Xiang Wei

43 papers A* 1A 1B 7Journal 26Unranked 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
J. Electronic Imaging
Wenhao Xiang, Qianying Tang, Junzhe Chen, Xiang Wei, Shunli Zhang, Li Zhang
2025 B conf
IEEE Big Data
Junqing Duan, Xiaotao Wei, Xiang Wei, Bingke Fu, Dashuai Guan, Ruiping Yu
2024 J jnl
Neural Comput. Appl.
Xiaoyu Guo, Weiwei Xing, Xiang Wei, Weibin Liu, Jian Zhang, Wei Lu
2024 A* conf
CVPR
Jingyao Xu, Yuetong Lu, Yandong Li, Siyang Lu, Dongdong Wang, Xiang Wei
2024 J jnl
CoRR
Jingyao Xu, Yuetong Lu, Yandong Li, Siyang Lu, Dongdong Wang, Xiang Wei
2023 B conf
ICPADS
Guanjia Zhang, Weiwei Xing, Shuzhong Yang, Weibin Liu, Xiang Wei, Jian Zhang, Shunli Zhang
2023 J jnl
Appl. Intell.
Xiaoyu Guo, Xiangyuan Kong, Weiwei Xing, Xiang Wei, Jian Zhang, Wei Lu
2023 J jnl
Inf. Sci.
Siyang Lu, Mingquan Wang, Dongdong Wang, Xiang Wei, Sizhe Xiao, Zhiwei Wang, Ningning Han, Liqiang Wang
2023 B conf
ICPADS
Dongdong Wang, Jingyao Xu, Siyang Lu, Xiang Wei, Liqiang Wang
2023 J jnl
Pattern Recognit.
Xiangyuan Kong, Xiang Wei, Xiaoyu Liu, Jingjie Wang, Weiwei Xing, Wei Lu
2023 J jnl
Vis. Comput.
Xiukun Zhang, Weibin Liu, Weiwei Xing, Xiang Wei
2023 J jnl
Signal Image Video Process.
Dandan Cao, Weibin Liu, Weiwei Xing, Xiang Wei
2023 J jnl
Appl. Intell.
Xiangyuan Kong, Xiang Wei, Jian Zhang, Weiwei Xing, Wei Lu
2023 J jnl
Vis. Comput.
Jia Xu, Weibin Liu, Weiwei Xing, Xiang Wei
2023 B conf
ICPADS
Haoran Li, Siyang Lu, Xiang Wei, Yingjun Qi
2023 J jnl
World Wide Web (WWW)
Siyang Lu, Ningning Han, Mingquan Wang, Xiang Wei, Zaichao Lin, Dongdong Wang
2023 B conf
ICPADS
Jintao Xing, Weiwei Xing, Xiang Wei, Jian Zhang, Wei Lu
2023 B conf
ICPADS
Zaichao Lin, Siyang Lu, Ningning Han, Dongdong Wang, Xiang Wei, Mingquan Wang
2022 J jnl
Knowl. Based Syst.
Xiangyuan Kong, Xiang Wei, Xiaoyu Liu, Jingjie Wang, Siyang Lu, Weiwei Xing, Wei Lu
2022 conf
ICONIP (2)
Zhiwei Wang, Siyang Lu, Mingquan Wang, Xiang Wei, Yingjun Qi
2022 conf
SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta
Dongdong Wang, Siyang Lu, Xiang Wei, Mingquan Wang, Yandong Li, Liqiang Wang
2022 J jnl
Appl. Intell.
Xiangyuan Kong, Jian Zhang, Xiang Wei, Weiwei Xing, Wei Lu
2022 J jnl
Signal Image Video Process.
Haitao Xu, Weibin Liu, Weiwei Xing, Xiang Wei
2022 conf
SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta
Jingjie Wang, Xiang Wei, Siyang Lu, Mingquan Wang, Xiaoyu Liu, Wei Lu
2022 conf
SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta
Ningning Han, Siyang Lu, Dongdong Wang, Mingquan Wang, Xiaoman Tan, Xiang Wei
2022 J jnl
Appl. Intell.
Jintao Xing, Xiangyuan Kong, Weiwei Xing, Xiang Wei, Jian Zhang, Wei Lu
2022 conf
SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta
Yang Pei, Weiwei Xing, Xiang Wei, Weibin Liu, Mingquan Wang, Fuyong Sun
2021 J jnl
Neural Networks
Xiang Wei, Xiaotao Wei, Xiangyuan Kong, Siyang Lu, Weiwei Xing, Wei Lu
2020 J jnl
IEEE Access
Xiaotao Wei, Xiang Wei, Weiwei Xing, Siyang Lu, Wei Lu
