Alphanumeric Passwords Research Articles

State space classification of Markov password – an alphanumeric password authentication scheme for secure communication in cloud computing

PurposePurpose of this study is to classify the states of Markov Chain for the implementation of Markov Password for effective security. Password confirmation is more often required in all authentication process, as the usage of computing facilities and electronic devices have developed hugely to access networks. Over the years with the increase in numerous Web developments and internet applications, each platform needs ID and password validation for individual users.Design/methodology/approachIn the technological development of cloud computing, in recent times, it is facing security issues. Data theft, data security, denial of service, patch management, encryption management, key management, storage security and authentication are some of the issues and challenges in cloud computing. Validation in user login authentications is generally processed and executed by password. To authenticate universally, alphanumeric passwords are used. One of the promising proposed methodologies in this type of password authentication is Markov password. Markov passwords – a rule-based password formation are created or generated by using Markov chain. Representation of Markov password formation can be done by state space diagram or transition probability matrix. State space classification of Markov chain is one of the basic and significant properties. The objective of this paper is to classify the states of Markov chain to support the practice of this type of password in the direction of effective authentication for secure communication in cloud computing. Conversion of some sample obvious password into Markov password and comparative analysis on their strength is also presented in this paper. Analysis on strength of obvious password of length eight has shown range of 7%–9% although the converted Markov password has shown more than 82%. As an effective methodology, this password authentication can be implemented in cloud portal and password login validation process.FindingsThe objective of this paper is to classify the states of Markov chain to support the practice of this type of password in the direction of effective authentication for secure communication in cloud computing. Conversion of some sample obvious password into Markov password and comparative analysis on their strength is also presented in this paper.Originality/valueValidation in user login authentications is generally processed and executed by password. To authenticate universally, alphanumeric passwords are used. One of the promising proposed methodologies in this type of password authentication is Markov password.

GRAPHICAL PASSWORD STRATEGY

The graphical password strategy could really change how a typical user would insert their password and how secure it could be, it still has its flaws and limitations. One of the limitations of a graphical password strategy is that it could be prone to shoulder surfing. Without having a password field just like an alphanumeric password would have, a graphical password could be physically observed and especially in public places and the attacker has a clear visual of the password being inserted for multiple times, they could easily crack the password which is quite a severe flaw. Another potential limitation of a graphical password strategy is that it is prone to guessing as well. Same as an alphanumeric password, if the user only registered a short and predictable password, the chances of it being prone to guessing would increase. To overcome these potential limitations, a shoulder surfing resistant technique could be implemented such as including multiple mouse cursors when the users are logging in to their account which would confuse the attacker from identifying which one is the legitimate mouse cursors and which click points has the user clicked. Next, same as an alphanumeric password, a requirement of at least 10 click points must be clicked to make the graphical password stronger could be implemented to the system to ensure that the user does not just enter a sloppy password which would decrease the chances of an attacker to guess the password of the user dramatically.

Implicit Authentication Approach by Generating Strong Password through Visual Key Cryptography

In this era of digitization where literally everything is available at the tip of the finger. Huge amount of data used to flow day in day out, where users used to work with various applications like internet websites, cloud applications, various data servers, web servers, etc. This paper provide idea about access control or authentication used to be acting as first line of defense for preserving data secrecy and its integrity, so far it is learned that the usual login password based methods are easy to implement and to use as well but it is also observed that they are more subjected to be get attacked therefore to preserve authentication on the basis of simple alphanumeric passwords is a challenging task now a days. Hence new methods which bring more strength for authentication and access control are so very expected and desirable.

Human Face Identification based on Optimal Sparse Features

Security of human being is an important aspect in the context of data communication. To maintain security, technology is being developed from alpha-numeric passwords to biometric scanners. Recent advancement in security is the user authentication using face recognition. But the flaws in existing face recognition systems are yet to be addressed. This paper discusses solutions to the issues encountered by face recognition systems. Sparsity based classification is performed in this work. This method can handle errors occurs due to compress in and occlusion in a robust manner. We suggest a comprehensive classification algorithm characterized by sparse representation and 1l -minimization. In this method, the feature points and selection of features are not critical. The effect of change in occlusion can be easily addressed by using this optimal sparse representation based classification (OSRC) algorithm.

