Igor Linkov

52 papers A 1B 2C 6Misc 1Journal 37Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
IEEE Open J. Commun. Soc.
Mohammed Tanvir Masud, Marwa Keshk, Nour Moustafa, Igor Linkov, Darren K. Emge
2025 C conf
CoDIT
Davis C. Loose, Megan C. Marcellin, Igor Linkov, Gigi Pavur, Maksim Kitsak, Michael A. Deegan, James H. Lambert
2025 conf
SysCon
Davis C. Loose, Megan C. Marcellin, Igor Linkov, Gigi Pavur, Maksim A. Kitsak, Michael A. Deegan, James H. Lambert
2025 C conf
CoDIT
Matthew C. Gunn, Davis C. Loose, Megan C. Marcellin, Megan E. Gunn, Gigi Pavur, Benjamin D. Trump, Igor Linkov, James H. Lambert
2025 C conf
CoDIT
Megan C. Marcellin, Gigi Pavur, Davis C. Loose, Benjamin D. Trump, Igor Linkov, James H. Lambert
2024 C conf
CoDIT
DeAndre A. Johnson, Benjamin D. Trump, Megan C. Marcellin, Gigi Pavur, Davis C. Loose, Saddam Q. Waheed, Thomas L. Polmateer, Igor Linkov, Venkataraman Lakshmi, John J. Cárdenas, James H. Lambert
2024 J jnl
Commun. ACM
Andrew Strelzoff, Benjamin D. Trump, Christopher L. Cummings, Madison Smith, Stephanie Elisabeth Galaitsi, Kelsey Stoddard, Jeffrey M. Keisler, Moshe Y. Vardi, Nathaniel D. Bastian, Alexander Kott, Igor Linkov
2024 C conf
CoDIT
Gigi Pavur, Benjamin J. Trump, Igor Linkov, Thomas L. Polmateer, James H. Lambert, Venkataraman Lakshmi
2024 J jnl
Syst.
Negin Moghadasi, Rupa S. Valdez, Misagh Piran, Negar Moghaddasi, Igor Linkov, Thomas L. Polmateer, Davis C. Loose, James H. Lambert
2024 J jnl
Computer
Alexander Kott, George Yegor Dubynskyi, Andrii Paziuk, Stephanie Elisabeth Galaitsi, Benjamin D. Trump, Igor Linkov
2024 J jnl
CoRR
Alexander Kott, George Yegor Dubynskyi, Andrii Paziuk, Stephanie E. Galaitsi, Benjamin D. Trump, Igor Linkov
2024 C conf
CoDIT
Zachary A. Collier, Elvie Sellers, Davis C. Loose, Igor Linkov, James H. Lambert
2023 J jnl
IEEE Trans. Intell. Transp. Syst.
Ayodeji Oseni, Nour Moustafa, Gideon Creech, Nasrin Sohrabi, Andrew Strelzoff, Zahir Tari, Igor Linkov
2023 J jnl
Commun. ACM
Igor Linkov, Alexandre K. Ligo, Kelsey Stoddard, Beatrice Perez, Andrew Strelzoff, Emanuele Bellini, Alexander Kott
2023 conf
UEMCON
Zachary A. Collier, Davis C. Loose, Elvie Sellers, Thomas L. Polmateer, Madhur Behl, Igor Linkov, James H. Lambert
2023 conf
CyCon
Igor Linkov, Kelsey Stoddard, Andrew Strelzoff, Stephanie Elisabeth Galaitsi, Jeffrey M. Keisler, Benjamin D. Trump, Alexander Kott, Pavol Bielik, Petar Tsankov
2022 J jnl
CoRR
Alexandre K. Ligo, Alexander Kott, Igor Linkov
2022 J jnl
CoRR
Alexander Kott, Maureen S. Golan, Benjamin D. Trump, Igor Linkov
2022 J jnl
CoRR
Stephanie Elisabeth Galaitsi, Benjamin D. Trump, Jeffrey M. Keisler, Igor Linkov, Alexander Kott
2022 J jnl
CoRR
Maksim Kitsak, Alexander A. Ganin, Ahmed Elmokashfi, Hongzhu Cui, Daniel A. Eisenberg, David L. Alderson, Dmitry Korkin, Igor Linkov
2021 J jnl
Computer
Alexandre K. Ligo, Alexander Kott, Igor Linkov
2021 J jnl
Frontiers Comput. Sci.
Alexandre K. Ligo, Krista Rand, Jason Bassett, Stephanie Elisabeth Galaitsi, Benjamin D. Trump, Bamini Jayabalasingham, Thomas Collins, Igor Linkov
2021 J jnl
CoRR
Emanuele Bellini, Franco Bagnoli, Alexander A. Ganin, Igor Linkov
2021 J jnl
Computer
Alexander Kott, Maureen S. Golan, Benjamin D. Trump, Igor Linkov
2021 J jnl
CoRR
Alexandre K. Ligo, Alexander Kott, Igor Linkov
2021 Misc conf
CSR
