Data Mining - Concepts and Techniques.

Usually, a proof of a theorem contains more knowledge than the mere fact that the theorem is true. For instance, to prove that a graph is Hamiltonian it suffices to exhibit a Hamiltonian tour in it; however, this seems to contain more knowledge than the single bit Hamiltonian/non-Hamiltonian.In this paper a computational complexity theory of the “knowledge” contained in a proof is developed. Zero-knowledge proofs are defined as those proofs that convey no additional knowledge other than the correctness of the proposition in question. Examples of zero-knowledge proof systems are given for the languages of quadratic residuosity and 'quadratic nonresiduosity. These are the first examples of zero-knowledge proofs for languages not known to be efficiently recognizable.

/pdf/the-knowledge-complexity-of-interactive-proof-systems-31apre0ecf.pdf

The knowledge complexity of interactive proof-systems

Simulation and the monte carlo method

The demand for wireless connectivity has grown exponentially over the last few decades. Fifth-generation (5G) communications, with far more features than fourth-generation communications, will soon be deployed worldwide. A new paradigm of wireless communication, the sixth-generation (6G) system, with the full support of artificial intelligence, is expected to be implemented between 2027 and 2030. Beyond 5G, some fundamental issues that need to be addressed are higher system capacity, higher data rate, lower latency, higher security, and improved quality of service (QoS) compared to the 5G system. This paper presents the vision of future 6G wireless communication and its network architecture. This article describes emerging technologies such as artificial intelligence, terahertz communications, wireless optical technology, free-space optical network, blockchain, three-dimensional networking, quantum communications, unmanned aerial vehicles, cell-free communications, integration of wireless information and energy transfer, integrated sensing and communication, integrated access-backhaul networks, dynamic network slicing, holographic beamforming, backscatter communication, intelligent reflecting surface, proactive caching, and big data analytics that can assist the 6G architecture development in guaranteeing the QoS. Besides, expected applications with 6G communication requirements and possible technologies are presented. We also describe potential challenges and research directions for achieving this goal.

/pdf/6g-wireless-communication-systems-applications-requirements-wv55ufdelk.pdf

6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions

LNBIP reports state-of-the-art results in areas related to business information systems and industrial application software development – timely, at a high level, and in both printed and electronic form.  The type of material published includes  • Proceedings (published in time for the respective event) • Postproceedings (consisting of thoroughly revised and/or extended final papers) • Other edited monographs (such as, for example, project reports or invited volumes) • Tutorials (coherently integrated collections of lectures given at advanced courses, seminars, schools, etc.) • Award-winning or exceptional theses LNBIP is abstracted/indexed in DBLP, EI and Scopus. LNBIP volumes are also submitted for the inclusion in ISI Proceedings.

Lecture notes in business information processing

Recently, money laundering is becoming more and more sophisticated, it seems to have moved from the personal gain to the cliche of drug trafficking and financing terrorism. This criminal activity poses a serious threat not only to financial institutions but also to the nation. Today, most international financial institutions have been implementing anti-money laundering solutions but traditional investigative techniques consume numerous man-hours. Besides, most of the existing commercial solutions are based on statistics such as means and standard deviations and therefore are not efficient enough, especially for detecting suspicious cases in investment activities. In this paper, we present a case study of applying a knowledge-based solution that combines data mining and natural computing techniques to detect money laundering patterns. This solution is a part of a collaboration project between our research group and an international investment bank.

Application of Data Mining for Anti-money Laundering Detection: A Case Study

A complete formalized knowledge representation model for advanced digital forensics timeline analysis

Sampling-based dimensionality reduction technique.Eliminating linearly redundant combined dimensions.Providing a convenient way to generate correlated multivariate random variables.Maintaining the integrity of the original information.Reducing the dimension of data space without losing important information. The recent trends in collecting huge and diverse datasets have created a great challenge in data analysis. One of the characteristics of these gigantic datasets is that they often have significant amounts of redundancies. The use of very large multi-dimensional data will result in more noise, redundant data, and the possibility of unconnected data entities. To efficiently manipulate data represented in a high-dimensional space and to address the impact of redundant dimensions on the final results, we propose a new technique for the dimensionality reduction using Copulas and the LU-decomposition (Forward Substitution) method. The proposed method is compared favorably with existing approaches on real-world datasets: Diabetes, Waveform, two versions of Human Activity Recognition based on Smartphone, and Thyroid Datasets taken from machine learning repository in terms of dimensionality reduction and efficiency of the method, which are performed on statistical and classification measures.

Dimensionality reduction in data mining

6G wireless networks improve on 5G by further increasing reliability, speeding up the networks and increasing the available bandwidth. These evolutionary enhancements, together with a number of revolutionary improvements such as high-precision 3D localization, ultra-high reliability and extreme mobility, introduce a new generation of 6G-native applications. Such application can be based on, for example, distributed, ubiquitous Artificial Intelligence (AI) and ultra-reliable, low-latency Internet of Things (IoT). Along with the enhanced connectivity and novel applications, privacy and security of the networks and the applications must be ensured. Distributed ledger technologies such as blockchain provide one solution for application security and privacy, but introduce their own set of security and privacy risks. In this work, we discuss the opportunities and challenges related to blockchain usage in 6G, and map out possible directions for overtaking the challenges.

/pdf/privacy-aware-blockchain-innovation-for-6g-challenges-and-2ney1biz76.pdf

M-Tahar Kechadi

Papers

Application of Data Mining for Anti-money Laundering Detection: A Case Study

A complete formalized knowledge representation model for advanced digital forensics timeline analysis

Dimensionality reduction in data mining

Privacy-Aware Blockchain Innovation for 6G: Challenges and Opportunities

BitTorrent Sync: First Impressions and Digital Forensic Implications