Radu Dobrescu

49 papers A 1C 2Journal 8Unranked 34
YearRankTypeTitle / Venue / Authors
2023 conf
CSCS
Gabriela Coman, Stefan Alexandru Mocanu, Radu Dobrescu
2023 conf
CSCS
Rîciu Ionela Mirela, Radu Dobrescu
2021 conf
CSCS
Giorgiana Cristescu, Oana Chenaru, Radu Dobrescu
2021 conf
CSCS
Gabriela Zinca, Stefan Alexandru Mocanu, Ana-Maria Dragulinescu, Radu Dobrescu
2021 J jnl
Comput. Methods Programs Biomed.
Radu Angelescu, Radu Dobrescu
2021 conf
CSCI
Teodora Mindra, Gheorghe Florea, Oana Chenaru, Radu Dobrescu, Lucian Toma
2021 conf
CSCS
Andrei Roznov, Radu Dobrescu, Dan Popescu, Loretta Ichim
2021 J jnl
Int. J. Comput. Integr. Manuf.
Radu Dobrescu, Stefan Alexandru Mocanu, Oana Chenaru, Maximilian Nicolae, Gheorghe Florea
2020 conf
ICSTCC
Radu Dobrescu, Oana Chenaru, Gheorghe Florea, Giorgiana Geampalia, Stefan Alexandru Mocanu
2019 J jnl
Comput. Electron. Agric.
Radu Dobrescu, Daniel Marian Merezeanu, Stefan Alexandru Mocanu
2019 conf
CSCS
Giorgiana Cristescu, Radu Dobrescu, Oana Chenaru, Gheorghe Florea
2019 conf
ICSTCC
Ioana D. Vasile, Maria Ghita, Dana Copot, Radu Dobrescu, Clara M. Ionescu
2019 conf
CSCS
Cristina Elena Poenaru, Radu Dobrescu
2019 conf
SOHOMA
Mihai Craciunescu, Oana Chenaru, Radu Dobrescu, Gheorghe Florea, Stefan Alexandru Mocanu
2019 J jnl
Comput. Ind.
Radu Dobrescu, Daniel Marian Merezeanu, Stefan Alexandru Mocanu
2019 conf
CSCS
Mihai Craciunescu, Diana Baicu, Maria Circiumaru, Stefan Alexandru Mocanu, Radu Dobrescu
2018 conf
SOHOMA
Mihai Craciunescu, Stefan Alexandru Mocanu, Daniel Marian Merezeanu, Radu Dobrescu
2018 conf
SOHOMA
Ana M. Chiriac, Andrei Lacatusu, Cosmin Popa, Stefan Alexandru Mocanu, Radu Dobrescu
2018 conf
IWSSIP
Mihai Craciunescu, Stefan Alexandru Mocanu, Cristian Dobre, Radu Dobrescu
2018 C conf
CoDIT
Radu Dobrescu, Stefan Alexandru Mocanu, Mihai Craciunescu, Magdalena Anghel
2017 conf
CSCS
Aimee-Theodora Dumitrescu, Ecaterina Oltean, Daniel Marian Merezeanu, Radu Dobrescu
2017 conf
CSCS
Cristina Elena Poenaru, Radu Dobrescu, Daniel Marian Merezeanu
2017 J jnl
Int. J. Neural Syst.
Óscar Martínez Mozos, Virginia Sandulescu, Sally Andrews, David A. Ellis, Nicola Bellotto, Radu Dobrescu, José Manuel Ferrández
2016 conf
SOHOMA
Radu Dobrescu, Daniel Marian Merezeanu
2015 conf
CSCS
Gheorghe Florea, Oana Chenaru, Dan Popescu, Radu Dobrescu
2015 conf
RAAD
Maximilian Nicolae, Dan Popescu, Radu Dobrescu, Cristian Mateescu
2015 ch.
Service Orientation in Holonic and Multi-agent Manufacturing
Radu Dobrescu, Gheorghe Florea
2015 conf
SOHOMA
Gheorghe Florea, Radu Dobrescu, Oana Chenaru, Mircea Eremia, Lucian Toma
2015 conf
CSCS
Oana Chenaru, Gheorghe Florea, Alexandru Stanciu, Vasile Sima, Dan Popescu, Radu Dobrescu
2015 conf
MED
Oana Chenaru, Alexandru Stanciu, Dan Popescu, Vasile Sima, Gheorghe Florea, Radu Dobrescu
2015 conf
IWBBIO (1)
Dan Popescu, Loretta Ichim, Radu Dobrescu
2014 A conf
ECAI
Grigore Stamatescu, Dan Popescu, Radu Dobrescu
2014 ch.
Service Orientation in Holonic and Multi-Agent Manufacturing and Robotics
Radu Dobrescu, Matei Dobrescu, Gheorghe Florea, Victor Lorin Purcarea
2013 conf
ICSCS
Cosmin Popa, Stefan Alexandru Mocanu, Radu Dobrescu
2013 conf
CSCS
Loretta Ichim, Radu Dobrescu
2013 conf
ICSCS
Gheorghe Florea, Radu Dobrescu, Oana I. Rohat
2013 ch.
Service Orientation in Holonic and Multi Agent Manufacturing and Robotics
Radu Dobrescu, Gheorghe Florea
2012 ch.
Service Orientation in Holonic and Multi-Agent Manufacturing Control
Radu Dobrescu, Victor Lorin Purcarea
2010 conf
TA
Stefan Arghir, Radu Dobrescu, Dan Popescu, Horia Humaila
2010 conf
WHISPERS
Radu Dobrescu, Matei Dobrescu, Loretta Ichim
2009 J jnl
Trans. Mass Data Anal. Images Signals
Loretta Ichim, Radu Dobrescu
2009 conf
eTELEMED
Radu Dobrescu, Matei Dobrescu, Dan Popescu, Henri George Coanda
2009 conf
IJCBS
Radu Dobrescu, Loretta Ichim
2008 conf
MDA
Radu Dobrescu, Loretta Ichim
2008 conf
BIOCOMP
Loretta Ichim, Radu Dobrescu, Catalin Vasilescu
2008 J jnl
Int. J. Funct. Informatics Pers. Medicine
Radu Dobrescu, Loretta Ichim
2007 C conf
BIBE
Radu Dobrescu, Loretta Ichim
2006 J jnl
Integr. Comput. Aided Eng.
Daniela Andone, Radu Dobrescu, Andrei Hossu, Matei Dobrescu
2001 conf
ECC
Radu Dobrescu, Daniela Andone, Matei Dobrescu
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` |