The continuous advancements of blockchain applications impose constant improvements on their technical features. Particularly immutability, a highly secure blockchain attribute forbidding unauthorized or illicit data editing or deletion, which functions as crucial blockchain security. Nonetheless, the security function is currently being challenged due to improper data stored, such as child pornography, copyright violation, and lately the enaction of the “Right to be Forgotten (RtbF)” principle disseminated by the General Data Protection Regulation (GDPR), where it requires blockchain data to be redacted to suit current applications’ urgent demands, and even compliance with the regulation is a challenge and an unfeasible practice for various blockchain technology providers owing to the immutability characteristic. To overcome this challenge, mutable blockchain is highly demanded to solve previously mentioned issues, where controlled and supervised amendments to certain content within constrained privileges granted are suggested by several researchers through numerous blockchain redaction mechanisms using chameleon and non-chameleon hashing function approaches, and methods were proposed to achieve reasonable policies while ensuring high blockchain security levels. Accordingly, the current study seeks to thoroughly define redaction implementation challenges and security properties criteria. The analysis performed has mapped these criteria with chameleon-based research methodologies, technical approaches, and the latest cryptographic techniques implemented to resolve the challenge posed by the policy in which comparisons paved current open issues, leading to shaping future research directions in the scoped field.

The proliferation of Distributed Denial of Service (DDoS) attacks poses a significant threat to network accessibility and performance. Traditional feature selection methods struggle with the complexity of network traffic data, leading to poor detection performance. To address this issue, a Genetic Algorithm Wrapper Feature Selection (GAWFS) is proposed, integrating Chi-squared and Genetic Algorithm (GA) approaches with a correlation method to select the most correlated features. GAWFS effectively reduces feature dimensions, eliminates redundancy, and identifies crucial and correlated features for classification. Detection accuracy is further improved by employing a stacking ensemble model, combining Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM) as base models, with Random Forest (RF) as the metamodel. The proposed classifier achieves impressive accuracies of 99.86% for training data and 98.89% for test data, representing improvements of approximately 5% and 40%, respectively, over previous studies. The training time was also reduced to 2,593 s, a substantial improvement of approximately 29.92%. Validation on various benchmark datasets confirmed the efficacy of the proposed approach, underscoring the importance of the enhanced feature selection method and the stacking ensemble model against DDoS attacks.

Mozilla Corporation has recently released a Linux-based open source operating system, namely Firefox OS. The arrival of this Firefox OS has created new challenges, concentrations and opportunities for digital investigators. Currently, Firefox OS is still not fully supported by most of the existing mobile forensic tools. Even when the phone is detected as Android, only pictures from removable card was able to be captured. Furthermore, the internal data acquisition is still not working. Therefore, there are very huge opportunities to explore the Firefox OS on every stages of mobile forensic procedures. This paper will present an approach for mobile forensic data acquisition in a forensically sound manner from a Firefox OS running device. This approach will largely use the UNIX dd command to create a forensic image from the Firefox OS running device.

The advancement of smartphone technology has attracted many companies in developing mobile operating system. Mozilla Corporation recently released Linux-based open source operating system, named Firefox OS. The emergence of Firefox OS has created new challenges, concentrations and opportunities for digital investigators. In general, Firefox OS is designed to allow smartphones to communicate directly with HTML5 applications using JavaScript and newly introduced WebAPI. However, the used of JavaScript in HTML5 applications and solely no OS restriction might lead to security issues and potential exploits. Therefore, forensic analysis for Firefox OS is urgently needed in order to investigate any criminal intentions. This paper will present an approach and methodology in forensically sound manner for Firefox OS.