2020 J jnl
IEEE Access
Limin Gao, Yunyang Jiu, Xiang Wei, Zhongchuan Wang, Weiwei Xing
2020 J jnl
KSII Trans. Internet Inf. Syst.
Xiaopin Zhao, Weibin Liu, Weiwei Xing, Xiang Wei
2020 B conf
SMC
Bowen Song, Wei Lu, Weiwei Xing, Xiang Wei, Yuxiang Yang, Limin Gao
2020 J jnl
IEEE Access
Xiangyuan Kong, Weiwei Xing, Xiang Wei, Peng Bao, Jian Zhang, Wei Lu
2019 J jnl
Future Gener. Comput. Syst.
Siyang Lu, Xiang Wei, Bingbing Rao, Byung-Chul Tak, Long Wang, Liqiang Wang
2019 conf
ICMU
Yingying Duan, Wei Lu, Weiwei Xing, Peng Bao, Xiang Wei
2018 conf
DASC/PiCom/DataCom/CyberSciTech
Siyang Lu, Xiang Wei, Yandong Li, Liqiang Wang
2018 conf
ICLR (Poster)
Xiang Wei, Boqing Gong, Zixia Liu, Wei Lu, Liqiang Wang
2018 J jnl
CoRR
Xiang Wei, Boqing Gong, Zixia Liu, Wei Lu, Liqiang Wang
2018 J jnl
Multim. Tools Appl.
Xiang Wei, Wei Lu, Peng Bao, Weiwei Xing
2017 J jnl
Multim. Tools Appl.
Xiang Wei, Wei Lu, Weiwei Xing
2017 A conf
ICWS
Siyang Lu, Bingbing Rao, Xiang Wei, Byung-Chul Tak, Long Wang, Liqiang Wang
2017 J jnl
Neurocomputing
Wei Lu, Xiang Wei, Weiwei Xing, Weibin Liu
2014 J jnl
J. Vis. Lang. Comput.
Weiwei Xing, Xiang Wei, Jian Zhang, Cheng Ren, Wei Lu
sql/redb_js_tables.sql
← Index sql/redb_js_tables.sql sql
-- JavaScript malware analysis tables
-- Engine: ReplacingMergeTree(analysis_date) — latest analysis wins on re-processing
--
-- File order:
--   1. redb_js_features
--   2. redb_js_suspicious_apis
--   3. redb_js_deobfuscation
--   4. code_text_content              (generic text-content table; JS today,
--                                      PowerShell / Python / email / extracted
--                                      PDF / Office text in the future)
--   5. redb_iocs source_type ALTER    (extends Enum8 with text_raw/text_normalized
--                                      so JS — and any future text-based pipeline —
--                                      can distinguish IOCs found in the raw vs
--                                      normalised surface)
--   6. redb_iocs ioc_type ALTER       (adds registry_key=42 so HKLM/HKCU/HKEY_*
--                                      keys are extracted alongside file paths)
--
-- Decoded strings from JS still go into the shared code_binja_strings_raw
-- table (same schema used by DecompileBinja and DecompileAPK). JS
-- string_encoding values: hex, unicode, charcode, base64, concat. Plain long
-- literals are not extracted here — they're already in code_text_content and
-- scraped by the IOC pipeline over text_raw/text_normalized.
-- string_offset is the line number in the source file.
--
-- redb_js_features.script_type values (file format / container, first match):
--   jse, wsf, hta, embedded_html, wscript, esm, node_module, standalone, unknown
-- redb_js_features.detected_environment values (runtime by API surface, first
-- match):
--   wscript, browser_extension, service_worker, deno, node, browser, unknown