Graphical Authentication Passcode Memorability: Context, Length, and Number

Authentication verifies users’ identities to protect against costly attacks. Graphical authentication schemes utilize pictures as passcodes rather than strings of characters, numbers, and symbols. Pictures are more memorable than alphanumeric passwords. Two studies investigated the memorability of graphical passcodes when users need to remember multiple passcodes or longer passcodes. Longer passcodes provide advantages to security by protecting against brute force attacks, and multiple passcodes need to be investigated as users need to authenticate for numerous accounts. It was found that participants have strong item retention for passcodes of up to eight images and for up to eight accounts. Also, these studies examined whether context can facilitate memorability. The impact of context was not found as assumed in the literature. Overall, memorability was still higher for all the number and length passcode conditions compared with alphanumeric passwords. These studies take steps toward understanding the readiness of graphical schemes as an authentication option.

PILOT: Password and PIN information leakage from obfuscated typing videos1

This paper studies leakage of user passwords and PINs based on observations of typing feedback on screens or from projectors in the form of masked characters that indicate keystrokes. To this end, we developed an attack called Password and Pin Information Leakage from Obfuscated Typing Videos (PILOT). Our attack extracts inter-keystroke timing information from videos of password masking characters displayed when users type their password on a computer, or their PIN at an ATM. We conducted several experiments in various attack scenarios. Results indicate that, while in some cases leakage is minor, it is quite substantial in others. By leveraging inter-keystroke timings, PILOT recovers 8-character alphanumeric passwords in as little as 19 attempts. When guessing PINs, PILOT significantly improved on both random guessing and the attack strategy adopted in our prior work [4]. In particular, we were able to guess about 3% of the PINs within 10 attempts. This corresponds to a 26-fold improvement compared to random guessing. Our results strongly indicate that secure password masking GUIs must consider the information leakage identified in this paper.

Graphical User Authentication System Resistant to Shoulder Surfing Attack

User authentication is one of the most significant issues in the field of Information Security. The most common and convenient authentication method used is the alphanumeric password which has significant drawbacks. To overcome the vulnerabilities of traditional methods, graphical password schemes have been developed as possible alternative solutions to text-based scheme. A potential drawback of graphical password schemes is that they are more vulnerable to shoulder surfing than conventional alphanumeric text passwords due to their visual interface. To overcome the shortcoming of existing graphical password schemes this project focuses on developing a graphical authentication system that is resistant to shoulder surfing attack.

TAPSTROKE: A novel intelligent authentication system using tap frequencies

Emerging security requirements lead to new validation protocols to be implemented to recent authentication systems by employing biometric traits instead of regular passwords. If an additional security is required in authentication phase, keystroke recognition and classification systems and related interfaces are very promising for collecting and classifying biometric traits. These systems generally operate in time-domain; however, the conventional time-domain solutions could be inadequate if a touchscreen is so small to enter any kind of alphanumeric passwords or a password consists of one single character like a tap to the screen. Therefore, we propose a novel frequency-based authentication system, TAPSTROKE, as a prospective protocol for small touchscreens and an alternative authentication methodology for existing devices. We firstly analyzed the binary train signals formed by tap passwords consisting of taps instead of alphanumeric digits by the regular (STFT) and modified short time Fourier transformations (mSTFT). The unique biometric feature extracted from a tap signal is the frequency-time localization achieved by the spectrograms which are generated by these transformations. The touch signals, generated from the same tap-password, create significantly different spectrograms for predetermined window sizes. Finally, we conducted several experiments to distinguish future attempts by one-class support vector machines (SVM) with a simple linear kernel for Hamming and Blackman window functions. The experiments are greatly encouraging that we achieved 1.40%–2.12% and 2.01%–3.21% equal error rates (EER) with mSTFT; while with regular STFT the classifiers produced quite higher EER, 7.49%–11.95% and 6.93%–10.12%, with Hamming and Blackman window functions, separately. The whole methodology, as an expert system for protecting the users from fraud attacks sheds light on new era of authentication systems for future smart gears and watches.

