Mohammad Jabed Morshed Chowdhury

Sudad Abed, Nasser Sabar, Abdun Mahmood et al.

Decentralized Federated Learning (FL) removes reliance on centralized coordinators but remains vulnerable to model poisoning, unreliable validation, and high validation overhead. This paper introduces Proof of Contribution Quality (PoCQ), a blockchain-based consensus framework designed to secure decentralized FL through reputation-aware validation and aggregation. PoCQ evaluates client updates using cryptographic commitments and lightweight norm-based validation, enabling efficient detection of malicious contributions while limiting validation cost. A reputation-driven consensus mechanism dynamically adjusts the influence of participants based on their historical contribution quality, while the blockchain stores only compact audit metadata to preserve scalability. Extensive experiments under poisoning scenarios across three benchmark datasets demonstrate that PoCQ outperforms the strongest state-of-the-art methods, achieving accuracy gains of 34.1% on challenging medical datasets in highly non-iid settings and an 11% improvement in global average accuracy. In addition, PoCQ reduces validation time by 21.27% on average per round, highlighting its effectiveness in jointly enhancing robustness and efficiency for fully decentralized federated learning.

Ifteher Alom, Md Sadek Ferdous, Mohammad Jabed Morshed Chowdhury

Blockchain Technology is an emerging technology with the potential to disrupt a number of application domains. Though blockchain platforms like Bitcoin and Ethereum have seen immense success and acceptability, their nature of being public and anonymous make them unsuitable for many enterprise level use-cases. To address this issue, Linux Foundation has started an open source umbrella initiative, known as the Hyperledger Platforms. Under this initiative, a number of private blockchain platforms have been developed which can be used for different enterprise level applications. However, the scalability and performance of these private blockchains must be examined to understand their suitability for different use-cases. Recent researches and projects on performance benchmarking for private blockchain systems are very specific to use-cases and are generally tied to a blockchain platform. In this article, we presentBlockMeter, an application agnostic performance benchmarking framework for private blockchain platforms. This framework can be utilised to measure the key performance matrices of any application deployed on top of an external private blockchain application in real-time. In this article, we present the architecture of the framework and discuss its different implementation aspects. Then, to showcase the applicability of the framework, we use BlockMeter to evaluate the two most widely used Hyperledger platforms, Hyperledger Fabric and HyperledgerSawtooth, against a number of use-cases.

Gervais Hatungimana, Abdun Naser Mahmood, Mohammad Jabed Morshed Chowdhury

Most corporate workplace environments enforce policies and technical controls that limit the storage of sensitive data on client endpoints. Consequently, ransomware operators have evolved variants that expand their attack surface from local systems to network drives and shared storage resources. As traditional endpoint detection mechanisms focus primarily on local system behaviour, a compromised client can impact remote file servers, such as by encrypting shared data, without directly triggering behavioural changes on the servers themselves. In this paper, we propose a hybrid detection framework for detecting crypto-ransomware intrusion within integrated file server and client environments. The framework is based on a new technique referred to as Region of Interest (RoI) to analyse network traffic and extract Indicators of Compromise (IoCs). The IoC repository serves as an additional ruleset to enhance existing security tools such as EDRs and IDSs, while RoI-derived features are used to train an ML model to detect highly evasive variants. This study incorporates a broader set of ransomwares families and carefully selected benign behaviors based on domain expertise, ensuring coverage of common user actions that could interfere with ransomware detection. Beyond IoCs, which operate in a signature-based manner, our machine learning module achieves a detection precision of 99.64%, with a 0% false negative rate (FNR) and a minimal false positive rate (FPR). Furthermore, the proposed method enables early detection, identifying ransomware intrusions before significant damage occurs, achieving an accuracy of 99.44%.

Shirajus Salekin Nabil, Md. Sabbir Alam Pran, Ali Abrar Al Haque et al.

Covid-19 (SARS-CoV-2) has changed almost all the aspects of our living. Governments around the world have imposed lockdown to slow down the transmissions. In the meantime, researchers worked hard to find the vaccine. Fortunately, we have found the vaccine, in fact a good number of them. However, managing the testing and vaccination process of the total population is a mammoth job. There are multiple government and private sector organisations that are working together to ensure proper testing and vaccination. However, there is always delay or data silo problems in multi-organisational works. Therefore, streamlining this process is vital to improve the efficiency and save more lives. It is already proved that technology has a significant impact on the health sector, including blockchain. Blockchain provides a distributed system along with greater privacy, transparency and authenticity. In this article, we have presented a blockchain-based system that seamlessly integrates testing and vaccination system, allowing the system to be transparent. The instant verification of any tamper-proof result and a transparent and efficient vaccination system have been exhibited and implemented in the research. We have also implemented the system as "Digital Vaccine Passport" (DVP) and analysed its performance.

Munshi Saifuzzaman, Tajkia Nuri Ananna, Mohammad Jabed Morshed Chowdhury et al.

