Transparent authentication methodology in electronic education

In the context of on-line assessment in e-learning, a problem arises when a student taking an exam may wish to cheat by handing over personal credentials to someone else to take their place in an exam, Another problem is that there is no method for signing digital content as it is being produced in a computerized environment. Our proposed solution is to digitally sign the participant’s work by embedding voice samples in the transcript paper at regular intervals. In this investigation, we have demonstrated that a transparent stenographic methodology will provide an innovative and practical solution for achieving continuous authentication in an online educational environment by successful insertion and extraction of audio digital signatures

Approaches to maintaining provenance throughout the additive manufacturing process

The development of 3D printers has resulted in significant Intellectual Property Right issues. This work presents a model for signing printable 3D objects. The paper initially reviews the security principles of signing of objects in both digital or physical form, and the metrics for assessing signatures. 3D designs are not just a file, but actual physical objects and should be treated identically, to digital documents that have associated intellectual property rights and copyright protection. In this paper we propose a signing methodology intended to resolve issues with the adaptation of rapid prototyping and 3D printing by users both in engineering and the humanities. The proposed digital signing methodology is based on physical signing principles that follow archival principles to maintain accurate records. The new model allows the transition of provenance between digital and physical form

Provenance framework for additive manufacturing

Advances in additive manufacturing have had a disruptive influence to the conventional manufacturing process by bringing manufacturing to the hands of the customer and shortening the supply chain. The customer can customise and manufacture any 3D object using additive manufacturing without leaving their office, lab or home. This paradigm shift in manufacturing raised concerns about the intellectual property rights of 3D objects. At the moment additive manufacturing has allowed owners of 3D printers to fabricate any 3D object with no accountability and no provenance measures for the original authors of the 3D objects. This is a problem because licensing usually allows for limited use and provenance reflects the value of the 3D object. This work presents a framework for provenance of 3D objects that investigates the transition of security properties from digital 3D objects to 3D printed objects because of the absence of such mechanisms. A wholistic security view of additive manufacturing process by presenting a additive manufacturing security reference model and a tool to benchmark security of additive manufacturing. This framework is intended to facilitate for the industry with the adaptation of 3D printing by engineers, designers and other types of users. The proposed framework is based on digital security measures, physical signing principles and following archival principles to maintain accurate records because of the nature of the transition of properties from digital to analogue records. The proposed framework has the potential of pushing 3D printing adaptation thought sharing and exchange of 3D objects by public and academic domain by using our security framework as enabling technology.The security reference model for additive manufacturing is intended to provide security by design for any additive manufacturing process, this reference model also covers the cyber to physical security aspect of additive manufacturing.The benchmarking tool provides a security measure that is flexible and is tailored fit assessment process to any additive manufacturing workflow, it give freedom to security practitioners to fit it to any organisation structure to report on the organisation state of security

Preventing Document Leakage through Active Document

Electronic documents inside any enterprise environment are assets that add to the enterprise’s capital in intellectual property such as design patents or customer information, securing, these assets is a priority requirement inany security system design. The security of these documentssuffers when they have migrated outside the organization security system, as there is not always a way to extend the enterprise security policy to limit/prevent access to those assets. This paper presents the challenges faced when preventing document leakage. We propose active document as a measure to control/limit access when electronic document are outside its domain

The effectiveness of transformer-based models for BEC attack detection

Business Email Compromise (BEC) attacks are a significant threat to organizations, with attackers using various tactics to acquire sensitive information and cause financial damage to target firms. These attacks are difficult to detect using existing email security systems, as approximately 60% of BEC attacks do not include explicit indicators such as attachments and links. Even state-of-the-art solutions using Natural Language Processing (NLP) rely heavily on such explicit indicators. This study proposes a transformer-based BEC detection method that can capture linguistic properties of emails so that could reduce the reliance on explicit indicators. Our method of combining BERT and BiLSTM offers the advantage of capturing both global context and local interdependence, resulting in a comprehensive and nuanced understanding of email text. In our experiment, the proposed method outperforms the state-of-the-art solutions, achieving a 0.99% accuracy and this highlights the potential of transformer-based models in detecting BEC attacks.</p