G-RAT | A Novel Graphical Randomized Authentication Technique for Consumer Smart Devices

User authentication is the process that is exercised millions of times around the globe by using different techniques and methods. The most prominent way of authentication is alphanumerical password forms that have been used for decades. Authorized access is becoming a challenging issue because of the introduction of modern technologies. In addition, traditional alphanumerical passwords have significant security issues, for example, humans forget the combination of keys due to the selection of a difficult key combination. Moreover, when they choose an easy key combination, this helps hackers to crack their passwords easily. Traditional passwords are also vulnerable to several types of attacks, for example, dictionary attack, brute force attack, and malware. To provide an easy and more secure authentication technique, a graphical password has been introduced in this paper for consumer electronic devices, which uses an image or a set of images for authentication. We have categorized the existing graphical password methods into recognition-based, cued-recall-based, pure-recall-based, and hybrid techniques. Due to the limitations of the existing graphical passwords, we have introduced a new technique, named graphical random authentication technique (gRAT), which generates a randomized set of images every time a user tries to authenticate him/herself by maintaining the security and usability at the same time. The gRAT technique is also tested by user-centric evaluation in terms of security, usability, usefulness, and utility, and the experimental results show that the proposed technique is more secure and useful in the real-life authentication applications.

Secured Key Management Scheme for Multicast Network Using Graphical Password

In recent days, management of keys in a group has become a significant part of data communication. The textual and alphanumerical passwords used for security concern have now changed its trend to different graphical passwords procedures. Many researchers have introduced various efficient and scalable key management schemes and it is difficult to remember this type of password. There are many textual password authentication mechanisms now available in the software market and are prone to eavesdropping, dictionary attacks and shoulder surfing. To address all the above vulnerability, many researchers and practitioners have developed different authentication methods who are interested in finding an alternate way to the existing problem. Hence, this paper proposes a secure group communication scheme between group members using graphical passwords and this is easy to remember compared to a textual password but difficult to hack. The elliptic curve cryptography technique is applied for key distribution. The group key is a graphical password which is static and shared among all the members in a group. The sequence of images will be sent to the members/users of a group during registration to form a group key and the group controller sends a pass point value of each image to the member by using elliptic curve cryptography after the registration. The main focus of the proposed scheme is to provide better security and ensures negligible communication overhead and computation overhead.

Privacy-Preserving iVector-Based Speaker Verification

This paper introduces an efficient algorithm to develop a privacy-preserving voice verification based on iVector and linear discriminant analysis techniques. This research considers a scenario in which users enrol their voice biometric to access different services (i.e., banking). Once enrolment is completed, users can verify themselves using their voice print instead of alphanumeric passwords. Since a voice print is unique for everyone, storing it with a third-party server raises several privacy concerns. To address this challenge, this paper proposes a novel technique based on randomization to carry out voice authentication, which allows the user to enrol and verify their voice in the randomized domain. To achieve this, the iVector-based voice verification technique has been redesigned to work on the randomized domain. The proposed algorithm is validated using a well-known speech dataset. The proposed algorithm neither compromises the authentication accuracy nor adds additional complexity due to the randomization operations.

A Fractal-Based Authentication Technique Using Sierpinski Triangles in Smart Devices.

The prevalence of smart devices in our day-to-day activities increases the potential threat to our secret information. To counter these threats like unauthorized access and misuse of phones, only authorized users should be able to access the device. Authentication mechanism provide a secure way to safeguard the physical resources as well the information that is processed. Text-based passwords are the most common technique used for the authentication of devices, however, they are vulnerable to a certain type of attacks such as brute force, smudge and shoulder surfing attacks. Graphical Passwords (GPs) were introduced as an alternative for the conventional text-based authentication to overcome the potential threats. GPs use pictures and have been implemented in smart devices and workstations. Psychological studies reveal that humans can recognize images much easier and quicker than numeric and alphanumeric passwords, which become the basis for creating GPs. In this paper a novel Fractal-Based Authentication Technique (FBAT) has been proposed by implementing a Sierpinski triangle. In the FBAT scheme, the probability of password guessing is low making system resilient against abovementioned threats. Increasing fractal level makes the system stronger and provides security against attacks like shoulder surfing.

