Password-based Authentication Mechanism Research Articles

A portable blind cloud storage scheme against compromised servers

Applications (Apps) generate large amounts of data on users’ storage-limited local devices. To alleviate the burden of local storage, users can outsource their App-generated data to a remote cloud server. Secure data outsourcing needs data portability and blindness. The former enables users to access data from multiple devices using a single password, and the latter ensures data privacy against unauthorized individuals. Portable blind cloud storage (PBCS) can satisfy both requirements. However, existing PBCS schemes are vulnerable to offline password guessing attacks (OPGA) if both the App server and the cloud server are compromised: an adversary can learn users’ passwords from compromised registered information of users. In this paper, we propose a PBCS scheme called IPBCS that is secure against OPGA. In IPBCS, a user hardens her/his password with a secret key, which is stored in trusted execution environments (TEE). With the hardened password and a user-specific randomness, a token can be derived for user authentication. By adopting TEE to protect secret keys, IPBCS guarantees security against OPGA even if both servers are compromised. Moreover, IPBCS adopts a password-based authentication mechanism to support authentication over public channels. Security analysis and performance evaluation demonstrate that IPBCS is secure and efficient.

Secure Socket Shell Bruteforce Attack Detection With Petri Net Modeling

Secure Socket Shell exposes a secure interface for login to remote users. Password based authentication mechanism used by remote users is vulnerable to bruteforcing. In this attack an adversary systematically tries many passwords. These attacks can either be generated from a single source or collectively from a set of sources. In this paper we propose a method to detect such bruteforcing attacks and subsequently classify these attempts into three types as originating from single source, single domain and distributed attacks. We develop Petri-Net based model which identifies SSH connections corresponding to failed login attempts using network flow characteristics. The model also keeps track of sources of failed login attempts using which it subsequently labels a time interval as experiencing bruteforcing or not and if the interval is experiencing bruteforcing which type of attack it is. We experiment with network traffic collected from a production level server and also generated within a testbed setup and show that our model can detect attacks and also classify them. We also experiment with stealth attack variant where attacker keeps a low profile of attacks and suggest methods to handle such attack instances.

Highly Secure and Easy to Remember Password-Based Authentication Approach

Everyone connected and using the Internet is concerned regarding the security and also the privacy of their sensitive information available on the Internet. As authentication is the fundamental part of security, there are different authentication mechanisms through which the systems can be secured. The password-based authentication mechanism is a cheap and easy method for enforcing authentication in the systems for many years. The weakest aspect in password security is human, as they choose weak and easy to guess passwords or a highly secure and complex password which might be difficult to remember and recover the password. On the other hand, Dictionary and Brute force attacks are widely used to compromise the passwords of the users over the Internet. In this paper, a password generation system is proposed which generates a password based on the user’s input like, time and location data. The system generates a password that is highly secure, easy to remember, easy to recover, and can effectively defend against Brute force and dictionary attacks. The generated passwords have been checked in three online password checkers, which verifies that the system is generating highly secure and crack resistant passwords. The system is implemented using PHP scripting language with a user-friendly environment.

Smart Android Graphical Password Strategy: A Review

In recent years, when users across the world have embraced smart devices in greater numbers owing to recent advances and appealing applications, they have also become a target for criminals who are zealously attempting to breach protection. As a result, a significant number of attacks have been observed on these systems. As a result, several password-based authentication mechanisms have been proposed to counteract these attacks. Among them, the graphical password scheme is more consistent with smart devices, which are highly graphic-oriented. However, current graphical password schemes are vulnerable to a variety of assaults, including shoulder surfing, smudging, intersection attacks, and reflection attacks. Thus, the paper aims to review recent published papers on android smart phone graphical password and identify used techniques. Moreover, the paper analyzes results to give better understanding for users of such devices to protect their devices from unauthorized access and attacks.

Secure Password-Protected Encryption Key for Deduplicated Cloud Storage Systems

In this article, we propose SPADE, an encrypted data deduplication scheme that resists compromised key servers and frees users from the key management problem. Specifically, we propose a proactivization mechanism for the servers-aided message-locked encryption (MLE) to periodically substitute key servers with newly employed ones, which renews the security protection and retains encrypted data deduplication. We present a servers-aided password-hardening protocol to resist dictionary guessing attacks. Based on the protocol, we further propose a password-based layered encryption mechanism and a password-based authentication mechanism and integrate them into SPADE to enable users to access their data only using their passwords. Provable security and high efficiency of SPADE are demonstrated by comprehensive analyses and experimental evaluations.