Transparent authentication in e-learning

In the context of on-line assessment in e-learning a problem arises is that someone taking an exam may wish to cheat by handing over personal credentials to someone to take their place in an exam. This differs from authenticating for on-line banking where it is in the user interest to ensure safe and correct authentication. Our proposed solution is to digitally sign the student work by embedding voice samples in the exam paper at regular intervals. In this investigation we have demonstrated that transparent steganography can provide an effective mechanism for achieving such a good goa

Malicious activity detection using smart contracts in IoT.

Internet of Things (IoT) is a unique element in the realm of Cybersecurity. It constitutes countless applications, including defense, health, agriculture, finance, amongst other industries. The majority of existing studies focus on various developments of IoT products and services essential to our day-to-day activities, with little emphasis on the security of developed systems. This has led to the proliferation of IoT solutions acquired through rapid development and overlooking the need for a structured security framework during the systems’ development stages.IoT security capability can be improved by using complementary technologies. This paper explores applying Risk-Based Access Control Model using Blockchain to control access to IoT devices. Although current access control models provide efficient security measures to control who can access the system resources, there is no way to detect and prevent malicious attacks after granting access. The proposed solution utilizes smart contracts under the Hyperledger Fabric (HLF) Blockchain Framework to create access permissions and measure the security risks associated with any event in the IoT system and create access permissions to determine what processes may be performed. This will allow the detection of any malicious activity at the early stages of the attack and grant or deny access based on the risk associated with any activity

Anomaly detection system: towards a framework for enterprise log management of security services

In recent years, enterprise log management systems have been widely used by organizations. Several companies such as (IBM, MacAfee and Splunk etc.) have brought their own log management solutions to the market. However, the problem is that these systems often require proprietary hardware and do not involve web usage mining to analyze the log data. The purpose of this paper is to investigate an approach towards a framework for managing security logs in enterprise organizations called of the anomaly detection system (ADS), built to detect anomalous behavior inside computer networks that is free from hardware constraints and benefits from web usage mining to extract useful information from the log files

Maintaining provenance throughout the additive manufacturing process

The introduction of affordable 3D printers made a significant impact on personal fabrication artistic designs that may or may not be covered by Intellectual Property Rights (IPR). Therefore copyright holders or creators of 3D objects have a legitimate concern about sharing 3D objects. This work presents a model for signing printable 3D objects to address the IPR issue. 3D files contain object geometry plus a number of attributes however it lacks security attributes when it comes to provenance procedures as it uses inherited security protocols for digital documents, digital media that are not intended for 3D objects. This paper reviews security principles of signing of objects in digital form, and the metrics for assessing digital signatures, then illustrate the shortcoming of digital signing principles and current provenance procedures for 3D printed object from digital sources.. The proposed digital signing methodology aims to transition all the meta data associated with the digital 3D object to the physical 3D printed object The new model allows the transition of provenance between digital and physical form. At the same time it will follow archival principles to maintain accurate records and provide provenance

Identifying food fraud using blockchain

Cross-contamination, counterfeit ingredients, false packaging, and labelling are all issues that contribute to food fraud which is a major concern undermining the integrity of the food supply chain and consumers health. Therefore, there is a need for an on-demand traceable, transparent food supply chain. This is a universal problem and blockchain presents itself as a means to maintain traceable, transparent food supply. This paper presents an innovative consensus algorithm and simulates the usage of it to identify the precision and recall of fraudulent food detection. This protocol aims to solve the issue of malicious leader node selection in common voting-based consensus protocols while achieving efficiency. Thus, providing a single version of truth for foods in a long food supply chain, preventing information asymmetries