Abbildung von: Data and Applications Security and Privacy XXXIII - Springer

Data and Applications Security and Privacy XXXIII

33rd Annual IFIP WG 11.3 Conference, DBSec 2019, Charleston, SC, USA, July 15-17, 2019, Proceedings

Simon N. Foley(Herausgeber*in)

Springer (Verlag)

Erschienen am 4. Juli 2019

XI, 419 Seiten

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Inhalt

Intro
Preface
Organization
Contents
Attacks
Detecting Adversarial Attacks in the Context of Bayesian Networks
1 Introduction
2 Problem Setting
3 Long-Duration Data Poisoning Attacks
4 Framework for Detecting Data Poisoning Attacks
5 Empirical Results
5.1 One-Step Data Poisoning Attacks
5.2 Long-Duration Data Poisoning Attacks
5.3 Discussion: Detecting Data Poisoning Attacks
6 Related Work
7 Conclusion and Future Work
A Causative, Long-duration Model Invalidation Attacks
References
AGBuilder: An AI Tool for Automated Attack Graph Building, Analysis, and Refinement
1 Introduction
2 Attack Graph Modeling Using PDDL
3 Our Approach for Automated Attack Graph Generation and Refinement
3.1 Automatically Generating PDDL Domain from Natural Language Textual Descriptions
3.2 Incremental Building and Refinement of the Attack Graph
4 AGBuilder Modules
4.1 Knowledge Base Components
4.2 AGBuilder Processing Modules
4.3 Working Example of Explanation Constructor
5 Related Work
6 Conclusion and Future Work
References
On Practical Aspects of PCFG Password Cracking
1 Introduction
1.1 Contribution
1.2 Structure of the Paper
2 Background and Related Work
3 Enhancements to PCFG
3.1 Key Observations
3.2 Long Base Structures
3.3 Calculating the Number of Password Candidates
3.4 The New PCFG Manager
3.5 Grammar Filtering
4 Experimental Results
4.1 The Performance of PCFG Manager
4.2 The Impact of PCFG Filtering
4.3 Evaluation
5 Conclusion
References
That's My DNA: Detecting Malicious Tampering of Synthesized DNA
1 Introduction
2 Limitations of Earlier Work and Current Contributions
2.1 Cyclic Shifts and Reverse Complement
2.2 Mutations in Identifying Tags
2.3 Signature Length
3 DNA Signature Generation and Verification Procedure
4 Allowing Mutations in Start and End Tags
5 New Identity-Based Signature Scheme with Shorter Signature Size
6 Conclusion and Future Work
References
Mobile and Web Security
Adversarial Sampling Attacks Against Phishing Detection
1 Introduction
1.1 Motivation
1.2 Problem Statement
1.3 Proposed Approach and Key Contributions
2 Related Work
2.1 Machine Learning for Phishing Detection
2.2 Learning in Adversarial Context
3 Threat Model
3.1 Attacker's Goal
3.2 Attacker's Knowledge
3.3 Attacker Influence
4 Adversarial Sampling for Phishing
4.1 Defining the Dataset
4.2 Selecting Features for Manipulation
4.3 Adversary Cost
4.4 Vulnerability Level
5 Experiments and Results
5.1 Used Datasets
5.2 Exp-1: Evaluation of Datasets
5.3 Generating Adversarial Samples
5.4 Exp-2: Robustness of Learning Model
5.5 Exp-3: Dataset Vulnerability Level
5.6 Comparing the Results with Previous Experiments
6 Conclusion and Future Work
References
Is My Phone Listening in? On the Feasibility and Detectability of Mobile Eavesdropping
Abstract
1 Introduction
2 Threat Model
3 Microphone-Based Eavesdropping
3.1 Microphone Access Permission
3.2 User Notifications and Visibility
4 Motion Sensor-Based Eavesdropping
4.1 Experimental Research Findings
4.2 Sampling Frequency Limits
4.3 Sensor Access Permissions and Energy Efficiency
5 Existing Mitigation and Detection Techniques
5.1 App Inspections Conducted by Ecosystem Providers
5.2 App Inspections Conducted by the Research Community
6 Ecosystem Providers as Potential Adversaries
