A selection from Stockholm University publication database

• Towards Security on Internet of Things

  2018. Kazi Masum Sadique, Rahim Rahmani, Paul Johannesson. Procedia Computer Science 141, 199-206

  Article

  The Internet of Things (IoT) paradigm refers to the network of physical objects or "things" embedded with electronics, software, sensors, and connectivity to enable objects to exchange data with servers, centralized systems, and/or other connected devices based on a variety of communication infrastructures. IoT data collected from different sensors, nodes and collectors are transferred to the cloud over the internet. IoT devices are used by consumers, healthcare, businesses as well as by the governments. It is being forecast that 31 billion IoT devices will be deployed all over the world by the year 2020. As the use of IoT devices is increasing every moment several IoT vulnerabilities are introduced. The results and analysis indicate that massive deployment of IoT with an integration of new technologies are introducing new security challenges in IoT paradigm. In this paper, IoT security challenges and open issues are discussed which provides a ground for future research.

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• Trust in Internet of Things

  2019. Kazi Masum Sadique, Rahim Rahmani, Paul Johannesson. 2018 International Conference on Innovation in Engineering and Technology (ICIET)

  Conference

  Current technology driven world is moving forward with massive implementation of smart objects. These smart objects or Internet of Things (IoT) nodes are involved in sensing of real time critical data from surroundings. Though these IoT nodes are involved in very specific task but their existence is very important for the complete system. Usually, in an IoT architecture, several heterogeneous nodes connect with a nearest gateway. The gateway itself connects with the world via Internet. IoT nodes need to flexible about connectivity as those may need to leave and join any gateway based on context (time, location etc.). To achieve flexibility, IoT components need a trust relationship between each other. In this paper, we have proposed a mechanism for integrating distributed trust management in IoT by using edge computing technology, considering the scalability and heterogeneous capability of IoT devices.

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• Identity Management in Internet of Things

  2020. Kazi Masum Sadique, Rahim Rahmani, Paul Johannesson. Proceedings of the 2nd International Conference on Communication, Devices and Computing, 495-504

  Conference

  Internet of things (IoT) network needs to accommodate billions of connected smart objects (things). Connected IoT objects should be able to communicate with each other. Objects should be able to travel between different networks regardless of their locations, network providers, and manufacturers. To allow transparent movement of IoT objects, it is very important to have a trust relationship between these objects. To establish trusted relationship, unique identity is one of the key properties for any IoT object. It will not be possible for the devices to freely move within the networks if we do not have a common identity solution. The use of software-defined networking (SDN) approach in IoT is increasing these days, due to its flexibility and easy adaptability with any network. In this paper, we have presented an SDN-based identity management system which will possibly solve the unique identity problem and increase trust in heterogeneous IoT network.

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• Fog Computing based Trust Solutions for Internet of Things (IoT)

  2020. Kazi Masum Sadique, Rahim Rahmani, Paul Johannesson. 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), 1-6

  Conference

  Scientific research is performed based on real life problems. Reproducibility of research result is one of the curtail criteria for any scientific research. Proper documentation about research methodology allows fellow researcher to reproduce the results and to further extend of the research findings. Fog computing-based solution enhances quality of IoT solutions by making a bridge between cloud layer and end devices of IoT paradigm. Also fog computing can also increase security and trust in IoT by processing data at the fog layer which is closer to the source of data where it is produced. But fog computing-based trust solutions for Internet of Things (IoT) is a new trend. Fog computing can be considered as engineering discipline. IoT itself covers many aspects of human life; we can call IoT as a social science research area. In this paper, authors have discussed about different scientific research approaches used in fog computing based trust management in IoT researches.

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• Layered Architecture for End-to-end Security, Trust, and Privacy for the Internet of Things

  2021. Kazi Masum Sadique, Paul Johannesson. Intelligent Computing and Innovation on Data Science, 289-298

  Conference

  The Internet of Things (IoT) paradigm consists of smart sensor objects and their related applications. All these intelligent sensors communicate and transfer data via the internet. Though communication between IoT devices and other network components is mostly performed over traditional Internet infrastructure, this process is still much more complex and different from a conventional client-server communication process. In general, both parties are authenticated and authorized via a centralized identity and authorization management server in a traditional client-server or peer-to-peer communication network architecture. But in an IoT infrastructure, the IoT devices, gateways, end-user applications need to be authenticated dynamically during or before the communication processes begin. Another issue in the communication process is secure communication between components of the IoT paradigm. Due to the heterogeneous behavior and dynamic communication between IoT devices, it is hard to define a standard way to secure communication between IoT infrastructure and cloud computing components. A new seven layers of IoT communication architecture is proposed to address the above-mentioned issues, where data communication and processing are done in a decentralized and distributed manner.

