Tram Truong-Huu

Tram Truong-Huu
Singapore Institute of Technology (SIT) | SIT · Infocomm Technology (ICT)

PhD

About

65
Publications
16,620
Reads
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750
Citations
Introduction
My research interests include software-defined networks, the Internet of Things, and the application of artificial intelligence to cybersecurity.
Additional affiliations
May 2019 - present
Agency for Science, Technology and Research (A*STAR)
Position
  • Researcher
May 2018 - April 2019
National University of Singapore
Position
  • Senior Researcher
January 2017 - April 2018
National University of Singapore
Position
  • Senior Researcher
Education
October 2007 - December 2010
University of Nice Sophia Antipolis
Field of study
  • Computer Science
September 2004 - October 2007
Francophone Institute for Computer Science
Field of study
  • Computer Sciences
September 1999 - June 2004
Danang University of Technology
Field of study
  • Computer Science and Engineering

Publications

Publications (65)
Article
Full-text available
In software-defined networks, a compromised controller that is Byzantine in nature would issue inconsistent messages selectively to its communicating nodes. Defending against such threats is very challenging since the infected messages look legitimate. To defend against f simultaneous controller failures using the conventional Byzantine fault toler...
Conference Paper
Full-text available
Malware detection is a critical task in cybersecurity to protect computers and networks from malicious activities arising from malicious software. With the emergence of machine learning and especially deep learning, many malware detection models (malware classifiers) have been developed to learn features of malware samples collected from static or...
Conference Paper
Full-text available
Identifying mobile apps based on network traffic has multiple benefits for security and network management. However, it is a challenging task due to multiple reasons. First, network traffic is encrypted using an end-to-end encryption mechanism to protect data privacy. Second, user behavior changes dynamically when using different functionalities of...
Article
Full-text available
Deep learning has achieved great success in many applications. However, its deployment in practice has been hurdled by two issues: the privacy of data that has to be aggregated centrally for model training and high communication overhead due to transmission of a large amount of data usually geographically distributed. Addressing both issues is chal...
Article
Full-text available
The maturity of machine learning (ML) development and the decreasing deployment cost of capable edge devices have proliferated the development and deployment of edge ML solutions for critical IoT-based business applications. The combination of edge computing and ML not only addresses the development cost barrier, but also solves the obstacles due t...
Article
Full-text available
Motivated by the fast advancements in artificial intelligence (AI) technologies, recent research has moved towards using machine learning and deep learning to detect and classify security attacks in computer networks. However, most prior works adopt supervised learning methods, and the performance heavily depends on the amount of labeled data used...
Preprint
Full-text available
Detection and Classification of Botnet Traffic using Deep Learning with Model Explanation Appendix
Article
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Distributed denial-of-service attacks are a kind of malicious attempts among many others that make target services unavailable to legitimate users by using a large number of bots, which send many service requests exceeding the processing capacity of the services. Detection of botnet traffic is therefore critical to maintaining the availability and...
Preprint
Full-text available
Generative Adversarial Networks (GANs) have emerged as useful generative models, which are capable of implicitly learning data distributions of arbitrarily complex dimensions. However, the training of GANs is empirically well-known for being highly unstable and sensitive. The loss functions of both the discriminator and generator concerning their p...
Conference Paper
Full-text available
Network anomaly detection is paramount to early detect traffic anomalies and protect networks against cyber attacks such as (distributed) denial of service attacks and phishing attacks. As deep learning has succeeded in various domains, it has been adopted for network anomaly detection using a supervised learning approach. Due to the high velocity...
Preprint
Full-text available
The maturity of machine learning (ML) development and the decreasing deployment cost of capable edge devices have proliferated the development and deployment of edge ML services in developing countries for critical IoT-based business applications. The combination of edge computing and ML not only addresses the development cost barrier but also solv...
Preprint
Full-text available
Understanding the dynamic behavior of computer programs during normal working conditions is an important task, which has multiple security benefits such as the development of behavior-based anomaly detection, vulnerability discovery, and patching. Existing works achieved this goal by collecting and analyzing various data including network traffic,...