7 Technical and Economic Feasibility
8 Unauthorized Access to Smartphones
9 Discussion
10 Conclusion
References
Droids in Disarray: Detecting Frame Confusion in Hybrid Android Apps
1 Introduction
2 Technical Background
2.1 Frame Confusion
3 A Frame Confusion Detection Methodology
3.1 Vulnerability Blueprint
3.2 Detection Algorithm
4 The FCDroid tool
4.1 Implementation Challenges
4.2 FCDroid Architecture
5 Experimental Results
6 Attacking and Exploiting the Frame Confusion
7 Related Work
8 Conclusion
References
Privacy
Geo-Graph-Indistinguishability: Protecting Location Privacy for LBS over Road Networks
1 Introduction
2 Preliminary and Problem Setting
2.1 Geo-Indistinguishability geospsi
2.2 Problem Statement
3 Evaluating Privacy and Utility of Geo-Indistinguishability
3.1 Empirical Privacy Evaluation
3.2 Utility
4 Geo-Graph-Indistinguishability
4.1 Definition
4.2 Graph Exponential Mechanism
4.3 Analyzing the Relationship Between GeoI and GeoGI
4.4 Discussion
5 Experiments
5.1 Privacy Protection Level of GEM
5.2 Utility of GEM
6 Related Work
6.1 Location Privacy on a Road Network
6.2 State-of-the-Art Privacy Models
7 Conclusion and Future Work
8 Appendix
8.1 Proofs
8.2 dX-privacy
8.3 Pseudocode of GEM
References
``When and Where Do You Want to Hide?'' - Recommendation of Location Privacy Preferences with Local Differential Privacy
1 Introduction
2 Preliminaries
2.1 Matrix Factorization
2.2 Local Differential Privacy
2.3 Definition of the Location Privacy Preference
3 Recommendation Method
3.1 Framework
3.2 Addition of Noise
4 Evaluation
4.1 Overview
4.2 Dataset
4.3 Metrics
4.4 Evaluation Process
4.5 Results
5 Conclusion
References
Analysis of Privacy Policies to Enhance Informed Consent
1 Introduction
2 The Privacy Policy Language Pilot
2.1 Basic Definitions
2.2 Abstract Syntax of Pilot Privacy Policies
2.3 Example: Vehicle Tracking
3 Abstract Execution Model
3.1 System State
3.2 System Events
4 Risk Analysis
4.1 Automatic Risk Analysis with SPIN
4.2 Case Study: Vehicle Tracking
4.3 Usability
5 Related Work
6 Conclusion
A Policy Subsumption
B Active Policies and Transfer Rules
C Policy Join
References
Security Protocol Practices
Lost in TLS? No More! Assisted Deployment of Secure TLS Configurations
1 Introduction
2 Background
2.1 TLS
2.2 Vulnerabilities
3 Tools Comparison
3.1 Mobile Clients
4 Mitigations Identification
5 TLSAssistant
5.1 Architecture
6 Experimental Evaluation
6.1 Use-Case: CIE 3.0
6.2 User Study
7 Conclusions and Future Work
A Post-questionnaire
B Report snippet
References
Contributing to Current Challenges in Identity and Access Management with Visual Analytics
1 Introduction
2 Background and Related Work
2.1 Background
2.2 Related Work
3 IAM Challenges
3.1 Approach for Identifying Challenges
3.2 Literature Survey
3.3 Practitioner's View
3.4 IAM Challenges
4 Applying Visual Analytics to IAM
4.1 Data Sources
4.2 Data Preparation
4.3 Data Visualization
5 Exemplary Use Cases
5.1 Identities Not Managed Within a Central IAM (C1, C4)
5.2 Identities with an Unusual Number of Entitlements (C3)
5.3 Poor Data Quality in IAM Data (C4)
6 Conclusion
References
Analysis of Multi-path Onion Routing-Based Anonymization Networks
1 Introduction
2 Related Work
3 Multi-path in Anonymization Systems
3.1 Conflux
3.2 mTor
3.3 MORE
3.4 mUDP-OR
4 Classifying Design Choices
4.1 Traffic Management
4.2 Circuit Construction
4.3 Path Selection
5 Performance Evaluation
5.1 Private Local Network Experiment
5.2 Larger-Scale Experiment
5.3 Design Recommendations
6 Anonymity Analysis
6.1 Client Multi-path Circuits Compromise
6.2 Using Multiple Entry Onion Routers
7 Conclusions and Future Work
References