Not Quite Yourself Today

The shortcomings of the traditional password-based authentication mechanism are becoming increasingly apparent as we transition from "one user - one device" to a richer "multiple users - multiple devices" computing paradigm. The currently dominant research direction focuses on on-device biometrics, which require sensitive information, such as images of a user's face, to be constantly streamed from a single recording source, often the device on which a user is getting authenticated. Instead, in this work we explore the possibilities offered by heterogeneous devices that opportunistically collect non-sensitive data in smart environments. We construct an IoT testbed in which we gather data pertaining to a person's movement in space, interaction with certain physical objects, PC terminal usage, and keyboard typing, and construct machine learning models capturing the person's behaviour traits. We commence our examination with models constructed from data sensed during a previously-completed task run and with such models we achieve up to 68% user identification accuracy (c.f. 7% baseline) among up to 20 individuals. Taking into account the limits of behaviour persistence we then revise our approach to continuously refine the model with the most recently sampled sensor data. This method allows us to achieve 99.3% user verification accuracy and successfully prevent a session takeover attack within 12 seconds with less than 1% of false attack detection.

The Method of Detecting Online Password Attacks Based on High-level Protocol Analysis and Clustering Techniques

Although there have been many solutions applied, the safety challenges related to the password security mechanism are not reduced. The reason for this is that while the means and tools to support password attacks are becoming more and more abundant, the number of transaction systems through the Internet is increasing, and new services systems appear. For example, IoT also uses password-based authentication. In this context, consolidating password-based authentication mechanisms is critical, but monitoring measures for timely detection of attacks also play an important role in this battle. The password attack detection solutions being used need to be supplemented and improved to meet the new situation. In this paper we propose a solution that automatically detects online password attacks in a way that is based solely on the network, using unsupervised learning techniques and protected application orientation. Our solution, therefore, minimizes dependence on the factors encountered by host-based or supervised learning solutions. The certainty of the solution comes from using the results of an in-depth analysis of attack characteristics to build the detection capacity of the mechanism. The solution was implemented experimentally on the real system and gave positive results.

The Method of Detecting Online Password Attacks Based on High-Level Protocol Analysis and Clustering Techniques

Although there have been many solutions applied, the safety challenges related to the password security mechanism are not reduced. The reason for this is that while the means and tools to support password attacks are becoming more and more abundant, the number of transaction systems through the Internet is increasing, and new services systems appear. For example, IoT also uses password-based authentication. In this context, consolidating password-based authentication mechanisms is critical, but monitoring measures for timely detection of attacks also play an important role in this battle. The password attack detection solutions being used need to be supplemented and improved to meet the new situation. In this paper we propose a solution that automatically detects online password attacks in a way that is based solely on the network, using unsupervised learning techniques and protected application orientation. Our solution therefore minimizes dependence on the factors encountered by host-based or supervised learning solutions. The certainty of the solution comes from using the results of in-depth analysis of attack characteristics to build the detection capacity of the mechanism. The solution was implemented experimentally on the real system and gave positive results.

Biometric re-authentication: an approach towards achieving transparency in user authentication

Providing fixed re-authentication attempts to the user in case of password mismatch is a very old concept. But as password based authentication mechanisms are prone to many security attacks, user’s biometric properties along with passwords are highly in use for user authentication these days. It will be more secure and convenient if re-authentication influenced by the biometric behavior of the user is applied in the authentication system. It is a challenging task to identify a genuine user using behavioral biometric due to its low repeatability and wide variation. So, to increase the efficiency and robustness of the authentication system in case of score mismatch, the clustering of user’s behavior and assigning different re-authentication attempt to different cluster is needed. In this paper, we have proposed a transparent fixed text, keystroke based user authentication framework, which will enhance the security of traditional password based authentication mechanism. A new classification algorithm and dynamic attempt allocation algorithm have been proposed which will make the authentication system smart enough to provide the genuine user a fare authentication attempt.

