
Data Protection from Insider Threats by Elisa Bertino
As data represent a key asset for today's organizations, the problem of how to protect this data from theft and misuse is at the forefront of these organizations' minds. Even though today several data security techniques are available to protect data and computing infrastructures, many such techniques -- such as firewalls and network security tools -- are unable to protect data from attacks posed by those working on an organization's "inside." These "insiders" usually have authorized access to relevant information systems, making it extremely challenging to block the misuse of information while still allowing them to do their jobs. This book discusses several techniques that can provide effective protection against attacks posed by people working on the inside of an organization. Chapter One introduces the notion of insider threat and reports some data about data breaches due to insider threats. Chapter Two covers authentication and access control techniques, and Chapter Three shows how these general security techniques can be extended and used in the context of protection from insider threats. Chapter Four addresses anomaly detection techniques that are used to determine anomalies in data accesses by insiders. These anomalies are often indicative of potential insider data attacks and therefore play an important role in protection from these attacks. Security information and event management (SIEM) tools and fine-grained auditing are discussed in Chapter Five. These tools aim at collecting, analyzing, and correlating -- in real-time -- any information and event that may be relevant for the security of an organization. As such, they can be a key element in finding a solution to such undesirable insider threats. Chapter Six goes on to provide a survey of techniques for separation-of-duty (SoD). SoD is an important principle that, when implemented in systems and tools, can strengthen data protection from malicious insiders. However, to date, very few approaches have been proposed for implementing SoD in systems. In Chapter Seven, a short survey of a commercial product is presented, which provides different techniques for protection from malicious users with system privileges -- such as a DBA in database management systems. Finally, in Chapter Eight, the book concludes with a few remarks and additional research directions. Table of Contents: Introduction / Authentication / Access Control / Anomaly Detection / Security Information and Event Management and Auditing / Separation of Duty / Case Study: Oracle Database Vault / Conclusion-
Datalog and Logic Databases
-
Blockchain-Enabled Large-Scale Transaction Management
-
Query Processing over Incomplete Databases
-
On Uncertain Graphs
-
Big Data Integration
-
An Introduction to Duplicate Detection
-
Full-Text (Substring) Indexes in External Memory
-
Data-Intensive Workflow Management
-
Database Replication
-
Transaction Processing on Modern Hardware
-
Multidimensional Databases and Data Warehousing
-
Scalable Processing of Spatial-Keyword Queries
-
Generating Plans from Proofs
-
Query Processing over Uncertain Databases
-
Probabilistic Ranking Techniques in Relational Databases
-
Relational and XML Data Exchange
-
The Four Generations of Entity Resolution
-
Advanced Metasearch Engine Technology
-
Privacy-Preserving Data Publishing
-
Data Profiling
-
Non-Volatile Memory Database Management Systems
-
Skylines and Other Dominance-Based Queries
-
Peer-to-Peer Data Management
-
Web Page Recommendation Models
-
Cloud-Based RDF Data Management
-
User-Centered Data Management
-
Uncertain Schema Matching
-
Data Exploration Using Example-Based Methods
-
Querying Graphs
-
Access Control in Data Management Systems
-
Keyword Search in Databases
-
Community Search over Big Graphs
-
Human Interaction with Graphs
-
Data Management in Machine Learning Systems
-
Natural Language Data Management and Interfaces
-
Data Cleaning
-
Blockchains
-
Fault-Tolerant Distributed Transactions on Blockchain
-
Similarity Joins in Relational Database Systems
-
Query Answer Authentication
-
Semantics Empowered Web 3.0
-
Foundations of Data Quality Management
-
Business Processes
-
Information and Influence Propagation in Social Networks
-
Incomplete Data and Data Dependencies in Relational Databases
-
Deep Web Query Interface Understanding and Integration
-
Probabilistic Databases
Elisa Bertino is a professor with the Computer Science Department at Purdue University and serves as research director of CERIAS. Previously, she was a faculty member in the Department of Computer Science and Communication of the University of Milan. Her main research interests include security, privacy, digital identity management systems, database systems, distributed systems, and multimedia systems. She is a fellow of the IEEE and a fellow of the ACM. She received the 2002 IEEE Computer Society Technical Achievement Award for outstanding contributions to database systems and database security and advanced data management systems and the 2005 IEEE Computer Society Tsutomu Kanai Award for pioneering and innovative research contributions to secure distributed systems.
| SKU | Unavailable |
| ISBN 13 | 9783031007620 |
| ISBN 10 | 303100762X |
| Title | Data Protection from Insider Threats |
| Author | Elisa Bertino |
| Series | Synthesis Lectures On Data Management |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer International Publishing AG |
| Year published | 2012-07-12 |
| Number of pages | 77 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |














