Emanuele Bellini, Franco Bagnoli, Mauro Caporuscio, Ernesto Damiani, Francesco Flammini, Igor Linkov, Pietro Liò, Stefano Marrone
2021 J jnl
Ind. Manag. Data Syst.
Maureen S. Golan, Benjamin D. Trump, Jeffrey C. Cegan, Igor Linkov
2021 J jnl
Int. J. Inf. Manag.
Stephanie Elisabeth Galaitsi, Jeffrey C. Cegan, Kaitlin Volk, Matthew Joyner, Benjamin D. Trump, Igor Linkov
2021 J jnl
Computer
Alexander Kott, Igor Linkov
2021 J jnl
CoRR
Alexander Kott, Igor Linkov
2020 J jnl
Computer
Igor Linkov, Stephanie Elisabeth Galaitsi, Benjamin D. Trump, Jeffrey M. Keisler, Alexander Kott
2019 J jnl
IEEE Secur. Priv.
Igor Linkov, Fabrizio Baiardi, Marie-Valentine Florin, Scott Greer, James H. Lambert, Miriam Pollock, Jean-Marc Rickli, Lada Roslycky, Thomas P. Seager, Heimir Thorisson, Benjamin D. Trump
2019 B conf
SERVICES
Emanuele Bellini, Franco Bagnoli, Alexander A. Ganin, Igor Linkov
2019 J jnl
Frontiers Artif. Intell.
Stephanie Elisabeth Galaitsi, Christine Ogilvie Hendren, Benjamin D. Trump, Igor Linkov
2019 J jnl
CoRR
Stephanie Elisabeth Galaitsi, Benjamin D. Trump, Jeffrey M. Keisler, Igor Linkov
2018 J jnl
CoRR
Alexander Kott, Benjamin A. Blakely, Diane Henshel, Gregory Wehner, James Rowell, Nathaniel Evans, Luis Muñoz-González, Nandi Leslie, Donald W. French, Donald Woodard, Kerry Krutilla, Amanda Joyce, Igor Linkov, Carmen Mas Machuca, Janos Sztipanovits, Hugh Harney, Dennis Kergl, Perri Nejib, Edward Yakabovicz, Steven Noel, Tim Dudman, Pierre Trepagnier, Sowdagar Badesha, Alfred Møller
2018 J jnl
CoRR
Igor Linkov, Alexander Kott
2018 J jnl
IEEE Access
Daniel A. Eisenberg, David L. Alderson, Maksim Kitsak, Alexander A. Ganin, Igor Linkov
2018 J jnl
Reliab. Eng. Syst. Saf.
T. P. Bostick, Elizabeth B. Connelly, James H. Lambert, Igor Linkov
2016 J jnl
Eur. J. Oper. Res.
Elisabeth C. Paulson, Igor Linkov, Jeffrey M. Keisler
2016 ch.
Handbook of Science and Technology Convergence
Igor Linkov, Viktoria Gisladottir, Matthew D. Wood
2015 J jnl
CoRR
Zachary A. Collier, Mahesh Panwar, Alexander A. Ganin, Alexander Kott, Igor Linkov
2014 J jnl
Environ. Model. Softw.
M. L. Chu, Jorge A. Guzman, Rafael Muñoz-Carpena, Gregory A. Kiker, Igor Linkov
2014 J jnl
Computer
Zachary A. Collier, Daniel DiMase, Steve Walters, Mark Mohammad Tehranipoor, James H. Lambert, Igor Linkov
2014 J jnl
Environ. Model. Softw.
Matteo Convertino, Rafael Muñoz-Carpena, Maria Librada Chu-Agor, Gregory A. Kiker, Igor Linkov
2013 J jnl
EAI Endorsed Trans. Complex Syst.
Matteo Convertino, Filippo Simini, Filippo Catani, Igor Linkov, Gregory A. Kiker
2012 A conf
AAMAS
Philip Hendrix, Elena O. Budrene, Igor Linkov, Benoit Morel
2011 J jnl
Environ. Model. Softw.
Maria Librada Chu-Agor, Rafael Muñoz-Carpena, Gregory A. Kiker, A. Emanuelsson, Igor Linkov
2011 J jnl
IEEE Trans. Syst. Man Cybern. Part A
Christopher W. Karvetski, James H. Lambert, Jeffrey M. Keisler, Igor Linkov
2010 J jnl
Int. J. Inf. Syst. Soc. Chang.
Boris Yatsalo, Vladimir Didenko, Alexander Tkachuk, Sergey Gritsyuk, Oleg Mirzeabasov, Valeria Slipenkaya, Alexey Babutski, Irina Pichugina, Terry Sullivan, Igor Linkov
2009 B conf
SMC
Igor Linkov, Matthew D. Wood, Todd Bridges, Daniel Kovacs, Sarah Thorne, Gordon Butte
2007 conf
EnviroInfo (2)
Alexandre Grebenkov, Boris Yatsalo, Terry Sullivan, Igor Linkov
Docker-README.md
← Index Docker-README.md markdown
# REDB Docker Setup

