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7th International Conference on Computer and Knowledge Engineering, ICCKE 2017

作者： Owhadi-Kareshk, Moein Sedaghat, Yasser Akbarzadeh, Mohammad-R.-T. Center of Excellence On Soft Computing and Intelligent Information Processing Ireland Dependable Distributed Embedded Systems Laboratory Department of Computer Engineering Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9781538608043

Software fault prediction is one of the significant stages in the software testing process. At this stage, the probability of fault occurrence is predicted based on the documented information of the software systems that are already tested. Using this prior knowledge, developers and testing teams can better manage the testing process. There are many efforts in the field of machine learning to solve this classification problem. We propose to use a pre-training technique for a shallow, i.e. with fewer hidden layers, Artificial Neural Network (ANN). While this method is usually employed to prevent over-fitting in deep ANNs, our results indicate that even in a shallow network, it improves the accuracy by escaping from local minima. We compare the proposed method with four SVM-based classifiers and a regular ANN without pre-training on seven datasets from NASA codes in the PROMISE repository. Results confirm that the pre-training improves accuracy by achieving the best overall ranking of 1.43. Among seven datasets, our method has higher accuracy in four of them, while ANN and support vector machine are the best for two and one datasets, respectively. © 2017 IEEE.

关键词： Software testing

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A metadata-based architectural model for dynamically resilient systems

Proceedings of the ACM Symposium on Applied Computing

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Proceedings of the ACM Symposium on Applied computing 2007年 566-572页

作者： Di Marzo Serugendo, Giovanna Fitzgerald, John Romanovsky, Alexander Guelfi, Nicolas School of Computer Science and Information Systems Birkbeck College London United Kingdom School of Computing Science University of Newcastle NE1 7RU Newcastle upon Tyne United Kingdom Laboratory for Advanced Software Systems University of Luxembourg Luxembourg Luxembourg

ISBN: (纸本)1595934804;9781595934802

Designing open and distributed systems that can dynamically adapt in a predictable way to unexpected events is a challenging issue still not solved. Achieving this objective is a very complex task since it implies reasoning at run-time, explicitly and in a combined way, on a system's functional and non-functional characteristics. This paper proposes a service-oriented architectural model allowing the dynamic enforcement of formally expressed metadata-based resilience policies. It also describes preliminary dynamic resilience experiments acting as proof of concept. Copyright 2007 ACM.

关键词： Metadata

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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Computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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TraCemop: Towards Federated Learning with Traceable Contribution Evaluation and Model Ownership Protection

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IEEE Transactions on Mobile computing 2025年

作者： Liu, Jingwei Zhou, Zihan Sun, Rong Liu, Lei Lu, Rongxing Dustdar, Schahram Niyato, Dusit Ministry of Education Engineering Research Center of Blockchain Technology Application and Evaluation China Xidian University Shaanxi Key Laboratory of Blockchain and Secure Computing Xi'an710071 China Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China Xidian University Guangzhou Institute of Technology Guangzhou510555 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Queen's University School of Computing KingstonONK7L 2N8 Canada TU Wien Distributed Systems Group Austria UPF ICREA Barcelona Spain Nanyang Technological University School of Computer Science and Engineering Singapore

Federated Learning (FL) allows multiple clients to collaboratively train machine learning models without the need to share their local private data. As a result, it can effectively address the issue of data fragmentation. Nevertheless, insufficient evaluation of individual contributions and the lack of protections for both the intellectual property rights (IPR) of models and client privacy can greatly reduce clients' motivations in federated training. To address these challenges, this paper introduces the Traceable Contribution Evaluation and Model Ownership Protection (TraCemop) framework for federated learning, which allows each client to swiftly assess the contributions of others in each round, with integrated support for the traceability of evaluation results. To safeguard the intellectual property of models, a collective watermark is embedded in the global model. Additionally, a secure mechanism for verifying model ownership is also available in case of disputes. Security analysis indicates that TraCemop is capable of resisting data reconstruction attacks as well as various types of model copyright infringements. Finally, we evaluate the proposed framework using two commonly-used datasets, and the experimental results show a significant improvement in the efficiency of contribution evaluation compared to existing methods. Meanwhile, IPR infringement tests on TraCemop reveal that the proposed framework is resilient against malicious efforts to monopolize model ownership. © 2002-2012 IEEE.

