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Ibrahim Khalil

Other affiliations: University of Bern, NICTA
Bio: Ibrahim Khalil is an academic researcher from RMIT University. The author has contributed to research in topics: Cloud computing & Encryption. The author has an hindex of 34, co-authored 217 publications receiving 4571 citations. Previous affiliations of Ibrahim Khalil include University of Bern & NICTA.


Papers
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Journal ArticleDOI
TL;DR: Concepts and algorithms related to clustering, a concise survey of existing (clustering) algorithms as well as a comparison, both from a theoretical and an empirical perspective are introduced.
Abstract: Clustering algorithms have emerged as an alternative powerful meta-learning tool to accurately analyze the massive volume of data generated by modern applications. In particular, their main goal is to categorize data into clusters such that objects are grouped in the same cluster when they are similar according to specific metrics. There is a vast body of knowledge in the area of clustering and there has been attempts to analyze and categorize them for a larger number of applications. However, one of the major issues in using clustering algorithms for big data that causes confusion amongst practitioners is the lack of consensus in the definition of their properties as well as a lack of formal categorization. With the intention of alleviating these problems, this paper introduces concepts and algorithms related to clustering, a concise survey of existing (clustering) algorithms as well as providing a comparison, both from a theoretical and an empirical perspective. From a theoretical perspective, we developed a categorizing framework based on the main properties pointed out in previous studies. Empirically, we conducted extensive experiments where we compared the most representative algorithm from each of the categories using a large number of real (big) data sets. The effectiveness of the candidate clustering algorithms is measured through a number of internal and external validity metrics, stability, runtime, and scalability tests. In addition, we highlighted the set of clustering algorithms that are the best performing for big data.

833 citations

Journal ArticleDOI
TL;DR: A Hidden Markov Model based approach for detecting abnormalities in daily activities, a process of identifying irregularity in routine behaviours from statistical histories and an exponential smoothing technique to predict future changes in various vital signs are described.

170 citations

Journal ArticleDOI
TL;DR: A wavelet-based steganography technique has been introduced which combines encryption and scrambling technique to protect patient confidential data and it is found that the proposed technique provides high-security protection for patients data with low distortion and ECG data remain diagnosable after watermarking.
Abstract: With the growing number of aging population and a significant portion of that suffering from cardiac diseases, it is conceivable that remote ECG patient monitoring systems are expected to be widely used as point-of-care (PoC) applications in hospitals around the world. Therefore, huge amount of ECG signal collected by body sensor networks from remote patients at homes will be transmitted along with other physiological readings such as blood pressure, temperature, glucose level, etc., and diagnosed by those remote patient monitoring systems. It is utterly important that patient confidentiality is protected while data are being transmitted over the public network as well as when they are stored in hospital servers used by remote monitoring systems. In this paper, a wavelet-based steganography technique has been introduced which combines encryption and scrambling technique to protect patient confidential data. The proposed method allows ECG signal to hide its corresponding patient confidential data and other physiological information thus guaranteeing the integration between ECG and the rest. To evaluate the effectiveness of the proposed technique on the ECG signal, two distortion measurement metrics have been used: the percentage residual difference and the wavelet weighted PRD. It is found that the proposed technique provides high-security protection for patients data with low (less than 1%) distortion and ECG data remain diagnosable after watermarking (i.e., hiding patient confidential data) and as well as after watermarks (i.e., hidden data) are removed from the watermarked data.

162 citations

Journal ArticleDOI
01 Jun 2014
TL;DR: The proposed CoCaMAAL model seeks to address issues and implement a service-oriented architecture (SOA) for unified context generation by efficiently aggregating raw sensor data and the timely selection of appropriate services using a context management system (CMS).
Abstract: Research into ambient assisted living (AAL) strives to ease the daily lives of people with disabilities or chronic medical conditions. AAL systems typically consist of multitudes of sensors and embedded devices, generating large amounts of medical and ambient data. However, these biomedical sensors lack the processing power to perform key monitoring and data-aggregation tasks, necessitating data transmission and computation at central locations. The focus here is on the development of a scalable and context-aware framework and easing the flow between data collection and data processing. The resource-constrained nature of typical wearable body sensors is factored into our proposed model, with cloud computing features utilized to provide a real-time assisted-living service. With the myriad of distributed AAL systems at play, each with unique requirements and eccentricities, the challenge lies in the need to service these disparate systems with a middleware layer that is both coherent and flexible. There is significant complexity in the management of sensor data and the derivation of contextual information, as well as in the monitoring of user activities and in locating appropriate situational services. The proposed CoCaMAAL model seeks to address such issues and implement a service-oriented architecture (SOA) for unified context generation. This is done by efficiently aggregating raw sensor data and the timely selection of appropriate services using a context management system (CMS). With a unified model that includes patients, devices, and computational servers in a single virtual community, AAL services are enhanced. We have prototyped the proposed model and implemented some case studies to demonstrate its effectiveness.

150 citations

Journal ArticleDOI
TL;DR: This article introduces a framework named PriModChain that enforces privacy and trustworthiness on IIoT data by amalgamating differential privacy, federated ML, Ethereum blockchain, and smart contracts.
Abstract: Industrial Internet of Things (IIoT) is revolutionizing many leading industries such as energy, agriculture, mining, transportation, and healthcare. IIoT is a major driving force for Industry 4.0, which heavily utilizes machine learning (ML) to capitalize on the massive interconnection and large volumes of IIoT data. However, ML models that are trained on sensitive data tend to leak privacy to adversarial attacks, limiting its full potential in Industry 4.0. This article introduces a framework named PriModChain that enforces privacy and trustworthiness on IIoT data by amalgamating differential privacy, federated ML, Ethereum blockchain, and smart contracts. The feasibility of PriModChain in terms of privacy, security, reliability, safety, and resilience is evaluated using simulations developed in Python with socket programming on a general-purpose computer. We used Ganache_v2.0.1 local test network for the local experiments and Kovan test network for the public blockchain testing. We verify the proposed security protocol using Scyther_v1.1.3 protocol verifier.

134 citations


Cited by
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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

01 Jan 2002

9,314 citations

01 Jan 1990
TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.
Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

2,933 citations

Journal ArticleDOI
01 May 1975
TL;DR: The Fundamentals of Queueing Theory, Fourth Edition as discussed by the authors provides a comprehensive overview of simple and more advanced queuing models, with a self-contained presentation of key concepts and formulae.
Abstract: Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

2,562 citations