Two-factor Research Articles

A blockchain-enabled privacy-preserving authentication management protocol for Internet of Medical Things

Over the last decade, with the increasing popularity and usage of the internet of things worldwide, Internet of Medical Things (IoMT) has emerged as a key technology of the modern era. IoMT uses Artificial Intelligence, 5G, big data, edge computing, and blockchain to provide users with electronic medical services. However, it may face several security threats and attacks over an insecure public network. Therefore, to protect sensitive medical data in IoMT, it is necessary to design a secure and efficient authentication protocol. In this study, we propose a privacy-preserving authentication management protocol based on blockchain. The protocol uses a blockchain to store identities and related parameters to assist communication entities in authentication. In addition, the protocol adopts a three-factor authentication method and introduces Chebyshev chaotic map to ensure the security of user login and authentication. Formal security proof and analysis using the random oracle model and Burrows-Abadi-Needham logic show that the proposed protocol is secure. Moreover, we use informal security analysis to demonstrate that the protocol can resist various security attacks. The functional comparison shows that the protocol has high security. Through performance analysis and comparison with other protocols, the proposed protocol can increase computation overhead, communication overhead, and storage overhead by up to 39.8%, 93.6%, and 86.7%,respectively.

A Novel Two-Factor Authentication Scheme for Increased Security in Accessing the Moodle E-Learning Platform

Moodle is a platform designed for universal learning to support pedagogical interactions and educational activities. The information technology (IT) administrator uses standard authentication methods for students logging into the Moodle platform. The need for two-factor authentication has grown as institutions, governments, and individuals realize that passwords are not secure enough to protect user accounts in their current technical format. The classic connection methods have vulnerabilities, and account passwords are easy to crack. Analyzing these aspects, the goal is to create a new safe and reliable alternative to the traditional authentication methods in e-learning platforms. The proposed solution introduces a new authentication factor using digital certificates stored on physical devices or the cloud to address the evolving authentication and security challenges effectively. The absence of this authentication within the Moodle ecosystem has imparted a sense of urgency for its implementation. With the innovative authentication scheme, the users have gained confidence, are satisfied with the new solution, and have not reported security breaches. The result is increased security, data protection, and better account management.

Cybersecurity Strategies for Safeguarding Customer’s Data and Preventing Financial Fraud in the United States Financial Sectors

As the financial sectors in the United States deal with expanding cyberthreats and a rising danger of financial crime, cybersecurity has become a top priority. This paper examines the crucial cybersecurity techniques used by financial institutions to protect client information and counter the growing risk of financial fraud. It proves that understanding common fraud tactics used to defraud financial institutions and customers, putting fraud detection and prevention techniques like anomaly detection and machine learning into practice, and using transaction monitoring and anti-money laundering tactics to spot and stop fraudulent activity are all necessary for preventing financial fraud. The paper begins by reviewing the common cyber dangers affecting the financial industry and the strategies used by cybercriminals to circumvent security precautions and take advantage of weaknesses. After looking at potential risks, the paper highlights the importance of proactive cybersecurity measures and risk mitigation techniques. It highlights crucial components of cybersecurity frameworks, including strong data encryption, multifactor authentication, intrusion detection systems, and ongoing security monitoring. This paper also emphasizes the value of educating and training financial institution staff members to increase cybersecurity resilience. It underlines the significance of building a strong security culture, educating personnel about potential dangers, and encouraging responsible management of client data. The study also explores the advantages of financial organizations working together and exchanging threat knowledge. It examines industry alliances, information-sharing platforms, and public-private partnerships as crucial methods for group protection against cyber threats. This paper highlighted the significance of artificial intelligence and machine learning in cybersecurity domain. It demonstrates how these technologies improve cybersecurity systems' capabilities by spotting irregularities and potential attacks. It emphasizes the significance of taking a proactive and dynamic strategy to securing client information and maintaining faith in the United States’ financial sectors. Overall, this paper provides a thorough overview of cybersecurity tactics crucial for protecting consumer data and avoiding financial fraud in the financial sectors across the United States. By taking a vigilant, team-based, and technology-driven strategy, financial institutions may strengthen their cyber defenses, protect the data of their clients, and defend the integrity of the financial system.

