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"The objective of this book is to provide the reader with a comprehensive survey of the topic compressed sensing in information retrieval and signal detection with privacy preserving functionality without compromising the performance of the embedding in terms of accuracy or computational efficiency. The reader is guided in exploring the topic by first establishing a shared knowledge about compressed sensing and how it is used nowadays. Then, clear models and definitions for its use as a cryptosystem and a privacy-preserving embedding are laid down, before tackling state-of-the-art results for both applications. The reader will conclude the book having learned that the current results in terms of security of compressed techniques allow it to be a very promising solution to many practical problems of interest. The book caters to a broad audience among researchers, scientists, or engineers with very diverse backgrounds, having interests in security, cryptography and privacy in information retrieval systems. Accompanying software is made available on the authors’ website to reproduce the experiments and techniques presented in the book. The only background required to the reader is a good knowledge of linear algebra, probability and information theory."

"Data are the prominent elements in scientific researches and approaches. Data Science methodology is used to select and to prepare enormous numbers of data for further processing and analysing. Big Data technology collects vast amount of data from many sources in order to exploit the information and to visualise trend or to discover a certain phenomenon in the past, present, or in the future at high speed processing capability. Predictive analytics provides in-depth analytical insights and the emerging of machine learning brings the data analytics to a higher level by processing raw data with artificial intelligence technology. Predictive analytics and machine learning produce visual reports for decision makers and stake-holders. Regarding cyberspace security, big data promises the opportunities in order to prevent and to detect any advanced cyber-attacks by using internal and external security data."

"Data merupakan unsur terpenting dalam setiap penelitian dan pendekatan ilmiah. Metodologi sains data digunakan untuk memilah, memilih dan mempersiapkan sejumlah data untuk diproses dan dianalisis. Teknologi big data mampu mengumpulkan data dengan sangat banyak dari berbagai sumber dengan tujuan untuk mendapatkan informasi dengan visualisasi tren atau menyingkapkan pengetahuan dari suatu peristiwa yang terjadi baik dimasa lalu, sekarang, maupun akan datang dengan kecepatan pemrosesan data sangat tinggi. Analisis prediktif memberikan wawasan analisis lebih dalam dan kemunculan machine learning membawa analisis data ke tingkat yang lebih tinggi dengan bantuan teknologi kecerdasan buatan dalam tahap pemrosesan data mentah. Analisis prediktif dan machine learning menghasilkan laporan berbentuk visual untuk pengambil keputusan dan pemangku kepentingan. Berkenaan dengan keamanan siber, big data menjanjikan kesempatan dalam rangka untuk mencegah dan mendeteksi setiap serangan canggih siber dengan memanfaatkan data keamanan internal dan eksternal."

"Keamanan data adalah infrastruktur yang dirancang untuk melindungi dan mengamankan data dari akses yang tidak sah, manipulasi data, malfungsi, perusakan, dan pengungkapan data yang tidak sesuai. Saat ini, organisasi banyak menggunakan transfer data untuk memvalidasi dan memverifikasi data menggunakan media yang berbeda terutama dalam koneksi host-to-host. Penelitian ini berfokus pada pertukaran data (end-to-end communication) menggunakan arsitektur jaringan Multi Protocol Label Switching (MPLS), Metro Ethernet, dan Software Defined Wide Area Network (SD-WAN) dengan pihak ketiga. Risiko yang timbul dari serangan siber pada transfer data pada transaksi host-to-host adalah kehilangan data, reputasi institusi, hingga yang paling berisiko adalah distribusi data tersebut. Penelitian ini bertujuan untuk mengembangkan kerangka kerja untuk memverifikasi data yang ditransfer dari satu host ke host lain di PT. ABC dengan standar keamanan yang berlaku yang sesuai dan mengikuti kebutuhan untuk membantu organisasi. Metodologi yang digunakan dalam penelitian ini adalah studi literatur, analisis data dengan metode reduksi data terhadap 4 standar dan aturan keamanan siber dengan tujuan untuk mengembangkan kerangka kerja keamanan transfer data dengan objek penelitian, yaitu ISO/EIC 27001:2013, NIST SP800- 161, ITU-T X.805, dan POJK 4/POJK.05/2021. Pengembangan kerangka kerja menghasilkan 8 dimensi keamanan, 20 kebutuhan keamanan, dan 41 aktivitas, serta memberikan mitigasi yang dapat meningkatkan sistem keamanan pertukaran data pada koneksi host-to-host di PT. ABC. Evaluasi dilakukan dengan dengan pendekatan professional judgement untuk mengetahui deskripsi penilaian ahli pada setiap variabel pembentuk kerangka kerja berdasarkan melengkapi hasil analisis statistik. Melalui konsep kerangka kerja keamanan transfer data host-to-host yang dihasilkan diharapkan dapat menjadi masukan dalam penyusunan instrumen tingkat kematangan keamanan siber dengan pihak ketiga.