-- 1. Core features & obfuscation metrics (1 row per sample)
CREATE TABLE IF NOT EXISTS redb_js_features (
    sha256 FixedString(64),
    line_count UInt32,
    char_count UInt64,
    text_entropy Float64,
    max_line_length UInt32,
    avg_line_length Float64,
    is_minified UInt8,
    is_likely_obfuscated UInt8,
    obfuscator_name LowCardinality(String),
    obfuscation_score UInt8,
    obfuscation_techniques Array(String),
    eval_count UInt32,
    function_constructor_count UInt32,
    settimeout_setinterval_count UInt32,
    document_write_count UInt32,
    innerhtml_count UInt32,
    unescape_count UInt32,
    fromcharcode_count UInt32,
    atob_count UInt32,
    decodeuri_count UInt32,
    total_function_count UInt32,
    total_variable_count UInt32,
    max_nesting_depth UInt16,
    avg_identifier_length Float64,
    hex_string_count UInt32,
    unicode_escape_count UInt32,
    long_string_count UInt32,
    base64_string_count UInt32,
    comment_ratio Float64,
    script_type LowCardinality(String),
    detected_environment LowCardinality(String),
    analysis_date DateTime64(3, 'UTC')
) ENGINE = ReplacingMergeTree(analysis_date)
ORDER BY sha256;

-- 2. Suspicious API calls (multi-row per sample)
--
-- `revealed_by_deobf` is 1 when the API only appears after the deobfuscation
-- pass (i.e. the call site is hidden in the raw artefact and surfaces only in
-- text_normalized). Useful for filtering "what did normalisation actually
-- buy us" without re-running the diff.
CREATE TABLE IF NOT EXISTS redb_js_suspicious_apis (
    sha256 FixedString(64),
    api_name String,
    api_category LowCardinality(String),
    call_count UInt32,
    line_numbers Array(UInt32),
    context_snippet String,
    revealed_by_deobf UInt8,
    analysis_date DateTime64(3, 'UTC')
) ENGINE = ReplacingMergeTree(analysis_date)
ORDER BY (sha256, api_name);

-- 3. Deobfuscation results (1 row per sample)
CREATE TABLE IF NOT EXISTS redb_js_deobfuscation (
    sha256 FixedString(64),
    deobfuscator_used LowCardinality(String),
    deobfuscation_successful UInt8,
    original_size UInt64,
    deobfuscated_size UInt64,
    size_change_ratio Float64,
    original_entropy Float64,
    deobfuscated_entropy Float64,
    new_strings_found UInt32,
    new_apis_found UInt32,
    deobfuscated_sha256 FixedString(64),
    analysis_date DateTime64(3, 'UTC')
) ENGINE = ReplacingMergeTree(analysis_date)
ORDER BY sha256;

-- 4. Generic text-content table for any text-based artefact (JS today;
--    PowerShell, Python, plain text, email bodies, extracted PDF/Office text
--    in the future). One row per sha256. content_type carries the magika
--    label so callers can filter without joining other tables.
CREATE TABLE IF NOT EXISTS code_text_content (
    sha256 FixedString(64),
    content_type LowCardinality(String),
    text_raw String CODEC(ZSTD(3)),
    text_normalized Nullable(String) CODEC(ZSTD(3)),
    normalizer_used Nullable(String),
    analysis_date DateTime64(3, 'UTC')
) ENGINE = ReplacingMergeTree(analysis_date)
ORDER BY sha256;