Lightweight blockchain-assisted intrusion detection system in energy efficient MANETs

This paper focuses on achieving high-level security in Mobile Adhoc Networks (MANET) by incorporating Blockchain technology-based Intrusion Detection systems (IDS). The existing works on MANET security focus on either security prevention or detection. Thus, the security level attained by the prior works is unable to cope with the increasing attacks. To resolve this main issue, this research paper introduces Lightweight Blockchain assisted Intrusion Detection System (LB-IDS) which jointly prevents and detects the attacks held on mobile networks. Initially, the network nodes are authenticated by a lightweight Blockchain-based Multi-Factor Authentication (LBMFA) scheme. This procedure prevents the malicious nodes entry to the network. Then, data packets are transmitted through the optimal route which is selected by Multi-Objective Strawberry Optimization (MOSO) algorithm. The collected data packets are fed into IDS which classifies the data into normal and malicious packets. For IDS, we proposed Deep Q-Learning (DQL) algorithm which takes actions by learning the environment. As the mitigation step, the Blockchain is updated with the trust value according to the data packet classification. For such continuous monitoring, K-Mode Clustering (KMC) algorithm is proposed. On the whole, the proposed work improves the network security in MANET through Prevention, Detection, and Mitigation. The results of the presented work attains better security level, packet delivery ratio (PDR), energy efficiency, delay, and detection accuracy.

Development of an electronic burns register: Digitisation of routinely collected hospital data for global burns surveillance

IntroductionBurn registers provide important data that can track injury trends and evaluate services. Burn registers are concentrated in high-income countries, but most burn injuries occur in low- and middle-income countries where surveillance data are limited. Injury surveillance guidance recommends utilisation of existing routinely collected data where data quality is adequate, but there is a lack of guidance on how to achieve this. Our aim was to develop a rigorous and reproducible method to establish an electronic burn register from existing routinely collected data that can be implemented in low resource settings. MethodsData quality of handwritten routinely collected records (register books) from a tertiary government hospital burn unit in Mysore, India was assessed prior to digitisation. Process mapping was conducted for burn patient presentations. Register and casualty records were compared to assess the case ascertainment rate. Register books from February 2016 to February 2022 were scanned and anonymised. Scans were quality checked and stored securely. An online data entry form was developed. All data underwent double verification. ResultsProcess mapping suggested data were reliable, and case ascertainment was 95%. 1930 presentations were recorded in the registers, representing 0.84% of hospital all-cause admissions. 388 pages were scanned with 4.4% requiring rescanning due to quality problems. Two-step verification estimated there to be errors remaining in 0.06% of fields following data entry. ConclusionWe have described, using the example of a newly established electronic register in India, methods to assess the suitability and reliability of existing routinely collected data for surveillance purposes, to digitise handwritten data, and to quantify error during the digitisation process. The methods are likely to be of particular interest to burn units in countries with no active national burns register. We strongly recommend mobilisation of resources for digitisation of existing high quality routinely collected data as an important step towards developing burn surveillance systems in low resource settings.

Keyless Security

This research paper introduces a novel approach to improve security and access control in smart door lock systems. The proposed system incorporates multi-factor authentication, combining a numerical keypad, mobile app, and RFID sensor. Each authentication method is associated with a specific lock, offering differentiated access control. Notably, the system requires the simultaneous use of the mobile app and RFID sensor to unlock a designated lock, adding an extra layer of security. To assess the system's effectiveness, a comprehensive study was conducted, considering security, usability, and user satisfaction. The study involved simulated attacks, user surveys, and usability tests, with data analysis providing insights into the system's resilience and user acceptance. This research contributes to the field of smart door lock systems by offering an innovative approach to enhance security through multi-factor authentication. The findings provide valuable insights for designing advanced access control mechanisms, empowering users with increased confidence in their security measures while maintaining a user-friendly experience.

