{"id":2615,"date":"2023-09-05T22:51:05","date_gmt":"2023-09-05T13:51:05","guid":{"rendered":"https:\/\/saraheee.com\/?p=2615"},"modified":"2023-10-05T12:26:07","modified_gmt":"2023-10-05T03:26:07","slug":"review-6-decision-and-game-theory-for-security","status":"publish","type":"post","link":"https:\/\/saraheee.com\/ko\/2023\/09\/review-6-decision-and-game-theory-for-security\/","title":{"rendered":"[review #6] Decision and Game Theory for Security | 13th International Conference, GameSec 2022"},"content":{"rendered":"

Concents<\/h2>\n\n\n\n
Decision and Game Theory for Security: 13th International Conference, GameSec 2022 Pittsburgh, PA, USA, October 26-28, 2022 Proceedings\n\n1) Deception in Security\n2) Planning and Learning in Dynamic Environments\n3) Security Games\n4) Adversarial Learning and Optimization\n5) Novel Applications and New Game Models<\/pre>\n\n\n\n
<\/p>\n\n\n\n
Deception in Security<\/h2>\n\n\n\n
The Risk of Attacker Behavioral Learning: Can Attacker Fool Defender Under Uncertainty?
Thanh Hong Nguyen and Amulya Yadav<\/mark><\/strong><\/h5>\n\n\n\n
Abstract<\/a><\/p>\n\n\n\n
Keywords: Security games \u00b7 Behavior models \u00b7 Deception \u00b7 Uncertainty<\/p>\n\n\n\n
\ubc29\uc5b4\uc790\uc758 \ud559\uc2b5 \uacb0\uacfc\uac00 \ubd88\ud655\uc2e4\ud558\ub2e4\ub294 \uc810\uc744 \uace0\ub824, \uacf5\uaca9\uc790\uac00 \ubaa8\ub378\uc5d0 \ub530\ub978 \uc77c\uad00\ub41c \ud50c\ub808\uc774\ub97c \ud1b5\ud574 \ud589\ub3d9 \ubaa8\ub378
\ud589\ub3d9 \ubaa8\ub378\uc744 \ubaa8\ubc29\ud558\ub294 \ubd88\ud655\uc2e4\uc131 \ud558\uc5d0\uc11c \uacf5\uaca9\uc790\uc758 \ubaa8\ubc29 \ud589\ub3d9 \uae30\ub9cc\uc744 \uc870\uc0ac<\/p>\n\n\n\n
three main contributions<\/p>\n\n\n\n
    \n
  1. introduce a new maximin-based algorithm to compute a robust attackers deception decision.<\/li>\n\n\n\n
  2. propose a new counter-deception algorithm to tackle the attacker’s deception.<\/li>\n\n\n\n
  3. conduct extensive experiments, demonstrating the effectiveness of our proposed algorithms.<\/li>\n<\/ol>\n\n\n\n
    <\/p>\n\n\n\n
    Casino Rationale: Countering Attacker Deception in Zero-Sum Stackelberg Security Games of Bounded Rationality
    Ryan Gabrys, Mark Bilinski, Justin Mauger, Daniel Silva, and Sunny Fugate<\/mark><\/strong><\/h5>\n\n\n\n
    Abstract<\/a><\/p>\n\n\n\n
    \uc81c\ub85c\uc12c \uac8c\uc784\uc744 \uace0\ub824\ud558\uc5ec, \uae30\ub9cc\uc801\uc778 \uacf5\uaca9\uc790\uc5d0 \ub300\ud55c \uc801\uc751\ud615 \ubc29\uc5b4\ub97c \uc704\ud55c \ucd5c\uc801\uc758 \uc804\ub7b5 \ucc3e\uc544\ub0c4
    \uacf5\uaca9\uc790\uc640 \ubc29\uc5b4\uc790 \ubaa8\ub450 \uc2dc\uac04\uc774 \uc9c0\ub0a8\uc5d0 \ub530\ub77c \uc804\ub7b5\uc744 \ubc1c\uc804\uc2dc\ud0ac \uc218 \uc788\ub294 \uc124\uc815 \uace0\ub824
