Mubashar Iqbal

Asifullah Khan, Aimen Wadood, Mubashar Iqbal et al.

Ransomware has become one of the most serious cybersecurity threats causing major financial losses and operational disruptions worldwide.Traditional detection methods such as static analysis, heuristic scanning and behavioral analysis often fall short when used alone. To address these limitations, this paper presents multimodal multi agent ransomware analysis framework designed for ransomware classification. Proposed multimodal multiagent architecture combines information from static, dynamic and network sources. Each data type is handled by specialized agent that uses auto encoder based feature extraction. These representations are then integrated through a fusion agent. After that fused representation are used by transformer based classifier. It identifies the specific ransomware family. The agents interact through an interagent feedback mechanism that iteratively refines feature representations by suppressing low confidence information. The framework was evaluated on large scale datasets containing thousands of ransomware and benign samples. Multiple experiments were conducted on ransomware dataset. It outperforms single modality and nonadaptive fusion baseline achieving improvement of up to 0.936 in Macro-F1 for family classification and reducing calibration error. Over 100 epochs, the agentic feedback loop displays a stable monotonic convergence leading to over +0.75 absolute improvement in terms of agent quality and a final composite score of around 0.88 without fine tuning of the language models. Zeroday ransomware detection remains family dependent on polymorphism and modality disruptions. Confidence aware abstention enables reliable real world deployment by favoring conservativeand trustworthy decisions over forced classification. The findings indicate that proposed approach provides a practical andeffective path toward improving real world ransomware defense systems.

Mubashar Iqbal, Raimundas Matulevicius

Although the blockchain-based applications are considered to be less vulnerable due to the nature of the distributed ledger, they did not become the silver bullet with respect to securing the information against different security risks. In this paper, we present a literature review on the security risks that can be mitigated by introducing the blockchain technology, and on the security risks that are identified in the blockchain-based applications. In addition, we highlight the application and technology domains where these security risks are observed. The results of this study could be seen as a preliminary checklist of security risks when implementing blockchain-based applications.

Mubashar Iqbal

Recently a library of design patterns for designing distributed user interfaces (DUIs) was created to help researchers and designers to create user interfaces and to provide an overview of solutions to common DUIs design problems without requiring a significant amount of time to be spent on reading domain-specific literature and exploring existing DUIs implementations. The current version of the DUI design patterns library need to be assessed because a lot of design patterns are overlapping each other and their relationships are not clear enough to effectively find the most relevant design pattern for solving particular design problem, so the purpose of this thesis is to mature the DUI design patterns knowledge field by removing the duplicate design patterns, their description and to create a taxonomy where each design pattern should be organised in a way that will reduce redundancy, possibly leading to grouping or eventually merging similar patterns and allow to navigate to related patterns. To achieve the defined goals, the first target was to investigate the possible overlaps among design patterns and their relevancy with each other, in order to get these insights natural language processing tool was built for extracting and analysing each design pattern research paper to find potential codes. Later in this study thematic analysis was done with domain experts to get themes, their description and higher level categories from generated codes to organize all related design patterns in a clear hierarchy. The outcomes of this thesis included the clarification of the relationships among design patterns by creating a taxonomy, clarified the description of individual design pattern, overlaps and duplicate design patterns were removed and merged similar design patterns.