A Formal Verification of a Reputation Multi-Factor Authentication Mechanism for Constrained Devices and Low-Power Wide-Area Network Using Temporal Logic.

There are many security challenges in IoT, especially related to the authentication of restricted devices in long-distance and low-throughput networks. Problems such as impersonation, privacy issues, and excessive battery usage are some of the existing problems evaluated through the threat modeling of this work. A formal assessment of security solutions for their compliance in addressing such threats is desirable. Although several works address the verification of security protocols, verifying the security of components and their non-locking has been little explored. This work proposes to analyze the design-time security of the components of a multi-factor authentication mechanism with a reputation regarding security requirements that go beyond encryption or secrecy in data transmission. As a result, it was observed through temporal logic that the mechanism is deadlock-free and meets the requirements established in this work. Although it is not a work aimed at modeling the security mechanism, this document provides the necessary details for a better understanding of the mechanism and, consequently, the process of formal verification of its security properties.

Secure two-factor mutual authentication scheme using shared image in medical healthcare environment

The cloud healthcare system has become the essential online service during the COVID-19 pandemic. In this type of system, the authorized user may login to a distant server to acquire the service and resources they demand, we need full security procedures that cover criteria such as authentication, privacy, integrity, and availability. The journey of security for any healthcare system starts with the authentication of users based on their privileges. Traditional user authentication mechanisms, such as password and personal identification number (PIN) typing, are vulnerable to malicious attacks like on/offline, insider, replay, guessing, and shoulder surfing. To address these issues, we proposed a secure authentication scheme that uses the authenticated delegating mechanism based on two factors: a one-time password and generating a secure variable vector from a legible user's digital image to enable the permission of a user through the back-end database of a cloud server. The proposed mutual authentication can protect the information against well-known attacks, ensure the user's privacy, and key management. Moreover, comparisons with existing schemes show that the proposed scheme supplies more privacy, security metrics, and resistance to attacks than the others while being more efficient in computation and communication costs.

Secure two-factor mutual authentication scheme using shared image in medical healthcare environment

The cloud healthcare system has become the essential online service during the COVID-19 pandemic. In this type of system, the authorized user may login to a distant server to acquire the service and resources they demand, we need full security procedures that cover criteria such as authentication, privacy, integrity, and availability. The journey of security for any healthcare system starts with the authentication of users based on their privileges. Traditional user authentication mechanisms, such as password and personal identification number (PIN) typing, are vulnerable to malicious attacks like on/offline, insider, replay, guessing, and shoulder surfing. To address these issues, we proposed a secure authentication scheme that uses the authenticated delegating mechanism based on two factors: a one-time password and generating a secure variable vector from a legible user's digital image to enable the permission of a user through the back-end database of a cloud server. The proposed mutual authentication can protect the information against well-known attacks, ensure the user's privacy, and key management. Moreover, comparisons with existing schemes show that the proposed scheme supplies more privacy, security metrics, and resistance to attacks than the others while being more efficient in computation and communication costs.

Toward IoT Node Authentication Mechanism in Next Generation Networks

Although the next generation networks (5G-NGNs) provide a flexible infrastructure to support latency-sensitive and bandwidth-hungry mission-critical Internet of Things (IoT) applications, however, the 5G-IoT integration in NGNs has increased the threat surface. Unfortunately, IoT devices are resource constrained, and the traditional Intrusion Detection Systems (IDS) approaches based on cryptography are not effective on 5G-IoT ecosystems. In this paper, we propose an effective 5GIoT node authentication approach that leverages unique RF (Radio Frequency) fingerprinting data to train the Deep learning model to detect legitimate and non-legitimate IoT nodes. Our approach is based on Mahalanobis Distance theory and Chisquare distribution theories. The proposed approach achieves a higher detection accuracy (99.35%) as well as lower training time compared to other existing approaches which is a key benefit of our approach in NGNs. The experiments are conducted using ETSI-Open Source NFV Management and Orchestration (OSM-MANO) platform on AWS (Amazon Web Services) cloud platform to verify how the proposed approach would fit in reallife scenarios. The method can be used as a standalone security system or as a part of multi-factor authentication.

