DACSA: A Decoupled Architecture for Cloud Security Analysis



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Transcription:

DACSA: A Decoupled Architecture for Cloud Security Analysis Jason Gionta, William Enck, Peng Ning NC State Ahmed Azab Samsung Ltd Xialoan Zhang Google Inc

Cloud Provider Landscape

Cloud Provider Landscape Steal Degrade Infect Degrade

Cloud Provider Landscape Steal Degrade How to ask security centric questions? Infect Degrade

Unique Features of Cloud Diverse Components and Applications Single Platform Owner Geographically Dispersed

Cloud Infrastructure as a Security Testbed Security Attributes

How to Create a Datasource? Network Monitoring Flow analysis Encrypted network data In-Guest VM Monitoring Virus Scanners / Security Software Application Firewalls Resource Intensive Software Management Host Based Out of VM Monitoring Peer into VM - VMWatcher Record and Replay - Revirt Scalability

How to Create a Datasource? Network Monitoring Flow analysis Encrypted network data In-Guest VM Monitoring Virus Scanners / Security Software Application Firewalls Resource Intensive Software Management Host Based Out of VM Monitoring Peer into VM - VMWatcher Record and Replay - Revirt Scalability Decouple analysis from attribute acquisition

Decoupled Architecture for Analysis Sensor Sensor Sensor Security Attributes

DACSA Sensor Context Acquisition Sensor Context Acquisition Sensor Context Acquisition Context Carver Security Attributes Analysis Tools DACSA Components

DACSA Goals Limit impact to client VMs and hosts Enable analysis on supporting infrastructure Transparent to clients Test for security violations ToS Bots/C&C Malicious software development

Context Acquisition Fast Memory Snapshots Logical memory copy of guest memory COW Limit impact to guest and host Reliable copies Pause guest Flush Asynchronous I/O

Carving Memory Apply memory forensic techniques Extract security centric information Open ports, registry keys, processes, API hooks Hashes of executable pages Forensic tools Volatility Work directly on memory Interpose file I/O

Analysis Clustering of system features Blacksheep Bianchi et al. Memory based virus scanning Memory only malware Security Audit PCI Requirements

Implementation Host Ubuntu 12.04 64-bit Guests Windows 7 SP1 64-bit KVM/QEMU Fork QEMU process Shared library for interposing File I/O Volatility Custom tool for parsing memory Analysis Window 7 GS register to walk internal data structures Scan viruses in memory

Evaluation Platform IBM System X server Xeon E5450 Quad-core Guests 1GB Ram Impact to Guest Impact to Host Correctly identify infected processes

Impact to Guest 1-15 VMs, snapshot VMs, carve process list Pause time Flush Async I/O, Fork QEMU Process, Resume VM ~.2112 seconds / standard deviation.07359 sec Reduction in system performance Run Novabench in snapshotted VM Measure CPU Ops/Sec and Memory Ops/Sec 0-6% CPU, 0-3% Memory

Impact to Host 1-15 VMs, snapshot VMs, carve process list Increased CPU and Memory Utilization ~3% CPU Negligible Memory overhead Write Working Set 100-300 MB per minute

Carving Process Memory Infected VM with Cerberus RAT iexplore.exe host process Carved process memory Scanned memory with ClamAV Identified infected process

Related Work Live VM Migration (Clark et al.) Migrations takes upwards of 90 seconds Performance degradation upto 20% Fast VM Cloning (Sun et al.) COW based by write protecting pages Technical challenges of cloning

Conclusion DACSA turns clouds into a platform for security analysis VMs lightweight sensors Minimal impact to VM and host operations Apply large scale analysis Future Work Deploy to Virtual Computing Lab at NC State Memory Scanning as a Service

Questions? Thanks Reviewers insightful comments Eric Eide for shepherding jjgionta@ncsu.edu