-- 5. Extend redb_iocs.source_type Enum8 with two universal text-content
--    surfaces: text_raw (the artefact's original text) and text_normalized
--    (a deobfuscated/canonicalised form). Used by the JS IOC extraction
--    pipeline today; any future text-based pipeline (PowerShell, PDF, etc.)
--    plugs into the same two values.
--
-- Existing rows keep their stored integer values; only newly-inserted rows
-- can use 4/5. The MODIFY COLUMN must list the full final enum, including
-- the existing values (1/2/3) — ClickHouse rejects partial alters.
ALTER TABLE redb_iocs
    MODIFY COLUMN source_type
    Enum8('decompiled_function'=1, 'disassembled_function'=2, 'string'=3,
          'text_raw'=4, 'text_normalized'=5);

-- 6. Extend redb_iocs.ioc_type Enum8 with registry_key=42. Windows registry
--    paths (HKLM\..., HKCU\..., HKEY_LOCAL_MACHINE\...) are a distinct class
--    of IOC from filesystem paths and were previously extracted by nothing.
--    Same MODIFY COLUMN constraint as the source_type alter — the full final
--    enum must be listed.
ALTER TABLE redb_iocs
    MODIFY COLUMN ioc_type
    Enum8('ipv4'=1, 'ipv6'=2, 'fqdn'=3, 'url'=4, 'email'=5, 'server'=6,
          'hash_md5'=10, 'hash_sha1'=11, 'hash_sha256'=12,
          'cve'=20, 'cwe'=21, 'cpe'=22,
          'crypto_btc'=30, 'crypto_eth'=31, 'crypto_xrp'=32, 'crypto_bch'=33,
          'crypto_ada'=34, 'crypto_substrate'=35,
          'path_linux'=40, 'path_windows'=41, 'registry_key'=42,
          'onion'=50);

-- 7. Migrate redb_js_features to the two-tier obfuscation verdict.
--    `is_obfuscated` (binary heuristic at score >=40) is renamed to
--    `is_likely_obfuscated` (heuristic at >=60 + ≥1 strong signal, OR
--    js-x-ray flagged the obfuscator family). `obfuscator_name` is the
--    family name reported by @nodesecure/js-x-ray (jsfuck, obfuscator.io,
--    morse, jjencode, freejsobfuscator, ...) or empty when not detected.
--
--    Run once against an existing deployment. The CREATE TABLE above
--    already reflects the post-migration shape, so fresh installs skip this.
ALTER TABLE redb_js_features
    RENAME COLUMN is_obfuscated TO is_likely_obfuscated;
ALTER TABLE redb_js_features
    ADD COLUMN IF NOT EXISTS obfuscator_name LowCardinality(String) AFTER is_likely_obfuscated;

-- 8. Harmonise code_text_content column names with redb_iocs.source_type
--    enum values. The enum already uses `text_raw` / `text_normalized` for
--    the surface labels; the table previously stored the same data under
--    `content_raw` / `content_normalized`, forcing every join across the two
--    to translate names. Renaming the columns produces a self-documenting
--    schema where `redb_iocs.source_type='text_raw'` points directly at
--    `code_text_content.text_raw`.
--
--    Run once against an existing deployment. The CREATE TABLE above
--    already reflects the post-migration shape, so fresh installs skip this.
ALTER TABLE code_text_content
    RENAME COLUMN content_raw TO text_raw;
ALTER TABLE code_text_content
    RENAME COLUMN content_normalized TO text_normalized;

-- 9. Add revealed_by_deobf flag to redb_js_suspicious_apis. The strings/APIs
--    extractors now scan both the raw source and the deobfuscated text so APIs
--    hidden behind one obfuscation layer (Vjw0rm-style array.join + eval,
--    Dean-Edwards packers, ...) surface in the table. The flag is 1 only when
--    the API was *not* found in the raw source — querying for it isolates
--    "deobf-only" findings without joining redb_js_deobfuscation.
--
--    Run once against an existing deployment. The CREATE TABLE above
--    already reflects the post-migration shape, so fresh installs skip this.
ALTER TABLE redb_js_suspicious_apis
    ADD COLUMN IF NOT EXISTS revealed_by_deobf UInt8 AFTER context_snippet;