Search results for: gesture-based passwords

Authors: Aboli Dhanavade, Shweta Bhimnath, Rutuja Jumale, Ajay Nadargi

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Security to any of our personal thing is our most basic need. It is not possible to directly apply that standard Human-computer—interaction approaches. Important usability goal for authentication system is to support users in selecting best passwords. Users often select text-passwords that are easy to remember, but they are more open for attackers to guess. The human brain is good in remembering pictures rather than textual characters. So the best alternative is being designed that is Graphical passwords. However, Graphical passwords are still immature. Conventional password schemes are also vulnerable to Shoulder-surfing attacks, many shoulder-surfing resistant graphical passwords schemes have been proposed. Next, we have analyzed the security and usability of the proposed scheme, and show the resistance of the proposed scheme to shoulder-surfing and different accidental logins.

Keywords: shoulder-surfing, security, authentication, text-passwords

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Authors: Bandar Alahmadi

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The fact that people tend to remember pictures better than texts, motivates researchers to develop graphical passwords as an alternative to textual passwords. Graphical passwords as such were introduced as a possible alternative to traditional text passwords, in which users prove their identity by clicking on pictures rather than typing alphanumerical text. In this paper, we present a scheme for graphical passwords that are resistant to shoulder surfing attacks and spyware attacks. The proposed scheme introduces a clicking technique to chosen images. First, the users choose a set of images, the images are then included in a grid where users can click in the cells around each image, the location of the click and the number of clicks are saved. As a result, the proposed scheme can be safe from shoulder surface and spyware attacks.

Keywords: security, password, authentication, attack, applications

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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For security purposes, it is important to detect passwords entered by unauthorized users. With traditional alphanumeric passwords, if the content of a password is acquired and correctly entered by an intruder, it is impossible to differentiate the password entered by the intruder from those entered by the authorized user because the password entries contain precisely the same character set. However, no two entries for the gesture-based passwords, even those entered by the person who created the password, will be identical. There are always variations between entries, such as the shape and length of each stroke, the location of each stroke, and the speed of drawing. It is possible that passwords entered by the unauthorized user contain higher levels of variations when compared with those entered by the authorized user (the creator). The difference in the levels of variations may provide cues to detect unauthorized entries. To test this hypothesis, we designed an empirical study, collected and analyzed the data with the help of machine-learning algorithms. The results of the study are significant.

Keywords: authentication, gesture-based passwords, shoulder-surfing attacks, usability

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Faraji Sepideh

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Nowadays, purchase rate of the smart device is increasing and user authentication is one of the important issues in information security. Alphanumeric strong passwords are difficult to memorize and also owners write them down on papers or save them in a computer file. In addition, text password has its own flaws and is vulnerable to attacks. Graphical password can be used as an alternative to alphanumeric password that users choose images as a password. This type of password is easier to use and memorize and also more secure from pervious password types. In this paper we have designed a more secure graphical password system to prevent shoulder surfing, smudge and brute force attack. This scheme is a combination of two types of graphical passwords recognition based and Cued recall based. Evaluation the usability and security of our proposed scheme have been explained in conclusion part.

Keywords: brute force attack, graphical password, shoulder surfing attack, smudge attack

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Authors: Saransh Sharma, Atharv Dekhne

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Passwords stored on central services and hashed are prone to cyberattacks and hacks. Hence, given all these nuisances, there’s a need to eliminate character-based authentication protocols, which would ultimately benefit all developers as well as end-users.To replace this conventional but antiquated protocol with a secure alternative would be Passwordless Authentication. The meta root.id system creates a public and private key, of which the user is only able to access the private key. Further, after signing the key, the user sends the information over the API to the server, which checks its validity with the public key and grants access accordingly.

Keywords: passwordless, OAuth, bitcoin, ZKP, SIN, BIP

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Authors: Hashim Ali, Sheheryar Khan

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Security for applications is always been a keen issue of concern. In general, security is to allow access of grant to legal user or to deny non-authorized access to the system. Shoulder surfing is an observation technique to hack an account or to enter into a system. When a malicious observer is capturing or recording the fingers of a user while he is entering sensitive inputs (PIN, Passwords etc.) and may be able to observe user’s password credential. It is very rigorous for a novice user to prevent himself from shoulder surfing or unaided observer in a public place while accessing his account. In order to secure the user account, there are five factors of authentication; they are: “(i) something you have, (ii) something you are, (iii) something you know, (iv) somebody you know, (v) something you process”. A technique has been developed of fifth-factor authentication “something you process” to provide novel approach to the user. In this paper, we have applied position based operational code authentication in such a way to more easy and user friendly to the user.

