Related papers: Password Based a Generalize Robust Security System…
The rapid development of computer network system brings both a great convenience and new security threats for users. Network security problem generally includes network system security and data security. Specifically, it refers to the…
Many computer-based authentication schemata are based on pass- words. Logging on a computer, reading email, accessing content on a web server are all examples of applications where the identification of the user is usually accomplished…
Conventional cryptography methods alone are not adequate for secure routing in Wireless Sensor Networks (WSNs). These networks are more vulnerable to security attacks due to their diverse applications, lack of supervision and limitations in…
Neural cryptography is based on synchronization of tree parity machines by mutual learning. We extend previous key-exchange protocols by replacing random inputs with queries depending on the current state of the neural networks. The…
Intrusion detection into computer networks has become one of the most important issues in cybersecurity. Attackers keep on researching and coding to discover new vulnerabilities to penetrate information security system. In consequence…
The advent of large-scale, complex computing systems has dramatically increased the difficulties of securing accesses to systems' resources. To ensure confidentiality and integrity, the exploitation of access control mechanisms has thus…
A myriad of authentication mechanisms embody a continuous evolution from verbal passwords in ancient times to contemporary multi-factor authentication. Nevertheless, digital asset heists and numerous identity theft cases illustrate the…
Radio Frequency Identification (RFID) and biometric technologies saw fast evolutions during the last years and which are used in several applications, such as access control. Among important characteristics in the RFID tags, we mention the…
Neural network inference typically operates on raw input data, increasing the risk of exposure during preprocessing and inference. Moreover, neural architectures lack efficient built-in mechanisms for directly authenticating input data.…
Password managers encourage users to generate passwords to improve their security. However, research has shown that users avoid generating passwords, often giving the rationale that it is difficult to enter generated passwords on devices…
Sensor networks technologies had proved their great practicability in the real world, being just a matter of time until this kind of networks will be standardized and used in the field. This paper presents a new approach to secure the…
Binarized Neural Networks (BNNs) are a class of deep neural networks designed to utilize minimal computational resources, which drives their popularity across various applications. Recent studies highlight the potential of mapping BNN model…
Nowadays, advanced security mechanisms exist to protect data, systems, and networks. Most of these mechanisms are effective, and security experts can handle them to achieve a sufficient level of security for any given system. However, most…
A large chunk of research on the security issues of neural networks is focused on adversarial attacks. However, there exists a vast sea of simpler attacks one can perform both against and with neural networks. In this article, we give a…
Passwords remain one of the most common methods for securing sensitive data in the digital age. However, weak password choices continue to pose significant risks to data security and privacy. This study aims to solve the problem by focusing…
Whenever we think of cyber applications, we visualize the model that gives the idea that we are sitting in front of computer at home or workplace connected to internet and performing all the work that generally we have to go and do on a…
The ability to hide information from unauthorized individuals has been a prevalent issue over the years. Countless algorithms such as DES, AES and SHA have been developed. These algorithms depend on varying key length and key management…
Since the demise of the password was predicted in 2004, different attempts in industry and academia have been made to create an alternative for the use of passwords in authentication, without compromising on security and user experience.…
Security flaws in software applications today has been attributed mostly to design flaws. With limited budget and time to release software into the market, many developers often consider security as an afterthought. Previous research shows…
Recently, deep learning, which uses Deep Neural Networks (DNN), plays an important role in many fields. A secure neural network model with a secure training/inference scheme is indispensable to many applications. To accomplish such a task…