This document describes the Docker containerization for the REDB malware analysis framework.

## Overview

REDB has been containerized as a single unified image that supports both feature extraction and decompilation analysis. The container is stateless, processes files from S3 or local mounts, and exports results to ClickHouse database or via API callbacks.

## Architecture

- **Single Unified Container**: One image handles both feature extraction and decompilation
- **Runtime Tool Installation**: Tools (CAPA, DIE, Binary Ninja) installed at runtime from host snapshots
- **Stateless Processing**: No persistent storage required between runs
- **Multiple Invocation Modes**: Supports `--nomad-job`, `--s3`, `--s3-solo`, and `--path` modes
- **External Dependencies**: Connects to external ClickHouse and S3 services

## Files Structure

```
├── Dockerfile                 # Single unified container definition
├── docker-build.sh            # Build script with Docker Desktop bug workaround
├── docker-push.sh             # Push script to registry
├── test-docker.sh             # Container testing script
├── test-nomad.sh              # Nomad job mode testing
├── .dockerignore              # Build context exclusions
└── scripts/
    └── setup-and-run.sh       # Runtime tool setup entrypoint
```

## Tool Installation Strategy

The container uses a **runtime installation** approach:

1. **Base Image**: Contains Python dependencies and REDB code
2. **Runtime Setup**: `scripts/setup-and-run.sh` configures tools at container start
3. **Host Snapshots**: Binary Ninja installed from `/opt/binaryninja` if available
4. **System Tools**: CAPA and DIE expected at `/usr/bin/capa` and `/usr/bin/nfdc`

## Build and Run

### 1. Build Container

```bash
# Build unified image
./docker-build.sh

# Manual build
docker build --platform linux/amd64 -f Dockerfile -t redb:latest .
```

### 2. Run Modes

#### Nomad Job Mode (Primary)
```bash
# Feature extraction
docker run --rm \
  -e JOB_ID="analysis_001" \
  -e S3_KEY="samples/malware.exe" \
  -e S3_BUCKET="malware-bucket" \
  -e WORKER_TYPE="feature_extraction" \
  -e CALLBACK_URL="https://api.example.com/callbacks" \
  -e ANALYSIS_MODULES="BasicPropertiesExtractor,PEFeaturesExtractor" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e S3_ACCESS_KEY="your-key" \
  -e S3_SECRET_KEY="your-secret" \
  redb:latest python3 start.py --nomad-job

# Decompilation (same container, different flags)
docker run --rm \
  -e JOB_ID="analysis_002" \
  -e S3_KEY="samples/malware.exe" \
  -e S3_BUCKET="malware-bucket" \
  -e WORKER_TYPE="decompilation" \
  -e CALLBACK_URL="https://api.example.com/callbacks" \
  -e ANALYSIS_MODULES="all" \
  -v /opt/binaryninja:/opt/binaryninja:ro \
  redb:latest python3 start.py --nomad-job --decompile
```

#### S3 Solo Mode
```bash
# Process single sample by S3 key (standard sharded path)
docker run --rm \
  -e S3_BUCKET="samples-bucket" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e INDEX_PREFIX="redb" \
  -e REPO="test-analysis" \
  redb:latest python3 start.py --s3-solo "09/f7/09f7d02a3c2382199458c98a62b045145ee54ab6aba86166aecf3d10c3c1444c.zip"

# Process private sample (with prepath)
docker run --rm \
  -e S3_BUCKET="samples-bucket" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e INDEX_PREFIX="redb" \
  -e REPO="test-analysis" \
  redb:latest python3 start.py --s3-solo "private/ab/cd/abcd1234567890abcdef1234567890abcdef1234567890abcdef123456.zip"
```

