V. Javier Traver

58 papers A 1B 2C 3Misc 5Journal 30Unranked 17
YearRankTypeTitle / Venue / Authors
2025 J jnl
Pattern Anal. Appl.
Yoelvis Moreno-Alcayde, Tuukka Ruotsalo, Luis A. Leiva, V. Javier Traver
2025 J jnl
Medical Biol. Eng. Comput.
Yoelvis Moreno-Alcayde, V. Javier Traver, Luis A. Leiva
2024 J jnl
IEEE Intell. Syst.
Tuukka Ruotsalo, V. Javier Traver, Aleksandra Kawala-Sterniuk, Luis A. Leiva
2024 J jnl
ACM Trans. Multim. Comput. Commun. Appl.
Kayhan Latifzadeh, Nima Gozalpour, V. Javier Traver, Tuukka Ruotsalo, Aleksandra Kawala-Sterniuk, Luis A. Leiva
2024 J jnl
CoRR
Luis A. Leiva, V. Javier Traver, Aleksandra Kawala-Sterniuk, Tuukka Ruotsalo
2024 J jnl
Int. J. Interact. Multim. Artif. Intell.
José Ribelles, Angeles López, V. Javier Traver
2022 J jnl
Expert Syst. Appl.
V. Javier Traver, Dima Damen
2022 J jnl
IEEE Robotics Autom. Lett.
Javier Marina-Miranda, V. Javier Traver
2022 J jnl
CoRR
Javier Marina-Miranda, V. Javier Traver
2022 Misc conf
IbPRIA
Francisco J. Moreno-Rodríguez, V. Javier Traver, Francisco Barranco, Mariella Dimiccoli, Filiberto Pla
2021 conf
UMAP (Adjunct Publication)
Xavier Anadón, Pablo Sanahuja, V. Javier Traver, Angeles López, José Ribelles
2021 J jnl
Sensors
V. Javier Traver, Judith Zorío, Luis A. Leiva
2020 J jnl
IEEE Access
V. Javier Traver, Roberto Paredes
2019 J jnl
Neuroinformatics
V. Javier Traver, Filiberto Pla, Marta Miquel, Maria Carbo-Gas, Isis Gil-Miravet, Julian Guarque-Chabrera
2019 J jnl
Image Vis. Comput.
Pedro Latorre-Carmona, V. Javier Traver, José Salvador Sánchez, Enrique Tajahuerce
2019 J jnl
Expert Syst. Appl.
Dan López-Puigdollers, V. Javier Traver, Filiberto Pla
2018 J jnl
Pattern Anal. Appl.
V. Javier Traver, Carlos Serra-Toro
2017 J jnl
Multim. Tools Appl.
Vicente Castelló, V. Javier Traver, Berenice Serrano, Raúl Montoliu, Cristina Botella
2017 Misc conf
IbPRIA
Carlos Serra-Toro, Ángel Hernández-Górriz, V. Javier Traver
2017 J jnl
IEEE Signal Process. Lett.
V. Javier Traver, Pedro Latorre-Carmona, Eva Salvador-Balaguer, Filiberto Pla, Bahram Javidi
2015 J jnl
J. Real Time Image Process.
Marco Antonelli, Francisco D. Igual, Francisco Ramos, V. Javier Traver
2014 J jnl
Pattern Recognit. Lett.
Pau Agustí, V. Javier Traver, Filiberto Pla
2014 J jnl
Pattern Recognit. Lett.
Carlos Serra-Toro, V. Javier Traver, Filiberto Pla
2014 C conf
FIE
Carlos Serra-Toro, V. Javier Traver, Juan-Carlos Amengual
2013 conf
VISAPP (1)
Pau Agustí, V. Javier Traver, Filiberto Pla, Raúl Montoliu
2013 Misc conf
IbPRIA
Pau Agustí, V. Javier Traver, Filiberto Pla
2013 Misc conf
IbPRIA
Carlos Serra-Toro, V. Javier Traver
2013 conf
CHI Extended Abstracts
Luis A. Leiva, V. Javier Traver, Vicente Castelló
2013 conf
VISAPP (1)
V. Javier Traver, Pau Agustí, Filiberto Pla
2013 J jnl
J. Math. Imaging Vis.
Carlos Serra-Toro, V. Javier Traver, Raúl Montoliu
2011 conf
CAIP (2)
Carlos Serra-Toro, V. Javier Traver
2011 conf
CAIP (2)
Pau Agustí, V. Javier Traver, Manuel J. Marín-Jiménez, Filiberto Pla
2011 conf
VISAPP
Carlos Serra-Toro, V. Javier Traver, Raúl Montoliu, José Martínez Sotoca
2011 J jnl
Neural Comput. Appl.
Mónica Millán-Giraldo, José Salvador Sánchez, V. Javier Traver
2011 conf
VISAPP
V. Javier Traver
2010 C conf
ICMLA
Mónica Millán-Giraldo, José Salvador Sánchez, V. Javier Traver
2010 J jnl
Robotics Auton. Syst.
V. Javier Traver, Alexandre Bernardino
2010 B conf
ICPR
Carlos Serra-Toro, Raúl Montoliu, V. Javier Traver, Isabel M. Hurtado-Melgar, Manuela Núñez-Redó, Pablo Cascales
2010 conf
ECCV (4)
V. Javier Traver, Majid Mirmehdi, Xianghua Xie, Raúl Montoliu
2010 J jnl
Adv. Hum. Comput. Interact.
V. Javier Traver
2009 J jnl
Rev. Iberoam. de Tecnol. del Aprendiz.
V. Javier Traver, Juan Manuel Pérez
2009 conf
ICONIP (1)
Mónica Millán-Giraldo, José Salvador Sánchez, V. Javier Traver
2008 conf
VISAPP (1)
Nadia Tamayo, V. Javier Traver
2008 J jnl
Image Vis. Comput.
V. Javier Traver, Filiberto Pla
2008 J jnl
J. Math. Imaging Vis.
V. Javier Traver, Filiberto Pla
2007 J jnl
ACM SIGCSE Bull.
V. Javier Traver
2007 conf
CCIA
M. Luis Puig, V. Javier Traver
2005 J jnl
Comput. Vis. Image Underst.
V. Javier Traver, Filiberto Pla
2004 conf
ICIAR (1)
V. Javier Traver, Alexandre Bernardino, Plinio Moreno, José Santos-Victor
2003 J jnl
Image Vis. Comput.
V. Javier Traver, Filiberto Pla
2003 conf
DGCI
V. Javier Traver, Filiberto Pla
2003 Misc conf
IbPRIA
V. Javier Traver, Filiberto Pla
2002 conf
ICPR (4)
V. Javier Traver, Filiberto Pla
2002 conf
CCIA
Filiberto Pla, V. Javier Traver
2001 C conf
CAIP
V. Javier Traver, Filiberto Pla
2000 B conf
ICPR
V. Javier Traver, Gabriel Recatalá, José Manuel Iñesta Quereda
2000 A conf
IROS
V. Javier Traver, Angel Pasqual del Pobil, Miguel Pérez-Francisco
1999 conf
CIRA
Pedro J. Sanz, Gabriel Recatalá, V. Javier Traver, Angel P. del Pobil
yara/README.md
← Index yara/README.md markdown
# YARA Rules Directory

