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This book captures the state of the art research in the area of malicious code detection, prevention and mitigation. It contains cutting-edge behavior-based techniques to analyze and detect obfuscated malware. The book analyzes current trends in malware activity online, including botnets and malicious code for profit, and it proposes effective models for detection and prevention of attacks using. Furthermore, the book introduces novel techniques for creating services that protect their own integrity and safety, plus the data they manage.
The modern society is rapidly becoming a fully digital society. This has many benefits, but unfortunately it also means that personal privacy is threatened. The threat does not so much come from a 1984 style Big Brother, but rather from a set of smaller big brothers. The small big brothers are companies that we interact with; they are public services and institutions. Many of these little big brothers are indeed also being invited to our private data by ourselves. Privacy as a subject can be problematic. At the extreme it is personal freedom against safety and security. We shall not take a political stand on personal privacy and what level of personal freedom and privacy is the correct one.A...
Botnets have become the platform of choice for launching attacks and committing fraud on the Internet. A better understanding of Botnets will help to coordinate and develop new technologies to counter this serious security threat. Botnet Detection: Countering the Largest Security Threat consists of chapters contributed by world-class leaders in this field, from the June 2006 ARO workshop on Botnets. This edited volume represents the state-of-the-art in research on Botnets.
Intended for advanced level students in computer science and mathematics, this key text, now in a brand new edition, provides a survey of recent progress in primality testing and integer factorization, with implications for factoring based public key cryptography. For this updated and revised edition, notable new features include a comparison of the Rabin-Miller probabilistic test in RP, the Atkin-Morain elliptic curve test in ZPP and the AKS deterministic test.
This volume contains the proceedings of the International Conference on Computer Aided Veri?cation (CAV), held in Edinburgh, Scotland, July 6–10, 2005. CAV 2005 was the seventeenth in a series of conferences dedicated to the advancement of the theory and practice of computer-assisted formal an- ysis methods for software and hardware systems. The conference covered the spectrum from theoretical results to concrete applications, with an emphasis on practical veri?cation tools and the algorithms and techniques that are needed for their implementation. We received 123 submissions for regular papers and 32 submissions for tool papers.Ofthesesubmissions,theProgramCommitteeselected32regularpapers...
This book addresses the privacy issue of On-Line Analytic Processing (OLAP) systems. OLAP systems usually need to meet two conflicting goals. First, the sensitive data stored in underlying data warehouses must be kept secret. Second, analytical queries about the data must be allowed for decision support purposes. The main challenge is that sensitive data can be inferred from answers to seemingly innocent aggregations of the data. This volume reviews a series of methods that can precisely answer data cube-style OLAP, regarding sensitive data while provably preventing adversaries from inferring data.
DATA EXFILTRATION THREATS AND PREVENTION TECHNIQUES Comprehensive resource covering threat prevention techniques for data exfiltration and applying machine learning applications to aid in identification and prevention Data Exfiltration Threats and Prevention Techniques provides readers the knowledge needed to prevent and protect from malware attacks by introducing existing and recently developed methods in malware protection using AI, memory forensic, and pattern matching, presenting various data exfiltration attack vectors and advanced memory-based data leakage detection, and discussing ways in which machine learning methods have a positive impact on malware detection. Providing detailed de...
This book constitutes the refereed proceedings of the 23rd International Conference on Automated Deduction, CADE-23, held in Wrocław, Poland, in July/August 2011. The 28 revised full papers and 7 system descriptions presented were carefully reviewed and selected from 80 submissions. Furthermore, four invited lectures by distinguished experts in the area were included. Among the topics addressed are systems and tools for automated reasoning, rewriting logics, security protocol verification, unification, theorem proving, clause elimination, SAT, satifiability, interactive theorem proving, theory reasoning, static analysis, decision procedures, etc.
This book constitutes the refereed proceedings of the 13th International Symposium on Recent Advances in Intrusion Detection, RAID 2010, held in Ottawa, Canada, in September 2010. The 24 revised full papers presented together with 15 revised poster papers were carefully reviewed and selected from 102 submissions. The papers are organized in topical sections on network protection, high performance, malware detection and defence, evaluation, forensics, anomaly detection as well as web security.
The popularity of Android mobile phones has caused more cybercriminals to create malware applications that carry out various malicious activities. The attacks, which escalated after the COVID-19 pandemic, proved there is great importance in protecting Android mobile devices from malware attacks. Intelligent Mobile Malware Detection will teach users how to develop intelligent Android malware detection mechanisms by using various graph and stochastic models. The book begins with an introduction to the Android operating system accompanied by the limitations of the state-of-the-art static malware detection mechanisms as well as a detailed presentation of a hybrid malware detection mechanism. The...