关键词： Federated learning

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A four worlds framework for understanding ubiquitous learning context engineering

A four worlds framework for understanding ubiquitous learnin...

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22nd International Business information Management Association Conference, IBIMA 2013

作者： Souabni, Raoudha Saadi, Ines Bayoudh Kinshuk Ghezala, Henda Ben RIADI Research Laboratory ENSI Manouba University Manouba Tunisia School of Computing and Information Systems Athabasca University Athabasca Canada

ISBN: (纸本)9780982148914

In the last decades, ubiquitous learning (u-learning) systems engineering became a major challenge due to the increasing variety of the highly dynamic learning context sources. Hence, an increasing number of ulearning systems, supporting learning through seamlessly integrated computers in everyday life, are now being developed. Each system aims to resolve a specific problem in a specific context. The development of these systems is mainly dependant on an individual developer's vision. There is no consensus on the learning context of each system or how it should be used and represented and how its representation should be developed. This paper proposes a common evaluating framework for u-learning systems along four different and complementary worlds. Each world is capturing a particular aspect of u-learning context engineering. The benefit of this evaluating framework is threefold. First, it helps understand and analyze in-depth how u-learning systems deal with the learner context. Second, it helps comparing systems according the framework's views. Third, it helps researchers to identify new research axes.

关键词： Learning systems

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Partial label learning via label-specific features enhancement and semi-disambiguation

Partial label learning via label-specific features enhanceme...

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2024 International Conference on Automation Control, Algorithm, and Intelligent Bionics, ACAIB 2024

作者： Hu, Jinhua Chai, Jing Sun, Xianran School of information Science and Engineering Yunnan University Kunming650504 China Yunnan Key Laboratory of Intelligent Systems and Computing China

ISBN: (纸本)9781510682597

Partial Label Learning (PLL) represents a common multi-class weakly supervised learning challenge, where each instance is linked with a set of possible labels, only one of which is the ground-truth label, and it remains unknown during the training. A common strategy for solving this multi-class problems is to decompose it into a series of binary classification problems based on certain coding rules (e.g., OvO, ECOC), and then process each binary classification problem separately using the original features. To address the deficiency of discriminative information in the original features, a feature enhancement mechanism is proposed to introduce label-specific features to improve the discriminative performance of features. Firstly, label-specific features are generated for each decomposed binary classification problem, and then fused with the original features. The fused features are used to design corresponding binary classifiers. Additionally, due to the presence of a large number of false positive labels in the training examples, a semi-disambiguation strategy can be employed to remove some false positive labels, thereby "slimming down" the candidate label set as a preprocessing step to reduce its ambiguity. The proposed partial label learning algorithm based on features enhancement and semi-disambiguation proves its effectiveness on synthetic and real-world data sets through extensive experiments. © 2024 SPIE.

关键词： Contrastive Learning

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A comprehensive view of ubiquitous learning context usage in context-aware learning system 2nd

A comprehensive view of ubiquitous learning context usage in...

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2nd International Conference on Context-Aware systems and Applications, ICCASA 2013

作者： Souabni, Raoudha Saadi, Ines Bayoudh Kinshuk Ghezala, Henda Ben RIADI Research Laboratory - ENSI Manouba University Manouba Tunisia School of Computing and Information Systems Athabasca University Athabasca Canada

ISBN: (纸本)9783319059389

Research related to context-aware u-learning system has proliferated during last decades. systems identified in literature are developed in ad-hoc manner to resolve a specific problem in a given context;however, u-learning systems developers need to have a clear and a general view of how their intended systems make use of the ubiquitous context. The paper details a general descriptive view of context usage within learning systems through three different view-points inspired from Dowson’s work [1]. Each view is capturing a particular aspect of context handling. Then a set of facets is associated to each given aspect in order to study, understand and appropriately describe it. This work would be useful for context-aware u-learning system developers in order to have a clear understanding of the context usage in such systems and to underline the requirements of the u-learning environment to respond. This research is also aimed to establish a structured baseline to help in comparing and evaluating context-aware u-learning systems according to the descriptive system views. © Springer International Publishing Switzerland 2014.

