Month: May 2020

Real-time DDoS Attack Defense System in SDN Using LSSOM

Posted on by Paul Leger

We have published and presented this paper at the 26th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN). DOI: https://doi.org/10.1109/ICIN56760.2023.10073509

ABSTRACT:

Software-Defined Networking (SDN) is a new paradigm in network architecture that improves scalability, flexibility, control, and network management by separating the control plane from the data plane. SDN controllers have a global view of the entire network and provide the ability to dynamically change traffic forwarding rules. However, Introducing SDN
brings some new DDoS attack vulnerabilities, such as limited flow table capacity and single point failure of a controller.
This paper proposes an approach that combines linear discriminant analysis (LDA) and a supervised self-organizing map (SOM) called LSSOM that enables to detecting suspicious packets to defend against DDoS attacks in real-time. Our experimental results show that using LSSOM achieves 98.2% accuracy and reduces the classification time by 73.5% compared to using supervised SOM only.

Points-to Analysis for Context-Oriented JavaScript Programs

Posted on by Paul Leger

We have published and presented a paper at the 25th ACM International Workshop on Formal Techniques for Java-like Programs (FTfJP ’23). DOI: https://doi.org/10.1145/3605156.3606451

ABSTRACT:

Static analyses, as points-to analysis, are useful to determine and assure different properties about a program, such as security or type
safety. While existing analyses are effective in programs restricted to static features, precision declines in the presence of dynamic language features, and even further when the system behavior changes dynamically. As a consequence, improved points-to sets algorithms taking into account such language features and uses are required. In this paper, we present and extension of the point-to sets analysis to incorporate the language abstractions introduced by context-oriented programming adding the capability for programs to adapt their behavior dynamically to the system’s execution context. To do this, we extend WALA to detect the context-oriented language abstractions, and their representation within the system, to capture the dynamic behavior, in the particular case of the Context Traits
JavaScript language extension. To prove the effectiveness of our extension, we evaluate the precision of the points-to set analysis with respect to the state of the art, over four context-oriented programs taken from the literature.

The Effect of Message Repetition on Information Diffusion on Twitter: An Agent-Based Approach

Posted on by Paul Leger

At the Pragmatics laboratory, we have published an article in the journal IEEE Transactions on Professional Communication. DOI: https://doi.org/10.1109/TPC.2023.3260449

ABSTRACT:
Twitter offers tools that facilitate the diffusion of information by which companies can engage consumers to share their messages. Literature review: Communication professionals are using platforms such as Twitter to disseminate information; however, the strategies that they should use to achieve high information diffusion are not clear. This article proposes message repetition as a strategy. Research questions: 1. What is the wear-out point of Twitter? 2. How many times should a company repeat a tweet written on its brand page to maximize the diffusion for seeds? 3. How many times should a company repeat a tweet written on its brand page to maximize the diffusion while minimizing the number of consumers reaching their wear-out point for seeds? 4. How many times should
a company repeat a tweet written on its brand page to maximize the diffusion for non-seeds? 5. How many times should a company repeat a tweet written on its brand page to maximize the diffusion while minimizing the number of consumers reaching their wear-out point for both seeds and non-seeds? Research methodology: An agent-based simulation model for information diffusion is proposed as an approach to measure the diffusion of a tweet that has been repeated. The model considers that consumers can reach their wear-out point when they read a tweet several times. Results: The results of the model indicate the number of times a company should send the same tweet to achieve high information diffusion before this action has negative effects on consumers. Brand followers are key to achieving high information diffusion; however, consumers begin to feel bothered by the tweet by the sixth repetition. Conclusions: To the best of our knowledge, this is the first study to examine tweet repetition as a strategy to achieve higher information diffusion on Twitter. In addition, it extends the information diffusion literature by controlling the wear-out
effect. It contributes to both communication and computational science literature by analyzing a communication problem using an agent-based approach. Finally, this article contributes to the field of technical and professional communication by testing a strategy to reach great information diffusion, and by creating a tool that any company can use to anticipate the results of a communication campaign created in Twitter before launching it.