Conference Paper
Full-text available
Nowadays, it is increasingly difficult even for a machine learn- ing expert to incorporate all of the recent best practices into their modeling due to the fast development of state-of-the-art machine learning techniques. For the applications that handle big data sets, the complexity of the problem of choosing the best performing model with the best...
Conference Paper
Full-text available
Understanding the dynamic behavior of computer programs during normal working conditions is an important task, which has multiple security benefits such as the development of behavior-based anomaly detection, vulnerability discovery, and patching. Existing works achieved this goal by collecting and analyzing various data including network traffic,...
Conference Paper
Full-text available
Network anomalies can arise due to various causes such as abnormal behaviors from users, malfunctioning network devices, malicious activities performed by attackers, malicious software or botnets. With the emergence of machine learning and especially deep learning, many works in the literature developed learning models that are able to detect netwo...
Preprint
Full-text available
The deployment of such deep learning in practice has been hurdled by two issues: the computational cost of model training and the privacy issue of training data such as medical or healthcare records. The large size of both learning models and datasets incurs a massive computational cost, requiring efficient approaches to speed up the training phase...
Article
Full-text available
Cloud data centers nowadays play an important role in providing computing and network resources for online applications and services. Such applications obtain cloud resources by submitting resource requests in the form of virtual networks that are embedded in the cloud infrastructures, referred to as virtual network embedding (VNE). Developing an e...
Conference Paper
Full-text available
Digital advertising is a critical task for any business sectors to announce their new products and attract customers (audience). Digital advertising requires efficient market segmentation methods (i.e., customer clustering) to group customers into different categories based on age, gender, and other particulars so that ads can reach the appropriate...
Conference Paper
Full-text available
Fast failure recovery is a critically-important problem in networks. To address this problem in software-defined networks (SDN), backup paths can be chosen in a proactive and adaptive manner in accordance with the traffic dynamics. Existing proactive approaches make use of only the network topology knowledge or a combined knowledge of the topology...
Article
Full-text available
With the proliferation of network devices and rapid development in information technology, networks such as Inter- net of Things are increasing in size and becoming more complex with heterogeneous wired and wireless links. In such networks, link faults may result in a link disconnection without immediate replacement or a link reconnection, e.g., a...
Article
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We address the problem of embedding service chains consisting of a sequence of virtual network functions (VNF) for 5G slices, considering diversified slice requirements. We develop a fine-grained approach that considers resource requirements and limited traffic processing capacity of VNFs, which can be shared (or not) among slices depending on VNF...
Preprint
Full-text available
With the proliferation of network devices and rapid development in information technology, networks such as Internet of Things are increasing in size and becoming more complex with heterogeneous wired and wireless links. In such networks, link faults may result in a link disconnection without immediate replacement or a link reconnection, e.g., a wi...
Preprint
Full-text available
Recent developments in intelligent transport systems (ITS) based on smart mobility significantly improves safety and security over roads and highways. ITS networks are comprised of the Internet-connected vehicles (mobile nodes), roadside units (RSU), cellular base stations and conventional core network routers to create a complete data transmission...
Conference Paper
Full-text available
In software-defined networks, distributed controller architectures provide improved scalability and reliability by using multiple controllers, each managing a partition of the network. However, due to the dynamics of network control traffic, static switch-controller mapping causes load imbalance while dynamic mapping causes frequent switch migratio...
Article
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Big data is becoming a major focus for both industry and academia, requiring drastic changes in all aspects of computer systems in order to store, process and transfer big data. In networks, a fundamental problem is how to efficiently transfer big data since the performance is affected by several factors such as path, bandwidth and scheduled start...
Conference Paper
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Communication networks such as wireless sensor networks, Internet of Things and vehicular ad-hoc networks are becoming more complex and increasing in size. This leads to high overhead (network and computation) and difficulty in determining the accurate network topology, which is an important information for traffic engineering and network managemen...