Analysis of Distinguishable Security between the One-Time Password Extraction Function Family and Random Function Family

A one-time password is a security system that uses a password that is only used once for authentication, and it is commonly used in multi-factor authentication systems. The process of generating an OTP is very similar to generating pseudorandom sequences in cryptography. However, since only a part of the bit string is used in OTP, an algorithm is needed to extract that part. In addition, the OTP process also includes converting the value of the bit string value into decimal form for human perception. This paper focuses on analyzing the extraction function, which is the step before the hexadecimal is reprocessed into the decimal form. We analyze a function family, which includes functions used in the process of extracting a bit string in terms of distinguishable security. As a result, we conclude that the OTP extraction function family is vulnerable in terms of distinguishable security compared to the random function family.

Siamese Neural Network for Keystroke Dynamics-Based Authentication on Partial Passwords.

The paper addresses issues concerning secure authentication in computer systems. We focus on multi-factor authentication methods using two or more independent mechanisms to identify a user. User-specific behavioral biometrics is widely used to increase login security. The usage of behavioral biometrics can support verification without bothering the user with a requirement of an additional interaction. Our research aimed to check whether using information about how partial passwords are typed is possible to strengthen user authentication security. The partial password is a query of a subset of characters from a full password. The use of partial passwords makes it difficult for attackers who can observe password entry to acquire sensitive information. In this paper, we use a Siamese neural network and n-shot classification using past recent logins to verify user identity based on keystroke dynamics obtained from the static text. The experimental results on real data demonstrate that keystroke dynamics authentication can be successfully used for partial password typing patterns. Our method can support the basic authentication process and increase users' confidence.

Design of a System for the Protection of Cardiac Data

The recording, processing, analysis and storage of cardiac data is an essential step in achieving better care for the cardiac health status of patients. An important aspect in the processing and access to this type of data is the ability to reliably protect it from unauthorized access. The article shows an automated system for registration and mathematical analysis of cardiac data and methods for their protection. Information protection is achieved by implementing two-factor authentication. The characteristic of two-factor authentication is that access to the system takes place in two stages: entering a password as the first step and a code/key as the second. In this way, for protection, unauthorized access to the patient 39 file, including personal information and results of cardiac tests, is prevented.

Securing Group Patient Communication in 6G-Aided Dynamic Ubiquitous Healthcare with Real-Time Mobile DNA Sequencing.

(1) Background: With an advanced technique, third-generation sequencing (TGS) provides services with long deoxyribonucleic acid (DNA) reads and super short sequencing time. It enables onsite mobile DNA sequencing solutions for enabling ubiquitous healthcare (U-healthcare) services with modern mobile technology and smart entities in the internet of living things (IoLT). Due to some strict requirements, 6G technology can efficiently facilitate communications in a truly intelligent U-healthcare IoLT system. (2) Research problems: conventional single user-server architecture is not able to enable group conversations where "multiple patients-server" communication or "patient-patient" communication in the group is required. The communications are carried out via the open Internet, which is not a trusted channel. Since heath data and medical information are very sensitive, security and privacy concerns in the communication systems have become extremely important. (3) Purpose: the author aims to propose a dynamic group-based patient-authenticated key distribution protocol for 6G-aided U-healthcare services enabled by mobile DNA sequencing. In the protocol, an authenticated common session key is distributed by the server to the patients. Using the key, patients in a healthcare group are allowed to securely connect with the service provider or with each other for specific purposes of communication. (4) Results: the group key distribution process is protected by a secure three-factor authentication mechanism along with an efficient sequencing-device-based single sign-on (SD-SSO) solution. Based on traceable information stored in the server database, the proposed approach can provide patient-centered services which are available on multiple mobile devices. Security robustness of the proposed protocol is proven by well-known verification tools and a detailed semantic discussion. Performance evaluation shows that the protocol provides more functionality and incurs a reasonable overhead in comparison with the existing works.