Wearable devices generate different types of physiological data about the individuals. These data can provide valuable insights for medical researchers and clinicians that cannot be availed through traditional measures. Researchers have historically relied on survey responses or observed behavior. Interestingly, physiological data can provide a richer amount of user cognition than that obtained from any other sources, including the user himself. Therefore, the inexpensive consumer-grade wearable devices have become a point of interest for the health researchers. In addition, they are also used in continuous remote health monitoring and sometimes by the insurance companies. However, the biggest concern for such kind of use cases is the privacy of the individuals. There are a few privacy mechanisms, such as abstraction and k-anonymity, are widely used in information systems. Recently, Differential Privacy (DP) has emerged as a proficient technique to publish privacy sensitive data, including data from wearable devices. In this paper, we have conducted a Systematic Literature Review (SLR) to identify, select and critically appraise researches in DP as well as to understand different techniques and exiting use of DP in wearable data publishing. Based on our study we have identified the limitations of proposed solutions and provided future directions.

Md. Saiful Islam Bhuiyan, Abdur Razzak, Md Sadek Ferdous et al.

A Chatbot is a popular platform to enable users to interact with a software or website to gather information or execute actions in an automated fashion. In recent years, chatbots are being used for executing financial transactions, however, there are a number of security issues, such as secure authentication, data integrity, system availability and transparency, that must be carefully handled for their wide-scale adoption. Recently, the blockchain technology, with a number of security advantages, has emerged as one of the foundational technologies with the potential to disrupt a number of application domains, particularly in the financial sector. In this paper, we forward the idea of integrating a chatbot with blockchain technology in the view to improve the security issues in financial chatbots. More specifically, we present BONIK, a blockchain empowered chatbot for financial transactions, and discuss its architecture and design choices. Furthermore, we explore the developed Proof-of-Concept (PoC), evaluate its performance, analyse how different security and privacy issues are mitigated using BONIK.

Md. Atik Shahriar, Faisal Haque Bappy, A. K. M. Fakhrul Hossain et al.

Blockchain technology has evolved through many changes and modifications, such as smart-contracts since its inception in 2008. The popularity of a blockchain system is due to the fact that it offers a significant security advantage over other traditional systems. However, there have been many attacks in various blockchain systems, exploiting different vulnerabilities and bugs, which caused a significant financial loss. Therefore, it is essential to understand how these attacks in blockchain occur, which vulnerabilities they exploit, and what threats they expose. Another concerning issue in this domain is the recent advancement in the quantum computing field, which imposes a significant threat to the security aspects of many existing secure systems, including blockchain, as they would invalidate many widely-used cryptographic algorithms. Thus, it is important to examine how quantum computing will affect these or other new attacks in the future. In this paper, we explore different vulnerabilities in current blockchain systems and analyse the threats that various theoretical and practical attacks in the blockchain expose. We then model those attacks using Petri nets concerning current systems and future quantum computers.

Md Sadek Ferdous, Mohammad Jabed Morshed Chowdhury, Kamanashis Biswas et al.

The popularity of smart cars is increasing around the world as they offer a wide range of services and conveniences.These smart cars are equipped with a variety of sensors generating a large amount of data, many of which are sensitive. Besides, there are multiple parties involved in a lifespan of a smart car ,such as manufacturers, car owners, government agencies, and third-party service providers who also produce data about the vehicle. In addition to managing and sharing data amongst these entities in a secure and privacy-friendly way which is a great challenge itself, there exists a trust deficit about some types of data as they remain under the custody of the car owner(e.g. satellite navigation and mileage data) and can easily be manipulated. In this paper, we propose a blockchain supported architecture enabling the owner of a smart car to create an immutable record of every data, called the auto biography of a car, generated within its lifespan. We also explain how the trust about this record is guaranteed by the immutability characteristic of the blockchain. Furthermore, the paper describes how the proposed architecture enables a secure and privacy-friendly sharing of smart car data between different parties in a secure yet privacy-friendly manner.

Mohammad Jabed Morshed Chowdhury, Narayan Ranjan Chakraborty

A CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is an automatic security mechanism used to determine whether the user is a human or a malicious computer program. It is a program that generates and grades tests that are human solvable, but intends to be beyond the capabilities of current computer programs. CAPTCHA should be designed to be very easy for humans but very hard for machines. Unfortunately, the existing CAPTCHA systems while trying to maximize the difficulty for automated programs to pass tests by increasing distortion or noise have consequently, made it also very difficult for potential users. To address the issue, this paper addresses an alternative form of CAPTCHA that provides a variety of questions from mathematical, logical and general problems which only human can understand and answer correctly in a given time. The proposed framework supports diversity in choosing the questions to be answered and a user-friendly framework to the users. A user-study is also conducted to judge the performance of the developed system with different background. The study shows the efficacy of the implemented system with a good level of user satisfaction over traditional CAPTCHA available today.