#### Local Files Mode
```bash
# Mount local samples
docker run --rm \
  -v /path/to/samples:/samples:ro \
  -v ./logs:/app/logs \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  redb:latest python3 start.py --path /samples --repo local_test --index_prefix redb
```

## Environment Variables

### Required for Nomad Job Mode
- `JOB_ID` - Unique job identifier
- `S3_KEY` - S3 object key for sample
- `S3_BUCKET` - S3 bucket name
- `WORKER_TYPE` - "feature_extraction" or "decompilation"
- `CALLBACK_URL` - API endpoint for results
- `ANALYSIS_MODULES` - Comma-separated extractor list or "all"

### Database Configuration
- `CLICKHOUSE_HOST` - ClickHouse server hostname
- `CLICKHOUSE_PORT` - Port (default: 8123)
- `CLICKHOUSE_USER` - Database user (default: default)
- `CLICKHOUSE_PASSWORD` - Database password
- `CLICKHOUSE_DATABASE` - Database name (default: default)

### S3 Configuration
- `S3_ENDPOINT` - S3 endpoint URL
- `S3_ACCESS_KEY` - S3 access key
- `S3_SECRET_KEY` - S3 secret key
- `S3_SECURE` - "true" or "false" for HTTPS

### Processing Configuration
- `INDEX_PREFIX` - Database table prefix (default: redb)
- `REPO` - Repository identifier for this analysis batch
- `BATCH_SIZE` - Processing batch size (default: 10)
- `REDB_TIMEOUT` - Analysis timeout in seconds (default: 300)

### Tool Timeouts
- `CAPA_TIMEOUT` - CAPA analysis timeout (default: 300)
- `DIE_TIMEOUT` - DIE analysis timeout (default: 180)
- `BINJA_TIMEOUT` - Binary Ninja timeout (default: 1200)
- `DECOMPILE_EXTRACTOR_TIMEOUT` - Decompilation timeout (default: 2580)

## Binary Ninja Setup

For decompilation capabilities, mount Binary Ninja from host:

```bash
# Mount Binary Ninja installation
-v /opt/binaryninja:/opt/binaryninja:ro

# Mount license file
-v /path/to/license.dat:/home/analyzer/.binaryninja/license.dat:ro
```

The container will automatically detect and configure Binary Ninja at runtime.

## Registry Deployment

### Push to Registry
```bash
# Tag and push
./docker-push.sh

# Or manually
docker tag redb:latest your-registry/redb:latest
docker push your-registry/redb:latest
```

### Pull and Run
```bash
docker pull your-registry/redb:latest
docker run your-registry/redb:latest python3 start.py --nomad-job
```

## Testing

### Container Functionality Test
```bash
# Test with S3 key (standard sharded path)
./test-docker.sh "09/f7/09f7d02a3c2382199458c98a62b045145ee54ab6aba86166aecf3d10c3c1444c.zip"

# Test with private sample S3 key
./test-docker.sh "private/ab/cd/abcd1234567890abcdef1234567890abcdef1234567890abcdef123456.zip"
```

### Nomad Job Architecture Test
```bash
# Test Nomad job mode
./test-nomad.sh
```

## Development

### Interactive Container
```bash
# Debug container interactively
docker run -it --entrypoint /bin/bash redb:latest

# Check tool availability
docker run --rm redb:latest which python3
docker run --rm redb:latest ls -la /usr/bin/capa
```

### Build Troubleshooting

The build script includes workarounds for Docker Desktop bugs:

```bash
# If build hangs at "exporting to image", press Ctrl+C
# The image will still be created and tagged automatically
./docker-build.sh
```

### Container Logs
```bash
# View logs from mounted directory
docker run -v ./logs:/app/logs redb:latest python3 start.py --path /samples
tail -f logs/*.txt
```

## Production Notes

### Resource Requirements
- **Memory**: 2-4GB recommended (8GB for decompilation)
- **CPU**: 2+ cores recommended
- **Disk**: Minimal (stateless container)
- **Network**: Access to ClickHouse and S3 services

### Security
- Container runs as non-root user `analyzer` (UID 1000)
- Sample files should be mounted read-only
- No persistent state between container runs
- Isolated processing environment for malware analysis

### Deployment Architecture

This container is designed for:
- **Nomad job dispatch**: Single-use containers processing one sample each
- **Kubernetes jobs**: Batch processing with external orchestration
- **CI/CD pipelines**: Automated analysis in build systems
- **Development**: Local testing and debugging

The unified container approach means the same image handles both feature extraction and decompilation - the difference is only in the command-line flags used when starting the container.