Reviewing the Usability of Web Authentication Procedures: Comparing the Current Procedures of 20 Websites

A sustainable online environment is essential to protecting businesses from abuse and data breaches. To protect sustainability, websites’ authentication procedures should continuously keep up with new technologies and the ways in which these technologies are used. Thus, a continuous assessment of these authentication procedures is required to ensure their usability. This research aimed to compare the status of the sign-up, sign-in, and password recovery processes on 20 websites. The researcher checked every website in a separate session and used the “think-aloud” technique while recording the screen to ensure accurate data analysis. Specific items were checked during every session to detect the similarities and differences between the tested websites in their authentication processes. The results led to valuable discussions and recommendations for improving authentication procedures. Some of these recommendations include best practices for better design of password rules, determining when two-factor authentication should be compulsory, and understanding how to improve password reset processes and keep accounts secure.

A Novel Authentication Method That Combines Honeytokens and Google Authenticator

Despite the rapid development of technology, computer systems still rely heavily on passwords for security, which can be problematic. Although multi-factor authentication has been introduced, it is not completely effective against more advanced attacks. To address this, this study proposes a new two-factor authentication method that uses honeytokens. Honeytokens and Google Authenticator are combined to create a stronger authentication process. The proposed approach aims to provide additional layers of security and protection to computer systems, increasing their overall security beyond what is currently provided by single-password or standard two-factor authentication methods. The key difference is that the proposed system resembles a two-factor authentication but, in reality, works like a multi-factor authentication system. Multi-factor authentication (MFA) is a security technique that verifies a user’s identity by requiring multiple credentials from distinct categories. These typically include knowledge factors (something the user knows, such as a password or PIN), possession factors (something the user has, such as a mobile phone or security token), and inherence factors (something the user is, such as a biometric characteristic like a fingerprint). This multi-tiered approach significantly enhances protection against potential attacks. We examined and evaluated our system’s robustness against various types of attacks. From the user’s side, the system is as friendly as a two-factor authentication method with an authenticator and is more secure.

Evaluation of Measures Taken by Telecommunication Companies in Preventing Social Engineering Attacks in Tanzania

This study aimed to evaluate the measures taken by telecommunication companies in preventing social engineering attacks in Tanzania. The study was guided by the deception theory, the researcher employed a descriptive research design and quantitative approach to conduct this study. Data was collected by using a questionnaire administered to the selected telecommunication companies in Tanzania. Furthermore, the obtained findings were as follows; most of the respondents who participated in this study are aware of social engineering and that they experienced social engineering. The study also revealed that there are common social engineering attacks experienced by the respondents such as business collaboration benefits, alleged wrong remittance of money, sim swaps, SMS phishing and fraudulent SMS from lost or stolen phones, password requisitions and links sharing. The findings of this study went further to reveal that social engineering has effects such as loss of sensitive data, financial loss, reputational damage, disruption of operations as well as legal and compliance issue. The general findings of this study show that most of the respondents said that there is a presence of security measures to prevent social engineering such as the provision of the awareness program, enabling the use of multifactor authentication, there is implementation of policies around social media usage, provision of regular software updates, regular review of security protocols, provision of well-known customer care services number. On the other hand, the study also revealed that telecommunication companies use the following ways to minimize social engineering attacks, provision of security awareness training for employees, implementing security policies and procedures, regularly reviewing and updating security protocols, detecting and responding to social engineering attacks, placing limits on the access each member has in the system, always require a username and password to be configured. On the strategies used to prevent social engineering, the finding of this study showed that telecommunication companies should ensure encrypting data, proper verification of emails or instructions sent to customers, ensure that even if hackers intercept communication they can’t access information contained within, use of SSL certificates from trusted authorities, incorporating phishing and malicious detection solutions into security stack. This study concludes that telecommunications ensure routine reviews of security standards, daily notifications for customers and other system users, and the availability of a well-known customer care services number. Due to the difficulties that information system users face, businesses have been using a variety of protection techniques to avoid social engineering, from putting up multifactor authentication for users' accounts to teaching employees how to spot suspect activity. Hence it is recommended that it is necessary to deploy mechanisms like machine learning-based ways to defend against social engineering-based assaults since cybercriminals exploit human activities to breach security as well as using the security features on messages (filter unknown senders) and calls (silence unknown callers).