The Coin Passcode: A Shoulder-Surfing Proof Graphical Password Authentication Model for Mobile Devices

Swiftness, simplicity, and security is crucial for mobile device authentication. Currently, most mobile devices are protected by a six pin numerical passcode authentication layer which is extremely vulnerable to Shoulder-Surfing attacks and Spyware attacks. This paper proposes a multi-elemental graphical password authentication model for mobile devices that are resistant to shoulder surfing attacks and spyware attacks. The proposed Coin Passcode model simplifies the complex user interface issues that previous graphical password models have, which work as a swift passcode security mechanism for mobile devices. The Coin Passcode model also has a high memorability rate compared to the existing numerical and alphanumerical passwords, as psychology studies suggest that human are better at remembering graphics than words. The results shows that the Coin Passcode is able to overcome the current shoulder-surfing and spyware attack vulnerability that existing mobile application numerical passcode authentication layers suffer from.

What Kind of Grid Formations and Password Formats are Useful for Password Authentication with Eye-Gaze-Based Input?

This study investigates which grid formations and password formats are useful for password authentication by means of eye-gazebased input. Sixteen grid formations were made, in between 3×3 to 6×6 cells (columns-by-rows), for three password formats. The formats were an alphanumeric format, a pattern format, and a picture format. The participants were asked to memorize a 4-object or a 6-object password and register (Task 1), confirm (Task 2), and log in (Task 4) the password on each of the 16 grids with eye-gaze-based input. In Task 3, the participants evaluated each grid with a rating scale. The results showed that task-completion time was mostly shorter for the alphanumeric password format than for the pattern or picture format. Task-completion time of 4-object or 6-object passwords generally increased as the grid density increased, while the task-success rate at the first attempt decreased when the grid density increased. Task-completion time often was longer for grids with more rows than columns (vertical formations, e.g., 3×4 cells) than for grids with more columns than rows (horizontal formations, e.g., 4×3 cells). These results suggest that password authentication with eye-gaze-based input is best performed on horizontal grids with relatively few cells and a traditional (alphanumeric) format.

A Graphical Authentication System Controlled by Eye Movement

Graphical password is a potential alternative to the traditional alphanumerical password due to its advantages of recognition and memory in the security system. Eye movement, a natural interaction modality, is a promising tool to replace the keyboard and the mouse in authentication. This paper proposes a graphical authentication system controlled by eye movement. In this keyboard-less authentication system, the user’s eye movements were recorded by eye-tracker as the control signal to generate recognition-based graphical passwords. The user test study has been conducted to verify the availability and effectiveness of this keyboard-less graphical authentication system. It’s also shown that the efficiency could be improved as the user getting familiar with this system.

NTRU based Security in Cloud Computing

The usage of Cloud Computing users keep their facts onto the third party owners and experience the online demand programs, services and garage from a shared pool of configurable computing resources, without the load of facts garage and protection and costs. The furnished security must guarantee no longer best on authentication but also on files over the cloud for the outsourced records, that is now maintained by way of third parties consisting of cloud carriers. Unluckily, the infrastructure of cloud computing is constructed on internet, and will stumble upon all of the risk of net. To lower the risks, an authentication mechanism is the viable answer. However, conventional alphanumeric password authentication mechanism isn't always relaxed sufficient. A cozy authentication mechanism the use of public-key encryption based totally password have to be proposed in this paper for enhancing traditional authentication mechanism and let users get entry to cloud services securely.

Sketch-Based User Authentication With a Novel String Edit Distance Model

The vast majority of user authentication in digital applications is based on alphanumeric passwords. Yet, due to severe problems that might arise with this approach, various efforts have been made in the last decade to replace this authentication paradigm. One candidate for the prospective paradigm shift might be found in the field of graphical passwords. The present paper introduces a novel framework for user authentication based on freehand sketches. The basic idea is that during the registration phase a user draws an arbitrary sketch in a specific drawing canvas (rather than typing a password). Registered users can then be authenticated whenever they are able to reproduce their personal sketch with sufficient precision. The major challenge of such a system is twofold. First, it has to provide a certain degree of error-tolerance such that the authentication of genuine users can be smoothly accomplished. Second, the system should detect even subtle forgeries and reject possible intruders. The main contributions of this paper are as follows. First, we formally represent the underlying sketches by means of strings and present a general authentication algorithm that is based on structural pattern recognition. Second, we present a novel cost model that is particularly useful in conjunction with string matching. Third, by means of an exhaustive empirical investigation using both random and skilled forgeries (stemming from several hundreds of users) we empirically confirm the feasibility of this particular authentication framework in a real-world scenario.