Keywords: shoulder surfing, malicious observer, sensitive inputs, authentication

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Authors: Shatadru Das, Natarajan Vijayarangan

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In this paper, a system and method for generating and recovering an authorization code has been designed and analyzed. The system creates an authorization code by accepting a base-sentence from a user. Based on the characters present in this base-sentence, the system computes a base-sentence matrix. The system also generates a plurality of patterns. The user can either select the pattern from the multiple patterns suggested by the system or can create his/her own pattern. The system then performs multiplications between the base-sentence matrix and the selected pattern matrix at different stages in the path forward, for obtaining a strong authorization code. In case the user forgets the base sentence, the system has a provision to manage and retrieve 'forgotten authorization code'. This is done by fragmenting the base sentence into different matrices and storing the fragmented matrices into a repository after computing matrix multiplication with a security question-answer approach and with a secret key provided by the user.

Keywords: easy authentication, key retrieval, memorable passwords, strong password generation

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Authors: Sajad Shokohuyar, Mahsa Zomorrodi Anbaji, Saghar Pouyan Shad

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According to fast technology growth, modern banking tries to decrease going to banks’ branches and increase customers’ consent. One of the problems which banks face is securing customer’s password. The banks’ solution is one time password creation system. In this research by adapting from acceptance of technology model theory, assesses factors that are effective on banking in Iran especially in using one time password machine by one of the private banks of Iran customers. The statistical population is all of this bank’s customers who use electronic banking service and one time password technology and the questionnaires were distributed among members of statistical population in 5 selected groups of north, south, center, east and west of Tehran. Findings show that confidential preservation, education, ease of utilization and advertising and informing has positive relations and distinct hardware and age has negative relations.

Keywords: security, electronic banking, one time password, information technology

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Authors: Raya Al Khayari, Rasha Al Jassim, Muna Al Balushi, Fatma Al Moqbali, Said El Hajjar

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This study utilizes linear regression analysis to investigate the correlation between user account passwords and the probability of civil ID exposure, offering statistical insights into civil ID security. The study employs multiple linear regression (MLR) analysis to further investigate the elements that influence consumers’ views of civil ID security. This aims to increase awareness and improve preventive measures. The results obtained from the MLR analysis provide a thorough comprehension and can guide specific educational and awareness campaigns aimed at promoting improved security procedures. In summary, the study’s results offer significant insights for improving existing security measures and developing more efficient tactics to reduce risks related to civil ID security in Oman. By identifying key factors that impact consumers’ perceptions, organizations can tailor their strategies to address vulnerabilities effectively. Additionally, the findings can inform policymakers on potential regulatory changes to enhance civil ID security in the country.

Keywords: civil-id disclosure, awareness, linear regression, multiple regression

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Jean Rosemond Dora, Karol Nemoga

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In this work, we tackle a frequent problem that frequently occurs in the cybersecurity field which is the exploitation of websites by XSS attacks, which are nowadays considered a complicated attack. These types of attacks aim to execute malicious scripts in a web browser of the client by including code in a legitimate web page. A serious matter is when a website accepts the “user-input” option. Attackers can exploit the web application (if vulnerable), and then steal sensitive data (session cookies, passwords, credit cards, etc.) from the server and/or from the client. However, the difficulty of the exploitation varies from website to website. Our focus is on the usage of ontology in cybersecurity against XSS attacks, on the importance of the ontology, and its core meaning for cybersecurity. We explain how a vulnerable website can be exploited, and how different JavaScript payloads can be used to detect vulnerabilities. We also enumerate some tools to use for an efficient analysis. We present detailed reasoning on what can be done to improve the security of a website in order to resist attacks, and we provide supportive examples. Then, we apply an ontology model against XSS attacks to strengthen the protection of a web application. However, we note that the existence of ontology does not improve the security itself, but it has to be properly used and should require a maximum of security layers to be taken into account.