Conference Paper
Full-text available
Security in Software Defined Networks (SDNs) has been a major concern for its deployment. Byzantine threats in SDNs are more sophisticated to defend since control messages issued by a compromised controller look legitimate. Applying traditional Byzantine Fault Tolerance approach to SDNs requires each switch to be mapped to 3f + 1 controllers to def...
Conference Paper
Full-text available
Distributed controller architectures in software defined networks raise the issue of switch-controller mapping and control traffic engineering. In a mapping approach where a switch distributes flow setup requests (traffic) to multiple controllers, a solution that finds the optimal switch-controller mapping and traffic distribution among the control...
Article
Full-text available
We propose an effective switch-controller mapping scheme for distributed controller architectures in Software Defined Networks. Our scheme maps a switch to multiple controllers and distributes flow setup requests among them to minimize flow setup time, satisfying the resilience constraint which requires that a specified fraction of setup requests a...
Conference Paper
Full-text available
Large amount of data is being generated at an alarming rate by various systems and devices such as computing systems, cameras, mobile devices, etc. The insights and findings obtained from data commonly referred to as "big data" , are revolutionizing several aspects of our everyday life. Owing to the huge volume of this data, its processing and anal...
Article
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Optical switching based on wavelength division multiplexing (WDM) has become a promising network technology to scale the performance of data centers. It provides high bisection bandwidth with low power consumption and low complexity of network wiring. However, it raises new challenges for the flow scheduling problem due to the dynamic arrival of tr...
Article
Full-text available
In Software Defined Networks (SDNs), while a proactive fault tolerance based on the local rerouting approach enables fast failure recovery, it requires to install forwarding rules for the backup paths in the switch Ternary Content Addressable Memory (TCAM) in advance. Since the TCAM size is limited and forwarding rules are long, using large number...
Conference Paper
Full-text available
Cloud data centers have become an attractive candidate for network-based large scale applications that require cloud resources in the form of a virtual network. Embedding virtual networks in data centers to allocate resources to their applications is therefore crucial since it affects resource efficiency and thus the final revenue of cloud provider...
Conference Paper
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Wavelength division multiplexed optical networks have become an attractive candidate to meet the ever-growing traffic demands in cloud data centers due to the features of large capacity and dynamic reconfiguration capability. While the bandwidth does not affect the makespan of compute-intensive and content-delivery-network applications, it has an i...
Article
Full-text available
In this paper, we address the problem of embedding dynamically-arriving workflow requests in data centers. Workflows pose challenges due to data precedence and time disjointness among tasks, thus driving the need for intelligent methods to embed workflows in data centers while improving the bandwidth efficiency as well as guaranteeing the applicati...
Article
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The emergence of cloud computing has made it become an attractive solution for large-scale data processing and storage applications. Cloud infrastructures provide users a remote access to powerful computing capacity, large storage space and high network bandwidth to deploy various applications. With the support of cloud computing, many large-scale...
Conference Paper
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Representing a large class of coarse-grained distributed applications , workflows require large computing and bandwidth resources for their execution. With specific resource requirements due to data precedence and time disjointness, mapping workflow resource requests in data centers is a challenging problem for cloud providers. While existing appro...
Conference Paper
Full-text available
In Software Defined Networks (SDNs), a reactive approach for failure recovery involves the centralized SDN controller which incurs long delays leading to packet losses. While a proactive approach enables fast failure recovery, it poses a new challenge concerning the number of additional forwarding rules required at every switch traversed by a flow...
Conference Paper
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With the increasing demand for large bandwidth and diversity of bandwidth requests, to maximize the revenue, cloud providers nowadays try to offer different bandwidth request models that include guaranteed bandwidth reservation requests and on-demand flexible bandwidth requests. While guaranteed bandwidth reservation requests are beneficial for pro...
Conference Paper
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With more parallel and distributed applications moving to Cloud and data centers, it is challenging to provide predictable and controllable resources to multiple tenants, and thus guarantee application performance. In this paper, we propose an integrated QoS-aware resource provisioning platform based on virtualization technology for computing, stor...