Divide and Conquer Approach for Solving Security and Usability Conflict in User Authentication

Knowledge based authentication schemes are divided into textual password schemes and graphical password schemes. Textual password schemes are easy to use but have well known security issues, such as weak against online security attacks. Graphical password schemes are generally weak against shoulder surfing attacks. Usability is another issue with most of the graphical password schemes. For improving security of knowledge-based authentication schemes complex password entry procedures are used, which improve security but weakens useability of the authentication schemes. In order to resolve this security and usability conflict, a user authentication scheme is proposed, which contains one registration and two login screens called easy and secure login screens. Easy login screen provides easy and quick way of authentication while secure login screen is resilient to different online security attacks. A user has to decide based upon the authentication environment, which login screen to be used for authentication. For secure environment, where chances of security attacks are less easy login screen is recommended. For insecure environments where chances of security attacks are high, secure login screen is recommended for authentication. In the proposed scheme, image based passwords can also be set along with alphanumeric passwords. Results suggest that proposed scheme improves security against offline and online attacks.

CMAPS: A Chess-Based Multi-Facet Password Scheme for Mobile Devices

It has long been recognized, by both security researchers and human–computer interaction researchers, that no silver bullet for authentication exists to achieve security , usability , and memorability . Aiming to achieve the goals, we propose a Multi-fAcet Password Scheme (MAPS) for mobile authentication. MAPS fuses information from multiple facets to form a password, allowing MAPS to enlarge the password space and improve memorability by reducing memory interference, which impairs memory performance according to psychology interference theory. The information fusion in MAPS can increase usability, as fewer input gestures are required for passwords of the same security strength. Based on the idea of MAPS, we implement a Chess-based MAPS (CMAPS) for Android systems. Only two and six gestures are required for CMAPS to generate passwords with better security strength than 4-digit PINs and 8-character alphanumeric passwords, respectively. Our user studies show that CMAPS can achieve high recall rates while exceeding the security strength of standard 8-character alphanumeric passwords used for secure applications.

Pixel Value Graphical Password Scheme: Fake <i>Passpix</i> Attempt on Hexadecimal Password Style

Early design of graphical password scheme solved the strong alphanumeric password deficiencies in term of hard to memorized, but they was exposed to password shoulder surfing and complicated to produced even by the legitimate users. Motivated to solve the problems, pixel value graphical password scheme was developed in 2012 where it require user to load any their desired digital image as their password. The term <i>Passpix</i> is referring to the pixel value that extracted from the loaded image file derived from the words password pixel. Pixel value in the form of RGB color strength could be representing as 3-octets 8-bits color code (0 to 255) or Hexadecimal code (000000 to FFFFFF) produced 16,777,216 combinations. Pixel value graphical password increases the password strength by implementing two-dimensional 8 by 8 grid extraction that increases the password strength to 1,073,741,824 combinations. It would result the password could be long or super long. Currently, pixel value graphical password scheme using the 8-bits color code as the pixel value and password that stored into database which could produce up to 576 characters. This would be require more storage capacity to store the password that brings into a suggestion to extracting the pixel value using hexadecimal code which produced 384 characters only. Further study on that idea it is found that the number of password characters did not brings a significant impact on-disk data size and it is easy information to construct a fake <i>Passpix</i> which is discussed further in this paper. This paper is organized into 5 sections where the background and concept of pixel value graphical password scheme is introduced in section 1. Section 2 of this paper is describing the password style of pixel value graphical password. The fake <i>Passpix</i> reconstruction is briefly explained in section 3 and section 4 is discussed further about the fake <i>Passpix</i> findings. The conclusion of this study can be found in section 5 and at the end of this paper, there are list of several references used in this study. Hopefully this paper will brings major contribution for safer pixel value graphical password scheme.