Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
マルウェアを機械学習する前に
Search
Yuma Kurogome
February 13, 2016
Programming
3
1.6k
マルウェアを機械学習する前に
Kaggle - Malware Classification Challenge勉強会 connpass.com/event/25007/ 発表資料
Yuma Kurogome
February 13, 2016
Tweet
Share
More Decks by Yuma Kurogome
See All by Yuma Kurogome
The Art of De-obfuscation
ntddk
16
27k
死にゆくアンチウイルスへの祈り
ntddk
55
38k
Windows Subsystem for Linux Internals
ntddk
10
2.9k
なぜマルウェア解析は自動化できないのか
ntddk
6
4.1k
Linear Obfuscation to Drive angr Angry
ntddk
4
820
CAPTCHAとボットの共進化
ntddk
2
1.1k
Peeling Onions
ntddk
7
3.5k
仮想化技術を用いたマルウェア解析
ntddk
8
27k
An Introduction to Drawbridge(ja)
ntddk
11
3.3k
Other Decks in Programming
See All in Programming
アジャイルを支えるテストアーキテクチャ設計/Test Architecting for Agile
goyoki
9
3.3k
【Kaigi on Rails 2024】YOUTRUST スポンサーLT
krpk1900
1
330
subpath importsで始めるモック生活
10tera
0
300
Streams APIとTCPフロー制御 / Web Streams API and TCP flow control
tasshi
2
350
色々なIaCツールを実際に触って比較してみる
iriikeita
0
330
タクシーアプリ『GO』のリアルタイムデータ分析基盤における機械学習サービスの活用
mot_techtalk
4
1.4k
Creating a Free Video Ad Network on the Edge
mizoguchicoji
0
120
ActiveSupport::Notifications supporting instrumentation of Rails apps with OpenTelemetry
ymtdzzz
1
230
Jakarta EE meets AI
ivargrimstad
0
140
Duckdb-Wasmでローカルダッシュボードを作ってみた
nkforwork
0
120
Make Impossible States Impossibleを 意識してReactのPropsを設計しよう
ikumatadokoro
0
170
Enabling DevOps and Team Topologies Through Architecture: Architecting for Fast Flow
cer
PRO
0
320
Featured
See All Featured
[RailsConf 2023] Rails as a piece of cake
palkan
52
4.9k
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
26
2.1k
Practical Tips for Bootstrapping Information Extraction Pipelines
honnibal
PRO
10
720
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
47
5k
GitHub's CSS Performance
jonrohan
1030
460k
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
28
2k
Code Reviewing Like a Champion
maltzj
520
39k
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
44
2.2k
Typedesign – Prime Four
hannesfritz
40
2.4k
Statistics for Hackers
jakevdp
796
220k
Building Better People: How to give real-time feedback that sticks.
wjessup
364
19k
Rails Girls Zürich Keynote
gr2m
94
13k
Transcript
@ntddk Kaggle - Malware Classification Challenge 2016.02.13 1
• http://ntddk.github.io/ • 2
3
4
Kaggle 5 https://www.kaggle.com/
6 • • • ※ David H. Wolpert, The Supervised
Learning No-Free-Lunch Theorems, In Proc. 6th Online World Conference on Soft Computing in Industrial Applications, pp.25-42, 2001.
7 • • • ※ David H. Wolpert, The Supervised
Learning No-Free-Lunch Theorems, In Proc. 6th Online World Conference on Soft Computing in Industrial Applications, pp.25-42, 2001.
8 There ain't no such thing as a free lunch
http://www.amazon.co.jp/dp/4150117489 http://www.amazon.co.jp/dp/B00GJMUKMG/ http://www.amazon.co.jp/dp/4150312133/
9 There ain't no such thing as a free lunch
http://www.amazon.co.jp/dp/4150117489 http://www.amazon.co.jp/dp/B00GJMUKMG/ http://www.amazon.co.jp/dp/4150312133/
10 http://blog.kaggle.com/
11 x η g a b c x …
12 x η g a b c x …
13 • • A B Satoshi Watanabe, Knowing and Guessing
― Quantitative Study of Inference and Information John Wiley & Sons, 1969.
14 • • A B Satoshi Watanabe, Knowing and Guessing
― Quantitative Study of Inference and Information John Wiley & Sons, 1969.
15 • • • •
16 https://www.av-test.org/en/statistics/malware/
17 http://www.mcafee.com/jp/resources/reports/rp-quarterly-threat-q2-2015.pdf
18 http://www.mcafee.com/jp/resources/reports/rp-quarterly-threat-q2-2015.pdf http://www.mcafee.com/jp/resources/reports/rp-threats-predictions-2016.pdf
19 • KERNEL32!VirtualAllocStub • KERNEL32!VirtualProtectStub • KERNEL32!OpenProcessStub • KERNEL32!OpenThreadStub •
…
20 CSEC: MWS: http://www.iwsec.org/mws/2015/about.html
21 https://www.kaggle.com/c/malware-classification/data 16
22 • https://virusshare.com/ • http://malware-traffic-analysis.net/
23 • • • •
24 • • • • API PE
25 https://github.com/corkami/
26 • • • • • •
27 #include <windows.h> typedef int (WINAPI *LPFNMESSAGEBOXW)(HWND, LPCWSTR, LPCWSTR, UINT);
int main() { HMODULE hmod = LoadLibrary(TEXT("user32.dll")); LPFNMESSAGEBOXW lpfnMessageBoxW = (LPFNMESSAGEBOXW)GetProcAddress(hmod, "MessageBoxW"); lpfnMessageBoxW(NULL, L"Hello, world!", L"Test", MB_OK); FreeLibrary(hmod); return 0; } •
28 { "category": "registry", "status": true, "return": "0x00000000", "timestamp": "2015-05-24
02:46:50,773", "thread_id": "3220", "repeated": 0, "api": "NtOpenKey", "arguments": [ { "name": "DesiredAccess", "value": "33554432" }, { "name": "KeyHandle", "value": "0x00000154" }, { "name": "ObjectAttributes", "value": "¥¥REGISTRY¥¥USER¥¥S-1-5-21-916742657-1382504153-4155998892-1001" } ], "id": 83 },
29 • • • ※ David H. Wolpert, The Supervised
Learning No-Free-Lunch Theorems, In Proc. 6th Online World Conference on Soft Computing in Industrial Applications, pp.25-42, 2001.
30 • AdaBoost, Gradient Boosting • Kaggle
DAF 31 Mohammad M. Masud, Latifur Khan, Bhavani Thuraisingham, A
scalable multi-level feature extraction technique to detect malicious executables, Information Systems Frontiers, Vol.10, Issue.1, pp.33-45, 2008. 16 DAF: Derived Assembly Features BFS: Binary N-gram Features