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Data security is an infrastructure designed to protect and secure data from unauthorized access, data manipulation, malfunction, destruction, and inappropriate data disclosure. Currently, organizations widely use data transfer to validate and verify data using different media particularly in host-to-host connections. This research focuses on data exchanged (end-to-end communication) using Multi Protocol Label Switching (MPLS), Metro Ethernet, and Software Defined Wide Area Network (SD-WAN) network architecture with third parties. The risks that arise from cyber attacks on data transfer in host-to-host are data loss, institutional reputation, to the riskiest is the distribution of the data. This research aims to develop a design and analysis framework for verifying data transferred from one host to another in ABC organization by applicable security standards that are appropriate and follow its needs to help the organization. Methodology used in this research is a literature study, data analysis with data reduction method on 4 standards and cyber security policies to develop a data transfer security framework with research objects, namely ISO/EIC 27001:2013, NIST SP800-161, ITU -T X.805, and POJK 4/POJK.05/2021. The framework development resulted in 8 security dimensions, 20 security requirements, and 41 activities, as well as providing mitigations that could improve the security system of data exchange on host-to-host connections at PT. ABC. The evaluation was carried out using a professional judgment approach to determine the description of the expert's judgment on each variable forming the framework based on the complete statistical analysis results. Through the concept of a host-to-host data transfer security framework, it is hoped that it can be used as input in the preparation of cybersecurity maturity level instruments with third parties."

"This book is a comprehensive introduction to the methods and algorithms and approaches of modern data analytics. It covers data preprocessing, visualization, correlation, regression, forecasting, classification, and clustering. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. Much of the content is based on the results of industrial research and development projects at Siemens."

"Semakin meningkatnya kebutuhan akan pengamanan data menyebabkan tingginya permintaan akan data center. Sebagai penyedia jasa layanan data center dengan nilai kontrak yang tidak sedikit perusahaan penyedia jasa layanan data center sepatutnya mengadakan analisa risiko dalam upaya mengurangi pencurian data. Penelitian ini melihat PT ?X? sebagai penyedia jasa data center melakukan analisa risiko kualitatif. Penelitian ini menggunakan metode kualitatif, dengan wawancara dan observasi sebagai teknik mengumpulkan data. Hasil penelitian ini menemukan bahwa PT ?X? belum melakukan analisa risiko dengan melewati tahapan yang baik, masih banyak kebijakan operasional yang diambil berdasarkan common sense dari manajemen

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The increasing need for data security have led to higher demand for data center. As a provider of data center services with a high of contract value, a data center service provider should conduct the risk analysis in an effort to reduce the risk of data theft. The research had observed PT "X" as the provider of data center perform qualitative risk analysis. This study uses qualitative methods, with interviews and observation as a technique to collect data. The results of this study found that PT "X" has not done the risk analysis with a good pass through, there are still many operational policies taken under the common sense of management."