Keywords: cybersecurity, web application vulnerabilities, cyber threats, ontology model

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Authors: Merve Sadetas Sezer, Ismail Sahin, Ahmet Oguz Akturk

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With the use of developing technology, mostly in communication and entertainment, students spend considerable time on the internet. In addition to the advantages provided by the internet, social isolation brings problems such as addiction. This is one of the problems of the virtual violence. Cyber-bullying is the common name of the intensities which students are exposed on the internet. The purpose of this study designed as a qualitative research is to find out the cyber bullying varieties and its effects on elementary school students. The participants of this research are 6th, 7th and 8th grade students of a primary school and 24 students agreed to participate in the study. The students were asked to fill an interview with semi-structured open-ended questions. According to the results obtained in the research, the most important statements determined by the participants are breaking passwords on social networking sites, slang insult to blasphemy and taking friendship offers from unfamiliar people. According to participants from the research, the most used techniques to prevent themselves from cyber bullying are to complain to the site administrator, closing accounts on social networking sites and countercharging. Also, suggestions were presented according to the findings.

Keywords: bullying, cyber-bullying, elementary, peer-relationship, virtual victimization

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Authors: Naveed Ghani, Samreen Javed

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In today’s heterogeneous network environment, there is a growing demand for distrust clients to jointly execute secure network to prevent from malicious attacks as the defining task of propagating malicious code is to locate new targets to attack. Residual risk is always there no matter what solutions are implemented or whet so ever security methodology or standards being adapted. Security is the first and crucial phase in the field of Computer Science. The main aim of the Computer Security is gathering of information with secure network. No one need wonder what all that malware is trying to do: It's trying to steal money through data theft, bank transfers, stolen passwords, or swiped identities. From there, with the help of our survey we learn about the importance of white listing, antimalware programs, security patches, log files, honey pots, and more used in banks for financial data protection but there’s also a need of implementing the IPV6 tunneling with Crypto data transformation according to the requirements of new technology to prevent the organization from new Malware attacks and crafting of its own messages and sending them to the target. In this paper the writer has given the idea of implementing IPV6 Tunneling Secessions on private data transmission from financial organizations whose secrecy needed to be safeguarded.

Keywords: network worms, malware infection propagating malicious code, virus, security, VPN

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Authors: Alejandro Villegas, Cihan Varol

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Voice over Internet Protocol (VoIP) products is an emerging technology that can contain forensically important information for a criminal activity. Without having the user name and passwords, this forensically important information can still be gathered by the investigators. Although there are a few VoIP forensic investigative applications available in the literature, most of them are particularly designed to collect evidence from the Skype product. Therefore, in order to assist law enforcement with collecting forensically important information from variety of Betamax VoIP tools, CVOIP-FRU framework is developed. CVOIP-FRU provides a data gathering solution that retrieves usernames, contact lists, as well as call and SMS logs from Betamax VoIP products. It is a scripting utility that searches for data within the registry, logs and the user roaming profiles in Windows and Mac OSX operating systems. Subsequently, it parses the output into readable text and html formats. One superior way of CVOIP-FRU compared to the other applications that due to intelligent data filtering capabilities and cross platform scripting back end of CVOIP-FRU, it is expandable to include other VoIP solutions as well. Overall, this paper reveals the exploratory analysis performed in order to find the key data paths and locations, the development stages of the framework, and the empirical testing and quality assurance of CVOIP-FRU.

Keywords: betamax, digital forensics, report utility, VoIP, VoIPBuster, VoIPWise

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Authors: Anthony I. Otuonye, Juliet N. Odii, Perpetual N. Ibe

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The obvious challenges faced by most commercial bank customers while using the services of ATMs (Automated Teller Machines) across developing countries have triggered the need for an improved system with better security features. Current ATM systems are password-based, and research has proved the vulnerabilities of these systems to heinous attacks and manipulations. We have discovered by research that the security of current ATM-assisted banking services in most developing countries of the world is easily broken and maneuvered by fraudsters, majorly because it is quite difficult for these systems to identify an impostor with privileged access as against the authentic bank account owner. Again, PIN (Personal Identification Number) code passwords are easily guessed, just to mention a few of such obvious limitations of traditional ATM operations. In this research work also, we have developed a system of fingerprint biometrics with PIN code Authentication that seeks to improve the security features of traditional ATM installations as well as other Banking Services. The aim is to ensure better security at all ATM installations and raise the confidence of bank customers. It is hoped that our system will overcome most of the challenges of the current password-based ATM operation if properly applied. The researchers made use of the OOADM (Object-Oriented Analysis and Design Methodology), a software development methodology that assures proper system design using modern design diagrams. Implementation and coding were carried out using Visual Studio 2010 together with other software tools. Results obtained show a working system that provides two levels of security at the client’s side using a fingerprint biometric scheme combined with the existing 4-digit PIN code to guarantee the confidence of bank customers across developing countries.

Keywords: fingerprint biometrics, banking operations, verification, ATMs, PIN code

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