IEEE North Jersey Section

[] Internet traffic modeling and analysis is critical for network design and for cybersecurity. Internet traffic differs from Telephone traffic insofar as it characterized by long range dependent scale-free temporal dynamics. In this talk, we will describe multiscale analysis as a state-of-the-art tool to assess and quantify scale-free dynamics. We will also that show that wavelet analysis mut be combined with random projection strategies to permit a statistical characterization of Internet background traffic both accurate and robust to anomalies. In turn, these random projections can be further involved into automated anomaly detection and into the identification of the IP addresses involved. However, scale-free analysis remained so far mostly univariate, applied independently to directional counts of either bytes or packets, while challenges in cybersecurity naturally call for multivariate analysis. Elaborating on recent theoretical developments on eigenvalue-based multivariate self-similarity analysis, this talk will provide evidence for multivariate self-similarity in 17 years of Internet traffic data from the MAWI repository and will discuss the potential use of multivariate self-similarity for low volume anomaly detection. Co-sponsored by: Fairleigh Dickinson University Speaker(s): Dr. Patrice Abry Agenda: Fairleigh Dickinson University 1000 River Road, Building: Muscarelle Center, Room Number: 105 Teaneck, New Jersey, United States 07666 For additional information about the venue and parking, please contact Dr. Hong Zhao zhao@fdu.edu Virtual: https://events.vtools.ieee.org/m/469441

Dear All, You are cordially invited to attend the April ExCom meeting at Montclair State University or on Zoom. Looking forward to seeing you all Best Regards Emad Montclair State University, Montclair, New Jersey, United States, Virtual: https://events.vtools.ieee.org/m/476228

Abstract: The rapid evolution of Artificial Intelligence (AI) in cybersecurity is reshaping how digital threats are detected, mitigated, and prevented. AI-driven security solutions enhance threat intelligence, automate responses, and strengthen cyber defense mechanisms. However, as AI becomes more embedded in cybersecurity frameworks, it raises critical concerns about human rights, privacy, and ethical governance. The use of AI in surveillance, data monitoring, and decision-making has sparked debates about its potential to infringe on fundamental freedoms, leading to questions about accountability, fairness, and transparency. This webinar will explore the intersection of cybersecurity, AI, and human rights, addressing how AI-driven security measures impact digital privacy, freedom of expression, and the ethical responsibilities of organizations and governments. Experts from cybersecurity, law, and ethics will discuss key challenges such as algorithmic bias, the risks of AI-powered surveillance, and the implications of cybersecurity policies on human rights. Additionally, the session will examine regulatory frameworks and best practices to ensure AI technologies are deployed responsibly while upholding democratic values and societal trust. Speaker Bio: Mr. Sheshananda Reddy Kandula is a seasoned Application Security professional with 15 years of experience, currently working at Adobe, where he specializes in securing web, mobile, and API ecosystems. His expertise lies in identifying and mitigating vulnerabilities in alignment with OWASP Top 10 security standards. He holds industry-recognized certifications, including OSWE, OSCP, and CISSP, and has extensive hands-on experience addressing real-world security challenges. Prior to his role at Adobe, he contributed to global security initiatives at Mastercard, leading efforts in vulnerability management and secure software development. Passionate about advancing cybersecurity, Mr. Kandula actively contributes to the security community by sharing insights on secure coding, threat modeling, and application security best practices. His commitment extends to mentorship, technical leadership, and research, fostering a security-first mindset across organizations and professionals. Through his work, he strives to empower security practitioners, promote awareness, and strengthen digital resilience in an evolving threat landscape. Virtual: https://events.vtools.ieee.org/m/470549

Special Presentation by Dr. Samson Lasulce (Khalifa U., UAE) Hosted by the Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group Date/Time: Thursday, 17 April 2025 @ 12:00 UTC Topic: Large Language Models (LLMs), Optimization, and Game Theory Abstract: In this talk, we will explore the interplay between large language models (LLMs) and optimization. After introducing a use case (consumption power scheduling) for which studying this interplay is fully relevant, we will survey the main approaches in this area, which include pure LLM-based approaches (e.g., to deal with math word problems) and combined approaches. Both limitations and promising solutions will be discussed. Application to radio resource management and to telecommunications more generally will also be addressed. In the last part of the talk, connections between LLMs and game theory will be discussed. Speaker: [] Samson Lasaulce is a Chief Research Scientist with Khalifa University. He is the holder of the TII 6G Chair on Native AI. He is also a CNRS Director of Research with CRAN at Nancy. He has been the holder of the RTE Chair on the "Digital Transformation of Electricity Networks". He has also been a part-time Professor with the Department of Physics at École Polytechnique (France). Before joining CNRS he has been working for five years in private R&D companies (Motorola Labs and Orange Labs). His current research interests lie in distributed networks with a focus on optimization, game theory, and machine learning. The main application areas of his research are wireless networks, energy networks, social networks, and now climate change. Dr Lasaulce has been serving as an editor for several international journals such as the IEEE Transactions. He is the co-author of more than 200 publications, including a dozen of patents and several books such as "Game Theory and Learning for Wireless Networks: Fundamentals and Applications". Dr Lasaulce is also the recipient of several awards such as the Blondel Medal award from the SEE French society.. Co-sponsored by: Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group Virtual: https://events.vtools.ieee.org/m/474729