关键词： Learning systems

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An intentional model for pedagogical process guidance supported by an adaptive learning system

An intentional model for pedagogical process guidance suppor...

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23rd International Business information Management Association Conference, IBIMA 2014

作者： Bayounes, Walid Saâdi, Ines Bayoudh Kinshuk Ghézala, Henda Ben RIADI Research Laboratory ENSI Manouba University Manouba Tunisia School of Computing and Information Systems Athabasca University Athabasca Canada

ISBN: (纸本)9780986041921

Pedagogical process is used by different learning systems with aim to guide learners and help to make learning easier and more effective. However, issues still remain;in particular learning systems guide the pedagogical process without any dynamic orientation to the learning process. Many commercial systems allow the experts to build the pedagogical process, but it is currently not possible to orient the pedagogical process to the learning process of individual learners through the pedagogical process guidance in real-time. In order to solve the issues of a process guidance;this paper discusses the potential of intentional model for pedagogical process guidance. The latter couples the teacher's intention with the pedagogical strategies, and provides a multitude of paths between teacher intentions. In fact, based on the family of pedagogical strategies, the family of pedagogical method and the teaching style, we can adaptively support the teacher to achieve his intention through the selected strategy. The paper concludes by discussing the benefits and limitations of our model implementation and discusses future extensions to allow for the automatic adaptation of pedagogical process.

关键词： Learning systems

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Refuting security proofs for tripartite key exchange with model checker in planning problem setting

Refuting security proofs for tripartite key exchange with mo...

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19th IEEE Computer Security Foundations Workshop, CSFW 2006

作者： Choo, Kim-Kwang Raymond Intelligent Systems Laboratory School of Computing and Information Technology University of Western Sydney Penrith South DC NSW 1797 Australia

ISBN: (纸本)0769526152

We encode a simplified version of the Canetti and Krawczyk (2001) formalism using Asynchronous Product Automata (APA). We then use a model checker tool, Simple Homomorphism Verification Tool (SHVT), to perform statespace analysis on our Automata in the setting of planning problem. As a case study, we revisit two tripartite key exchange protocols of Hitchcock, Boyd, and Gonzalez Nieto (2004), which carry claimed security proofs in the Canetti and Krawczyk (2001) model. We refute their proofs of security by pointing out previously unpublished flaws in the protocols using SHVT. We then point out corresponding flaws in the refuted proofs. © 2006 IEEE.

关键词： Security of data

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Robust Scheduling of Scientific Workflows with Deadline and Budget Constraints in clouds

Robust Scheduling of Scientific Workflows with Deadline and ...

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IEEE International Conference on Advanced information Networking and Applications

作者： Deepak Poola Saurabh Kumar Garg Rajkumar Buyya Yun Yang Kotagiri Ramamohanarao Cloud Computing and Distributed Systems (CLOUDS) Laboratory Department of Computing and Information Systems The University of Melbourne Australia Department of Computing and Information Systems University of Tasmania Hobart Australia Faculty of SET Swinburne University of Technology Melbourne Australia

ISBN: (纸本)9781479936311

Dynamic resource provisioning and the notion of seemingly unlimited resources are attracting scientific workflows rapidly into cloud computing. Existing works on workflow scheduling in the context of clouds are either on deadline or cost optimization, ignoring the necessity for robustness. Robust scheduling that handles performance variations of cloud resources and failures in the environment is essential in the context of clouds. In this paper, we present a robust scheduling algorithm with resource allocation policies that schedule workflow tasks on heterogeneous cloud resources while trying to minimize the total elapsed time (makespan) and the cost. Our results show that the proposed resource allocation policies provide robust and fault-tolerant schedule while minimizing makespan. The results also show that with the increase in budget, our policies increase the robustness of the schedule.

关键词： Workflows cloud Robustness Fault-Tolerance Scheduling

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