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• Enhancing Data Privacy in the Internet of Things (IoT) using Edge Computing

  2020. Kazi Masum Sadique, Rahim Rahmani Chianeh, Paul Johannesson. Trends in Computational Intelligence, Security and Internet of Things, 231-243

  Conference

  The vast deployment of the Internet of Things (IoT) is improving human life standards every day. These IoT applications are producing a huge amount of data from the environment where it is deployed. The collected data are mostly including end-user private data or industrial data which are transmit-ted over the internet to the cloud devices for storing, processing, and sharing with the connected applications. Recent IoT data privacy related researches are mostly focused on data privacy within a particular location of the network or at a particular device but none has pointed and listed all the places where the end-user or industrial data privacy risks exist. In this work, we have addressed both technical and management aspects for the enhancement of the privacy of IoT data. We have identified and listed the places where IoT data privacy risks exist, followed by our proposed model for data privacy enhancement in the inter-net of things (IoT) and listed ten suggestions for avoiding data privacy leakage and for IoT data privacy enhancement. The results of this work should be useful for both academic researchers and stakeholders from the industry while designing and implementing new IoT solutions for the enhancement of human society.

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• Dynamic and Decentralized Trust Management for the Internet of Things (IoT) Paradigm

  2021. Kazi Masum Sadique, Rahim Rahmani Chianeh, Paul Johannesson. Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020), 1017-1026

  Conference

  Trust is an invisible behavior of any entity. An entity could be a living being or a cyber-physical system. The Internet of Things (IoT) is a connected network of smart objects or things where trusted relationships are crucial. Trust in an entity can increase or decrease based on different parameters and properties of the specific entity. Trusted relationships can dynamically reach based on contextual data collected over time. The heterogeneous behavior of IoT devices makes trust measurement more difficult. The massive deployment of IoT devices and related innovative IoT applications leads to exploring new trust management frameworks for the IoT paradigm. Emerging IoT applications need to trust entities deployed by third-party providers. Innovative external IoT applications need to be dynamically trusted by the IoT devices and IoT gateways. Dynamic trust achievement is a complex process when an entity is new within the network. In this article, we have defined the trust management for IoT and discussed the need for trusted architecture for dynamic IoT infrastructure, and elaborated the requirements of trust management policies. We have also heightened the need for decentralized architecture for trust management for the Internet of Things (IoT). A new edge-centric multi-agent-based dynamic and decentralized trust management model is proposed and simulated to solve the aforementioned issues. The results of this work are useful for further research in the field of trust management for IoT. 

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• A Survey on 5G Architecture and Security Scopes in SDN and NFV

  2021. Jehan Hasneen, Kazi Masum Sadique. Applied Information Processing Systems, 447-460

  Conference

  5G is an emerging technology. 5G is not going to be an update to its predecessors. Researchers are intended to achieve a head-turning advancement in terms of all the way performances such as, data rates, network reliability, massive connectivity, mobility, energy efficiency, latency, secured channel, spectral efficiency etc. 5G is going to be an end-to-end system that will provide hyper-connectivity to its users. It is supposed to support roughly three use cases i.e. Enhanced Mobile Broadband (eMBB), Ultra Reliable and Low Latency Communication (URLLC), and massive Machine Type Communication (mMTC). All of these create convergence among wireless communication and computer networking that incorporates Software Driven Network (SDN), Network Functions Virtualization (NFV), Service Based Architecture (SBA), 5G new radio technologies (M-MIMO, mmWave, UDN, FD), massive IoT techniques. This hyper-convergence will introduce new trust and security threats and relevant threat management challenges. In this paper we tried to summarize on why and how 5G is evolved and what are the technology requirements for 5G revolution and steps adopted for technology change over to 5G. We focused on potential threats and challenges and their suggested mitigation techniques. A number of open issues are identified and probable future research directions in the very field are also discussed in this paper.

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Show all publications by Kazi Masum Sadique at Stockholm University