This SpringerBrief discusses underlying principles of malware reverse engineering and introduces the major techniques and tools needed to effectively analyze malware that targets business organizations. It also covers the examination of real-world malware samples, which illustrates the knowledge and skills necessary to take control of cyberattacks.
This SpringerBrief explores key tools and techniques to learn the main elements of malware analysis from the inside out. It also presents malware reverse engineering using several methodical phases, in order to gain a...
This SpringerBrief discusses underlying principles of malware reverse engineering and introduces the major techniques and tools needed to effecti...
This book addresses several knowledge discovery problems on multi-sourced data where the theories, techniques, and methods in data cleaning, data mining, and natural language processing are synthetically used. This book mainly focuses on three data models: the multi-sourced isomorphic data, the multi-sourced heterogeneous data, and the text data. On the basis of three data models, this book studies the knowledge discovery problems including truth discovery and fact discovery on multi-sourced data from four important properties: relevance, inconsistency, sparseness, and heterogeneity,...
This book addresses several knowledge discovery problems on multi-sourced data where the theories, techniques, and methods in data cleaning, data...
This book presents the state of the art for multi-party fair exchange protocols and provides insight details regarding multi-party applications for buying physical products. The authors tackle the fairness problem in e-commerce protocols for buying physical products in scenarios involving complex and chained transactions and provide use cases of these protocols for B2C and B2B scenarios. The book also includes the formal verification of the fair multi-party exchange e-commerce protocols using the Constraint-Logic-based Attack Searcher from AVISPA, a tool for the Automated Validation of...
This book presents the state of the art for multi-party fair exchange protocols and provides insight details regarding multi-party applications for...
This book provides basic knowledge about main memory management in relational databases as it is needed to support large-scale applications processed completely in memory. In business operations, real-time predictability and high speed is a must. Hence every opportunity must be exploited to improve performance, including reducing dependency on the hard disk, adding more memory to make more data resident in the memory, and even deploying an in-memory system where all data can be kept in memory.
The book provides one chapter for each of the main related topics, i.e. the memory...
This book provides basic knowledge about main memory management in relational databases as it is needed to support large-scale applications process...
This SpringerBrief introduces methodologies and tools for quantitative understanding and assessment of supply chain risk to critical infrastructure systems. It unites system reliability analysis, optimization theory, detection theory and mechanism design theory to study vendor involvement in overall system security. It also provides decision support for risk mitigation.
This SpringerBrief introduces I-SCRAM, a software tool to assess the risk. It enables critical infrastructure operators to make risk-informed decisions relating to the supply chain, while deploying their IT/OT...
This SpringerBrief introduces methodologies and tools for quantitative understanding and assessment of supply chain risk to critical infrastructure...
Emerging machine learning techniques bring new opportunities to flexible network control and management. This book focuses on using state-of-the-art machine learning-based approaches to improve the performance of Software-Defined Networking (SDN). It will apply several innovative machine learning methods (e.g., Deep Reinforcement Learning, Multi-Agent Reinforcement Learning, and Graph Neural Network) to traffic engineering and controller load balancing in software-defined wide area networks, as well as flow scheduling, coflow scheduling, and flow migration for network function virtualization...
Emerging machine learning techniques bring new opportunities to flexible network control and management. This book focuses on using state-of-the-art m...
This book is intended as an introduction to a versatile model for temporal data. It exhibits an original lattice structure on the space of chronicles and proposes new counting approach for multiple occurrences of chronicle occurrences. This book also proposes a new approach for frequent temporal pattern mining using pattern structures. This book was initiated by the work of Ch. Dousson in the 1990’s. At that time, the prominent format was Temporal Constraint Networks for which the article by Richter, Meiri and Pearl is seminal.
Chronicles do not conflict with temporal...
This book is intended as an introduction to a versatile model for temporal data. It exhibits an original lattice structure on the space of chronicl...
This book mainly shows readers how to calibrate and control robots. In this regard, it proposes three control schemes: an error-summation enhanced Newton algorithm for model predictive control; RNN for solving perturbed time-varying underdetermined linear systems; and a new joint-drift-free scheme aided with projected ZNN, which can effectively improve robot control accuracy. Moreover, the book develops four advanced algorithms for robot calibration – Levenberg-Marquarelt with diversified regularizations; improved covariance matrix adaptive evolution strategy; quadratic interpolated...
This book mainly shows readers how to calibrate and control robots. In this regard, it proposes three control schemes: an error-summation enhanced ...
This book provides a broad overview of the key results and frameworks for various NSAI tasks as well as discussing important application areas. This book also covers neuro symbolic reasoning frameworks such as LNN, LTN, and NeurASP and learning frameworks. This would include differential inductive logic programming, constraint learning and deep symbolic policy learning. Additionally, application areas such a visual question answering and natural language processing are discussed as well as topics such as verification of neural networks and symbol grounding. Detailed...
This book provides a broad overview of the key results and frameworks for various NSAI tasks as well as discussing important application areas.&nbs...
Document layout analysis (DLA) is a crucial step towards the development of an effective document image processing system. In the early days of document image processing, DLA was not considered as a complete and complex research problem, rather just a pre-processing step having some minor challenges. The main reason for that is the type of layout being considered for processing was simple. Researchers started paying attention to this complex problem as they come across a large variety of documents. This book presents a clear view of the past, present, and future of DLA, and it also...
Document layout analysis (DLA) is a crucial step towards the development of an effective document image processing system. In the early days of doc...