Threshold Lattice-Based Signature Scheme for Authentication by Wearable Devices

This paper presents a new threshold signature scheme based on Damgaard’s work. The proposed scheme allows for changing the message signature threshold, thereby improving the flexibility of the original Damgaard scheme. This scheme can be applied as a user authentication system using wearable devices. Based on the hardness of lattice problems, this scheme is resistant to attacks on a quantum computer, which is an advantage over the currently used multi-factor authentication schemes. The scheme’s security relies on the computational complexity of the Module-LWE and Module-SIS problems, as well as the Shamir secret sharing scheme’s security.

Examination of Cybersecurity Technologies, Practices, Challenges, and Wish List in K-12 School Districts

With the growth in digital teaching and learning, there has been a sharp rise in the number of cybersecurity attacks on K-12 school networks. This has demonstrated a need for security technologies and cybersecurity education. This study examined security technologies used, effective security practices, challenges, concerns, and wish list of technology leaders in K-12 settings. Data collected from 23 district websites and from interviews with 12 district technology leaders were analyzed. Top security practices included cloud-based technologies, segregated network/V-LAN, two-factor authentication, limiting access, and use of Clever or Class Link. Top challenges included keeping users informed, lack of buy-in from staff and decision-makers, lack of expertise to implement modern best practices, and cost of resources. Top concerns included possible cyberattacks, leaked student data, and lack of user awareness. Finally, their wish list included technology personnel, access to Clever of Class Link, external system diagnostic checks, professional development for staff, and replacing aging infrastructure. The findings have implications for K-12 administrators, technology leaders, and teachers.

Privacy-Preserving Three-Factor Authentication Protocol for Wireless Sensor Networks Deployed in Agricultural Field

The agriculture is the backbone of economic system, and it plays an essential part in the survival of a nation’s prosperity. In addition to providing raw materials and food, it also offers numerous employment opportunities. Consequently, agriculture necessitates modern technology to increase productivity. In these circumstances, Wireless Sensor Networks (WSNs) are used to detect climatic parameters like light, humidity, carbon dioxide, acidity, soil moisture, and temperature in an agricultural field. However, the research that is being done at the moment is unable to circumvent the issue that safety and effectiveness cannot coexist. Several studies employ time-consuming cryptographic security structures, whereas the majority of lightweight systems are designed without reviewing certain security aspects like resistance to ephemeral secret leakage (ESL) attacks, perfect forward secrecy, and so on. According to our opinion, this issue may be overcome through the use of lightweight cryptographic primitives, paying particular attention to protocol weaknesses, and keeping in mind the ever-changing security needs of individuals. We present an extensive lightweight three-factor authentication protocol with diverse security criteria, along with the adaptive privacy preservation, that is suited for user-friendly situation in the WSN enviroment. This is accomplished by removing all extraneous cryptographic structures. It has been illustrated that proposed protocol is much better in terms of the privacy and security aspects via the usage of security aspects, proof of the real-or-random (ROR) model, protocols of internet security, and applications that are subjected to experimental validation utilizing automated validation. and comparison with other protocols’ security aspects. The performance analysis shows how superior our proposed protocol is to other competing protocols in terms of communication and computational overheads, with respective efficiencies of 53% and 39%. Moreover, using the ROR model reveals that this study has benefits in performance compared with other competing research.