This folder contains YARA rules for scanning binary samples.

## Setting Up YARA-Forge Rules

To use the YARA-Forge rules from [https://github.com/YARAHQ/yara-forge](https://github.com/YARAHQ/yara-forge):

```bash
# Download the latest release
cd /path/to/redb/yara
# wget https://github.com/YARAHQ/yara-forge/releases/latest/download/yara-forge-rules-core.zip
wget https://github.com/YARAHQ/yara-forge/releases/latest/download/yara-forge-rules-extended.zip

# Extract rules
# unzip yara-forge-rules-core.zip
unzip yara-forge-rules-extended.zip
```

Available packages:
- `yara-forge-rules-core.zip` - Core rules (~5,000 rules)
- `yara-forge-rules-extended.zip` - Extended rules (~10,000 rules)
- `yara-forge-rules-full.zip` - Full rules (~11,000+ rules)

## Pre-compiling Rules (Recommended for Production)

For large rulesets like YARA-Forge, pre-compiling rules significantly improves startup time:

```bash
# Pre-compile all rules into a single .yarac file
python -m redb.extractors.yara --compile

# Or specify custom paths
python -m redb.extractors.yara --compile --rules-path /path/to/rules --output /path/to/output.yarac
```

This creates `yara/compiled_rules.yarac` which is loaded automatically on subsequent runs.

### Performance Comparison

| Method | First Scan Startup | Subsequent Scans |
|--------|-------------------|------------------|
| Source files (.yar) | ~10-30 seconds (11k rules) | Instant (cached) |
| Pre-compiled (.yarac) | ~1-2 seconds | Instant (cached) |

## Directory Structure

```
yara/
├── README.md
├── .gitkeep
├── compiled_rules.yarac    # (optional) Pre-compiled rules
├── packages/               # YARA-Forge packages
│   └── core/
│       └── *.yar
└── custom/                 # Your custom rules
    └── my_rules.yar
```

Rules are loaded in this priority:
1. `compiled_rules.yarac` (if exists) - fastest
2. All `.yar` and `.yara` files recursively - compiles on first run

## Usage

### Scan with YARA only

```bash
# Scan local files
python start.py --path /path/to/samples -y --repo my_repo --index_prefix redb

# Scan S3 samples
python start.py --s3 --repo bazaar -y --index_prefix redb

# Dry-run (print results instead of storing in ClickHouse)
python start.py --path /path/to/samples -y --dry-run --repo test --index_prefix redb
```

