Xiangli Li

38 papers A* 2B 1C 1Journal 29Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Knowl. Inf. Syst.
Xiangli Li, Yongqi Mi, Zhibin Zhu
2026 conf
KDD (1)
Ziyang Zeng, Heming Jing, Jindong Chen, Xiangli Li, Hongyu Liu, Yixuan He, Zhengyu Li, Yige Sun, Zheyong Xie, Yuqing Yang, Shaosheng Cao, Jun Fan, Yi Wu, Yao Hu
2025 J jnl
Neurocomputing
Xiangli Li, Yalin Kou, Yongqi Mi
2025 J jnl
Robotics Comput. Integr. Manuf.
Yi Gong, Xiangli Li, Rui Zhou, Miao Li, Sheng Liu
2025 J jnl
Appl. Soft Comput.
Xiangli Li, Qifan Wang, Baozhi Qiu
2025 J jnl
Expert Syst. Appl.
Xiangli Li, Jiafeng Wei, Tengchi Xie
2025 J jnl
CoRR
Ziyang Zeng, Heming Jing, Jindong Chen, Xiangli Li, Hongyu Liu, Yixuan He, Zhengyu Li, Yige Sun, Zheyong Xie, Yuqing Yang, Shaosheng Cao, Jun Fan, Yi Wu, Yao Hu
2025 J jnl
Neurocomputing
Xiangli Li, Jianping Mei, Yuanjian Mo
2024 A* conf
ICRA
Mengde Li, Fuqiang Zhao, Xiangli Li, Mingchang Li, Sheng Liu, Miao Li
2024 J jnl
Circuits Syst. Signal Process.
Zhenwei Shi, Lincheng Zhou, Haodong Yang, Xiangli Li, Mei Dai
2024 conf
ICIRA (7)
Xiangli Li, Yufei Hao, Hui Wang, Jianhua Zhang
2024 J jnl
Eng. Appl. Artif. Intell.
Xiangli Li, Rui Zhou, Wei Wang, Mengde Li, Yi Gong, Miao Li
2021 J jnl
Int. J. Model. Identif. Control.
Lingzhong Zhang, Xiangli Li, Junxin Xia, Jin Shang
2021 J jnl
Int. J. Comput. Appl. Technol.
Xiangli Li, Lincheng Zhou
2021 J jnl
Int. J. Model. Identif. Control.
Lincheng Zhou, Xiangli Li
2021 J jnl
IEEE Access
Xiangli Li, Lezhi Ye, Mingfei Li, Qiang Lv
2020 J jnl
Mob. Networks Appl.
Bin Feng, Xiangli Li, Yingmo Jie, Cheng Guo, Huijuan Fu
2020 A* conf
ISMAR
Songhai Zhang, Xiangli Li, Yingtian Liu, Hongbo Fu
2020 J jnl
CoRR
Songhai Zhang, Xiangli Li, Yingtian Liu, Hongbo Fu
2019 conf
ICICDT
Xiangli Li, Fen Ge, Ben Rui, Ning Wu, Fang Zhou
2019 J jnl
IEEE Access
Zeng Hu, Longqin Xu, Liang Cao, Shuangyin Liu, Zhijie Luo, Jing Wang, Xiangli Li, Lu Wang
2019 J jnl
PeerJ Comput. Sci.
Yufan Feng, Shuo Yu, Kaiyuan Zhang, Xiangli Li, Zhaolong Ning
2019 J jnl
IEEE Trans. Neural Networks Learn. Syst.
Xiaofeng Cao, Baozhi Qiu, Xiangli Li, Zenglin Shi, Guandong Xu, Jianliang Xu
2019 J jnl
Int. J. Model. Identif. Control.
Ya Gu, Peiyi Zhu, Xiangli Li, Jianfei Gu
2018 J jnl
Neurocomputing
Xiangli Li, Qiong Han, Baozhi Qiu
2018 J jnl
Appl. Intell.
Xiangli Li, Qiong Han, Baozhi Qiu
2017 J jnl
J. Frankl. Inst.
Lincheng Zhou, Xiangli Li, Lijie Shan, Jing Xia, Wei Chen
2017 C conf
QSHINE
Bin Feng, Xiangli Li, Yingmo Jie, Cheng Guo, Huijuan Fu
2017 J jnl
计算机科学
Xiangli Li, Maoyi Xuan
2016 J jnl
Intell. Data Anal.
Xiangli Li, Peng Geng, Baozhi Qiu
2016 J jnl
Peer-to-Peer Netw. Appl.
Kaimin Wei, Song Guo, Xiangli Li, Deze Zeng, Ke Xu
2015 J jnl
Algorithms
Lincheng Zhou, Xiangli Li, Huigang Xu, Peiyi Zhu
2015 conf
ICCAIS
Lincheng Zhou, Xiangli Li, Huigang Xu, Peiyi Zhu
2015 conf
ICCAIS
Xiangli Li, Lincheng Zhou, Peiyi Zhu
2014 J jnl
Circuits Syst. Signal Process.
Xiangli Li, Lincheng Zhou, Ruifeng Ding
2012 J jnl
IEEE J. Solid State Circuits
Gordon Wan, Xiangli Li, Gennadiy Agranov, Marc Levoy, Mark Horowitz
2011 J jnl
J. Networks
Xiangli Li, Kaimin Wei, Xiaolin Sun, Yanhong Gao
2006 B conf
IEEE Congress on Evolutionary Computation
Huizhong Yang, Xiangli Li, Cuimei Bo, Xinguang Shao
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;