Online Signature Authentication by Using Mouse Behavior

Several large-scale parole leakages exposed users to associate unprecedented risk of speech act and abuse of their data. associate inadequacy of password-based authentication mechanisms is turning into a serious concern for the complete data society. carries with it 3 major modules: (1) Mouse–Behavior dynamics Capture, (2) Feature Construction, and (3) coaching or Classification. the primary module serves to make a taking mouse behavior user signs. The second module is employed to extract holistic and procedural options to characterize mouse behavior and to map the raw options into distance-based options by exploitation numerous distance metrics. The third module, within the coaching section, applies neural network on the distance-based feature vectors to reckon the predominant feature elements, then builds the user’s profile employing a one-class classifier. within the classification section, it determines the user’s identity exploitation the trained classifier within the distance-based feature exploitation NN. A four Digit OTP is generated to the user’s email ID. The user are going to be giving the ‘2’ digit OTP and therefore the server are going to be giving balance ‘2’ digit OTP. Users ‘2’ digit OTP is verified by the server and contrariwise.

Holistic and Procedural Features for Authenticating Users

Security systems help to protect machines or sensitive data from unauthorized users. The need for better and cheap security systems is growing with the growth in technologies and hacking skills of the people. Various techniques are available that can provide some level of security. The problem of unintended side-effects of inconsistent experimental condition and environmental variables by restricting user's mouse operation to a tightly-controlled environment has been addressed with the solution of mouse operations as dynamics. Mouse dynamics measures and assesses a user's mouse-behavior characteristic for use as a biometric. For Each mouse operation task both holistic and procedural features are extracted. This type of authentication is very simple and efficient for the users. Then a Nearest Neighbor algorithm is employed for extracting the feature and anytime algorithm for the accuracy and speed. This approach achieves to improve the number of users with a false acceptance rate of 8.75% and a false rejection rate of 7.70%.This approach could lead to a performance boost both in authentication accuracy and authentication time. I. Introduction As data are moved from traditional localized computing environments to the new cloud computing paradigm, the need for better authentication has become more pressing. These things should provide public confidence in the security of the current information infrastructure; the inadequacy of password-based authentication mechanism is becoming a major concern for the entire information society of various solutions to this problem, a particularly promising technique is mouse dynamics. Hence it is suitable for the current internet environment. When users try to log into a computer system, mouse dynamic only requires her to provide the login name and to perform certain sequence of mouse operations. Mouse dynamic based user authentication, usually only the data from the legitimate user are readily available, since the user would choose her specific sequence of mouse operation and would not share it with others. A mouse dynamic based user authentication performs authentication in a short time while maintaining high accuracy. The several properties are (a) it is easy to comprehend and implement, (b) it requires no specialized hardware (c) it requires only about 12 seconds o mouse behavior data to provide good, steady performance. Mouse dynamic is a behavioral biometric for analyzing behavior data from pointing devices, provides user authentication in an accessible and convenient manner. The mouse dynamic is mostly used for intrusion detection, which analyzes mouse-behavior characteristics at particular moments. Information security (IS) The protection of information and information systems against unauthorized access or modification of information, whether in storage, processing, or transit, and against denial of service to authorized users. Information security includes those measures necessary to detect, document, and counter such threats. Information security is composed of computer security and communications security.

A Novel User Authentication Scheme Based on QR-Code

User authentication is one of the fundamental procedures to ensure secure communications and share system resources over an insecure public network channel. Thus, a simple and efficient authentication mechanism is required for securing the network system in the real environment. In general, the password-based authentication mechanism provides the basic capability to prevent unauthorized access. Especially, the purpose of the one-time password is to make it more difficult to gain unauthorized access to restricted resources. Instead of using the password file as conventional authentication systems, many researchers have devoted to implement various one-time password schemes using smart cards, time-synchronized token or short message service in order to reduce the risk of tampering and maintenance cost. However, these schemes are impractical because of the far from ubiquitous hardware devices or the infrastructure requirements. To remedy these weaknesses, the attraction of the QR - code technique can be introduced into our one-time password authentication protocol. Not the same as before, the proposed scheme based on QR code not only eliminates the usage of the password verification table, but also is a cost effective solution since most internet users already have mobile phones. For this reason, instead of carrying around a separate hardware token for each security domain, the superiority of handiness benefit from the mobile phone makes our approach more practical and convenient.