### Scan already-analyzed samples

Run YARA on samples that were previously analyzed (already in `basic_properties`).
Deduplication is handled by the `yara_matches` table — samples already scanned are
automatically excluded before processing begins:

```bash
# Scan all analyzed macho samples with YARA
python start.py --analyzed --magika macho -y --index_prefix redb

# Scan all analyzed PE samples with YARA
python start.py --analyzed --magika pe -y --index_prefix redb

# Scan all analyzed samples (no filetype filter)
python start.py --analyzed -y --index_prefix redb
```

### Partition large YARA runs by date

Combine `--analyzed` with `--range` to partition millions of samples into
manageable batches. Only samples in `basic_properties` AND within the date
range (by `first_seen` in `catalog_samples`) are processed:

```bash
# Scan analyzed PE samples from Feb 2025
python start.py --range 2025-02-01 2025-02-28 --analyzed --magika pebin -y --index_prefix redb

# Scan analyzed PE samples from first week of March 2025
python start.py --range 2025-03-01 2025-03-08 --analyzed --magika pebin -y --index_prefix redb
```

YARA dedup still applies — re-running a range safely skips already-scanned samples.

### Combined Features + YARA

Run feature extraction and YARA scanning together on the same samples:

```bash
# Local files with features + YARA
python start.py --path /path/to/samples --with-yara --repo my_repo --index_prefix redb

# S3 samples with features + YARA
python start.py --s3 --repo bazaar --with-yara --index_prefix redb
```

### Pre-compile Rules

```bash
# Compile and save to default location (yara/compiled_rules.yarac)
python -m redb.extractors.yara --compile

# Compile with custom paths
python -m redb.extractors.yara --compile --rules-path ./my_rules --output ./compiled.yarac
```

### Sync Rules to Database

Before batch scanning, sync rules to ensure all rule metadata is stored:

```bash
# Sync rules to database
python -m redb.extractors.yara --sync-rules

# Sync with custom source collection name
python -m redb.extractors.yara --sync-rules --source-collection yara-forge-core

# Compile and sync in one command
python -m redb.extractors.yara --compile --sync-rules
```

## ClickHouse Table Schema

YARA data uses a **normalized schema** with two tables for efficient storage.

### Matches Table: `yara_matches`

Stores one row per sample-rule match (optimized with binary sha256 and rule_id):

| Column | Type | Description |
|--------|------|-------------|
| sha256 | FixedString(32) | Binary SHA256 (32 bytes, use `hex(sha256)` to display) |
| rule_id | UInt64 | Unique rule identifier (xxHash64 of canonical rule content) |
| rule_name | LowCardinality(String) | YARA rule name (denormalized for convenience) |
| scan_date | DateTime64(3, 'UTC') | Scan timestamp |
| match_strings | Array(String) | Matched string identifiers |

### Rules Table: `yara_rules`

Stores rule metadata once per unique rule (deduplicated by rule_id):

| Column | Type | Description |
|--------|------|-------------|
| rule_id | UInt64 | Unique rule identifier (xxHash64 of canonical rule content) |
| rule_name | String | YARA rule name |
| source_collection | LowCardinality(String) | Source collection (e.g., 'yara-forge-core', 'malpedia') |
| ingested_at | DateTime64(3, 'UTC') | When this rule was ingested |
| rule_text | String | Full rule source code |
| rule_meta | JSON | Rule metadata (author, description, reference, etc.) |
| rule_tags | Array(LowCardinality(String)) | Rule tags |

### Schema Benefits

- **Binary SHA256**: 32 bytes vs 64 bytes (50% storage savings on hash columns)
- **UInt64 rule_id**: Fast joins and lookups via integer key
- **Content-based rule_id**: xxHash64 of canonical rule content (excluding metadata) for deduplication
- **Denormalized rule_name**: Allows queries without joins for common use cases

### Example Queries

```sql
-- Get matches with hex sha256
SELECT
    hex(m.sha256) as sha256,
    m.rule_name,
    m.match_strings
FROM yara_matches m
WHERE m.sha256 = unhex('abc123...')

-- Join with rules for full metadata
SELECT
    hex(m.sha256) as sha256,
    m.rule_name,
    m.match_strings,
    r.rule_meta,
    r.source_collection
FROM yara_matches m
JOIN yara_rules r ON m.rule_id = r.rule_id
WHERE m.sha256 = unhex('abc123...')

-- Find all samples matching a specific rule
SELECT hex(sha256), scan_date
FROM yara_matches
WHERE rule_name = 'APT_Lazarus_Loader'
ORDER BY scan_date DESC
```

## Environment Variables

| Variable | Description | Default |
|----------|-------------|---------|
| `YARA_RULES_PATH` | Override the YARA rules directory | `yara/` |
| `YARA_COMPILED_RULES` | Compiled rules filename | `compiled_rules.yarac` |
| `YARA_SOURCE_COLLECTION` | Default source collection name | `default` |