Conference Paper
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The significant development of mobile cloud computing allows a mobile user to access resources of the nearby mobile devices, i.e., Cloudlets, for processing tasks by using the offloading mechanism. However, due to the mobility of the user and cloudlets, the connection between the user's device and cloudlets may be interrupted since cloudlets move o...
Conference Paper
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Mobile devices like smartphones have become the computing device of choice for many users, heralding the era of mobile computing. Many applications have been developed to run on mobile devices. However, despite the increased processing and wireless network speeds of mobile devices, their resources are still limited in terms of processing capacity a...
Article
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Having received significant attention in the industry, the cloud market is nowadays fiercely competitive with many cloud providers. On one hand, cloud providers compete against each other for both existing and new cloud users. To keep existing users and attract newcomers, it is crucial for each provider to offer an optimal price policy which maximi...
Conference Paper
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With many providers in today's cloud market, it is crucial for each provider to offer an optimal price policy which maximizes the final revenue and improves the competitive advantage. The competition among providers leads to the evolution of the market and dynamic resource prices over time. In this paper, we address the competition among cloud prov...
Article
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In this paper, we leverage the previous work on the SHIWA bundling format and expand on this specification in order to facilitate workflow execution within a multi-workflow environment. We introduce a scalable and robust execution pool environment that supports workflows consisting of sub-workflows built upon a multitude of different workflow engin...
Conference Paper
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Cloud computing is emerging as a paradigm for large-scale data-intensive applications. Cloud infrastructures allow users to remotely access to computing power and data over the Internet. Beside the huge economical impact, data centers consume enormous amount of electrical energy, contributing to high operational cost and carbon footprints to the en...
Article
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Neuroimaging is a field that benefits from distributed computing infrastructures (DCIs) to perform data- and compute-intensive processing and analysis. Using grid workflow systems not only automates the processing pipelines, but also enables domain researchers to implement their expertise on how to best process neuroimaging data. To share this expe...
Conference Paper
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In spite of the growing interest for grids and cloud infrastructures among scientific communities and the availability of such facilities at large-scale, achieving high performance in production environments remains challenging due to at least four factors: the low reliability of very large-scale distributed computing infrastructures, the performan...
Conference Paper
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This paper reports on the implementation of a comprehensive framework for design and execution of scientific applications on multiple distributed computing infrastructures. The architecture leverages available tools of the scientific community underlining the effort of the integration process. The framework brings together heterogeneous technologie...
Article
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Cloud computing infrastructures are providing resources on demand for tackling the needs of large-scale distributed applications. To adapt to the diversity of cloud infrastructures and usage, new operation tools and models are needed. Estimating the amount of resources consumed by each application in particular is a difficult problem, both for end...
Thesis
Full-text available
Cloud computing is increasingly exploited to tackle the computing challenges raised in both science and industry. Clouds provide computing, network and storage resources on demand to satisfy the needs of large-scale distributed applications. To adapt to the diversity of cloud infrastructures and usage, new tools and models are needed. Estimating th...
Conference Paper
Full-text available
Through the recent emergence of joint resource and network virtualization, dynamic composition and provisioning of time-limited and isolated virtual infrastructures is now possible. One other benefit of infrastructure virtualization is the capability of transparent reliability provisioning (reliability becomes a service provided by the infrastructu...
Conference Paper
Full-text available
Cloud computing infrastructures are providing resources on demand for tackling the needs of large-scale distributed applications. Determining the amount of resources to allocate for a given computation is a difficult problem though. This paper introduces and compares four automated resource allocation strategies relying on the expertise that can be...
Conference Paper
Full-text available
Cloud computing infrastructures are providing resources on demand. Determining the amount of resources to allocate for a given application run is a difficult problem though. This paper introduces and compares four automated resource allocation strategies relying on the expertise that can be captured in workflow-based applications. The evaluation of...
Conference Paper
With the expansion and convergence of communication and computing, dynamic provisioning of cus- tomized networking and processing infrastructures as well as resource virtualization are appealing concepts and technologies. Therefore new models and tools are needed to allow users to create, trust and enjoy such on-demand virtual infrastructures withi...