성균관대학교 · Computer Science
나와브 무하마드 파시크 쿠레시 교수의 연구실은 인공지능 기반의 스마트 헬스케어 및 미래 통신 네트워크의 보안과 안정성 확보를 핵심으로 합니다. 특히 의료사물인터넷(IoMT), 6G 통신 기술, 드론 기반 물리계층 보안, 스마트그리드의 지능형 제어 등에서 AI와 신뢰성 있는 네트워크 기반 기술을 융합한 연구를 수행하고 있습니다. 기존 보안 기법의 한계를 넘어 양자 컴퓨팅에 대비한 신보안 기반 기술 개발도 주요 과제입니다. 특히 실시간 데이터 처리와 저지연 통신을 요구하는 임상 및 산업 응용 분야에 특화된 솔루션 개발에 역량을 집중하고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
With the advancement in the Internet of Medical Things (IoMT) infrastructure, network security issues have become a serious concern for hospitals and medical facilities. For this, a variety of customized network security tools and frameworks are used to distract several generalized attacks such as botnet-based distributed denial of services attacks (DDoS) and zero-day network attacks. Thus, it becomes difficult to operate routine IoMT services and tasks in between the under-attack scenario. This
The Internet of Medical Things (IoMT) facilitates patients with all-time-connected medical devices through cost-effective solutions and a feeling of comfort with round-the-clock hospital support. The patients who cannot visit hospitals for routine checkups prefer the usage of IoMT devices. The healthcare facilities also rely on the real-time statistics of IoMT machines and diagnose problems and their solutions within a small interval of time. This could only be possible when a robust convergence
5G has been launched in a few countries of the world, so now all focus shifted towards the development of future 6G networks. 5G has connected all aspects of society. Ubiquitous connectivity has opened the doors for more data sharing. Although 5G is providing low latency, higher data rates, and high-speed yet there are some security-related vulnerabilities. Those security issues need to be mitigated for securing 6G networks from existing challenges. Classical cryptography will not remain enough
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Unmanned Aerial Vehicles (UAVs) will be essential to support mission-critical applications of Ultra Reliable Low Latency Communication (URLLC) in futuristic Sixth-Generation (6G) networks. However, several security vulnerabilities and attacks have plagued previous generations of communication systems; thus, physical layer security, especially against eavesdroppers, is vital, especially for upcoming 6G networks. In this regard, UAVs have appeared as a winning candidate to mitigate security risks.
The fifth-generation mobile network (5G) supports Internet of Things (IoT) devices and processes large-scale data volumes through mobile devices. With this facility, we find a novel concept of Cooperative communication that manages massive channels accessibility, heterogeneous networks, complex interference environments and high energy consumption mediums through high signal coverage and capacity among mobile devices. The core of cooperative communication system relies on resource allocation tec
The tremendous growth in the internet of things (IoT) technology has provided great support for e-healthcare applications. The remote health monitoring of patients at home is gaining popularity with the increase in design of number of IoT enabled wearable devices. The secure and efficient health data retrieval during continuous uploading of huge data on network is a challenge. In addition, another challenge exists due to limited resources available with IoT device to proceed efficient data retri
Employee churn analytics is the process of assessing employee turnover rate and predicting churners in a corporate company. Due to the rapid requirement of experts in the industries, an employee may switch workplaces, and the company then has to look for a substitute with the training to deal with the tasks. This has become a bottleneck and the corporate sector suffers with additional cost overheads to restore the work routine in the organization. In order to solve this issue in a timely manner,
Big data analytics has simplified the processing complexity of extremely large data sets through ecosystems, such as Hadoop, MapR, and Cloudera. Apache Hadoop is an open-source ecosystem that manages large data sets in a distributed environment. MapReduce is a programming model that processes massive amount of unstructured data sets over Hadoop cluster. Recently, Hadoop enhances its homogeneous storage function to heterogeneous storage and stores data sets into multiple storage media, i.e., SSD,