers to mount more successful dictionary attacks.

All three cued-recall schemes discussed PCCP, CCP, and PassPoints are susceptible to shoulder surfing although no published empirical study to date has examined the extent of the threat. To log in, they repeat the sequence of clicks in the correct order, within a system-defined tolerance square of the original click-points.

We thank the participants of our lab study for their time andValuable feedback. Given that hotspots and click-point clustering are significantly less prominent for PCCP than for CCP and PassPoints, guessing attacks based on these characteristics are less likely to succeed. Previous models have shown that hotspots are a problem in click-based graphical passwords, leading to a reduced effective password space that facilitates more successful dictionary attacks.


In this lab study, initially three participants are considered for the experiment. Then, the participant logs in with that password, meantime the other participants are made to stand in a group behind the participant who is entering the password and are made to peek in over the shoulder of the participant and observe his password the click points on the images.

It is a type of capture attack. In recognition based,a user is presented with a set of images and the user passes the authentication by recognizing and identifying the images he selected during the registration stage. The viewport positioning algorithm randomly placed the viewport on the image, ensuring that the entire viewport was always visible and that users had the entire viewport area from which to select a click-point. The shuffle button was used moderately.

We interviewed participants to learn about their shuffling strategy. In PassPoints, a password consists of a sequence of five click-points on a given image see Figure 1. Physiologically, the human eye can observe only a small part of an image at a time. One preliminary study [22] suggests that password sharing through verbal description may be possible for PassPoints.


Remembering the order of the click-points is no longer a requirement on users, as the system presents the images one at a time. A potential improvement would be to allow the viewport to wrap around the edges of pointz image, resulting in situations where the viewport is split on opposite edges of the image.

User interface manipulations such as reducing the size of the mouse cursor or dimming the image may offer some protection, but have not been tested. Design and longitudinal evaluation of a graphical password system.