Distributed Systems
Shoal: Query Optimization and Operator Placement for Access Controlled Stream Processing Systems
1 Introduction
2 Background and System Model
2.1 Background on DDSPSs
2.2 Access Controls
3 Problem Description
3.1 Problem Description
3.2 Optimize-then-place Approach
4 The Shoal Optimizer
4.1 Online Optimization Approach
4.2 Greedy and Hybrid Approaches
4.3 Example
5 Evaluation
5.1 Online Optimizer
5.2 Comparison to the State-of-the-Art
6 Related Work
7 Conclusion
References
A Distributed Ledger Approach to Digital Twin Secure Data Sharing
1 Introduction
2 Background
3 Problem Statement
3.1 Digital Twin Model
3.2 A Formal Basis for Secure Digital Twin Data Sharing
3.3 Requirements for Secure DT Data Sharing
4 Solution Architecture
4.1 Technology Selection
4.2 System Architecture
4.3 Data Storage
4.4 Capabilities
4.5 Setup Process
5 Use Case
5.1 Setting
5.2 Framework Iteration
5.3 Results
6 Evaluation
6.1 Requirements Fulfillment
6.2 Discussion
7 Conclusion
References
Refresh Instead of Revoke Enhances Safety and Availability: A Formal Analysis
1 Introduction
2 Related Work
3 System Model and Assumptions
3.1 Refresh Vs. Revocation
3.2 System Assumptions
4 Consistency Levels Formal Characterization
4.1 Preliminaries
4.2 Interval Consistency
4.3 Interval Consistency with Request Time
4.4 Forward-Looking Consistency
5 Limitations and Practical Issues
6 Conclusion
References
Source Code Security
Wrangling in the Power of Code Pointers with ProxyCFI
1 Introduction
1.1 Contributions of This Paper
2 Protecting Control Flow with ProxyCFI
2.1 Threat Model
2.2 Pointer Proxies
2.3 Building Code with Pointer Proxies
2.4 Load-Time Program Verifier
2.5 Deterring CFG Mimicry Attacks
2.6 Shared Libraries with Pointer Proxies
3 ProxyCFI in GNU GCC
3.1 Compilation Flow
3.2 ProxyCFI Optimizations
4 Evaluation
4.1 Evaluation Framework
4.2 Performance Analysis
4.3 Security Analysis
5 Related Work
6 Conclusion
A Redis-benchmark Results Breakdown
References
CASFinder: Detecting Common Attack Surface
1 Introduction
2 Preliminaries
2.1 Motivating Example
2.2 Background
3 The Model of Common Attack Surface
3.1 Conditional Common Attack Surface (CCAS) Metric
3.2 Probabilistic Common Attack Surface Metric
4 Design and Implementation
5 Experiments
5.1 Dataset
5.2 Cross-Category Common Attack Surface
5.3 Common Attack Surface in the Same Category
6 Related Work
7 Conclusion
References
Algorithm Diversity for Resilient Systems
1 Introduction
2 Background on DistAlgo
3 Creating Variants Using Incrementalization
4 Synchronized Execution for DistAlgo
5 Diversity Metrics and Runtime Monitoring Tools
5.1 Code Diversity
5.2 Trace Diversity
5.3 Input Access Diversity
6 Evaluation
6.1 Sequential Algorithms
6.2 Distributed Algorithms
7 Related Work
7.1 Evaluation of Diversity Techniques
References
Malware
Online Malware Detection in Cloud Auto-scaling Systems Using Shallow Convolutional Neural Networks
1 Introduction
2 Related Work
3 Key Intuition
4 Methodology
4.1 Malware Detection in Multiple VMs Using Single Samples (MVSS)
4.2 Malware Detection in Multiple VMs Using Paired Samples (MVPS)
5 Experiment Setup and Results
5.1 CNN Model Architecture
5.2 Experimental Setup
5.3 Evaluation
5.4 MVSS and MVPS Results
6 Conclusion and Future Work
References
Redirecting Malware's Target Selection with Decoy Processes
1 Introduction
2 Honeypot Experiment
3 Decoy Processes
4 Performance Support for a Decoy Process
4.1 Heatmaps
4.2 Deep Learning of Performance Fingerprints
5 Experimental Testing and Validation
6 Related Work
7 Conclusions
References
Author Index

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