    \uacf5\uaca9\uc790\uac00 \ud569\ub9ac\uc131\uc758 \uc815\ub3c4\ub97c \ub2e4\uc591\ud558\uac8c \ud5c8\uc6a9\ud558\uba74 \uacf5\uaca9\uc790\uc5d0\uac8c \uc720\ub9ac\ud55c \uac8c\uc784\uc5d0 \ud070 \uc601\ud5a5\uc744 \ubbf8\uce60 \uc218 \uc788\uc74c
    \uc801\uc751\ud615 \ubc29\uc5b4\ub97c \uc704\ud55c \ucd5c\uc801\uc758 \uc804\ub7b5 \ucc3e\uc544\ub0c4<\/p>\n\n\n\n
    <\/p>\n\n\n\n
    Cyber Deception Against Zero-Day Attacks: A Game Theoretic Approach
    Md Abu Sayed, Ahmed H. Anwar, Christopher Kiekintveld, Branislav Bosansky, and Charles Kamhoua<\/mark><\/strong><\/h5>\n\n\n\n
    arxiv.org<\/a><\/p>\n\n\n\n
    Keywords: Cyber deception \u00b7 Game theory \u00b7 Zero-day attacks<\/p>\n\n\n\n
    Zero-day attacks: \uc54c\ub824\uc9c0\uc9c0 \uc54a\uc740 \ucde8\uc57d\uc810\uc744 \uc545\uc6a9\ud558\uace0 \ubc29\uc5b4\uc5d0 \ub300\ud55c \uc6b0\uc704 \uc81c\uacf5
    Honeypots: \ub124\ud2b8\uc6cc\ud06c\uc758 \uc2e4\uc81c \uc0c1\ud0dc\ub97c \uc65c\uace1\ud558\uc5ec \uc18d\uc774\ub294 \ub370\uc5d0 \uc0ac\uc6a9
    “How to allocate honeypots over the network?”
    two-player zero-sum game \uc774\ub860\uc801 \uc811\uadfc \ubc29\uc2dd\uc744 \uac1c\ubc1c\ud568
    \uc81c\uc548\ub41c \uc18d\uc784\uc218 \uae30\uc220\uc758 \uc131\ub2a5\uc5d0 \ub300\ud55c \uc81c\ub85c \ub370\uc774 \ucde8\uc57d\uc810 \uc601\ud5a5\uc744 \uc870\uc0ac\ud558\uae30 \uc704\ud574 \ubbfc\uac10\ub3c4 \ubd84\uc11d
    \uc81c\ub85c\ub370\uc774 \ucde8\uc57d\uc810\uc5d0 \ub300\ud55c \ub124\ud2b8\uc6cc\ud06c\ub97c \ubc29\uc5b4\ud558\uae30 \uc704\ud55c \uc644\ud654 \uc804\ub7b5 \uc81c\uc548<\/p>\n\n\n\n
    \uc81c\ub85c \ub370\uc774 \uacf5\uaca9\uc5d0 \ub300\ud55c \uc0ac\uc774\ubc84 \uc18d\uc784\uc218\uc758 \ud6a8\uacfc\ub97c \ud3c9\uac00\ud558\uae30 \uc704\ud55c \uc0c8\ub85c\uc6b4 \ud504\ub808\uc784\uc6cc\ud06c \uc81c\uc548
    \uacf5\uaca9 \uadf8\ub798\ud504\uc758 \uc77c\ubd80\uac00 \uc218\ube44\uc218\uc5d0\uac8c \uc54c\ub824\uc9c0\uc9c0 \uc54a\uc558\ub2e4\uace0 \uac00\uc815
    \uc601\ud5a5\ub3c4 \ub192\uc740 \ud2b9\uc815 \ub178\ub4dc\uc5d0 \ub300\ud55c \uc704\uce58 \ud655\uc778, \uc774 \ub178\ub4dc \uc704\uce58\uc5d0 \ucd08\uc810\uc744 \ub9de\ucda4<\/p>\n\n\n\n
    <\/p>\n\n\n\n
    Planning and Learning in Dynamic Environments<\/h2>\n\n\n\n
    On Almost-Sure Intention Deception Planning that Exploits Imperfect Observers
    Jie Fu<\/mark><\/strong><\/h5>\n\n\n\n
    arxiv.org<\/a><\/p>\n\n\n\n
    Keywords: Game theory \u00b7 Deception \u00b7 Formal methods \u00b7 Opacity \u00b7 Discrete Event Systems<\/p>\n\n\n\n
    \uc758\ub3c4\uc801 \uc18d\uc784\uc218: \uc0c1\ub300\ubc29\uc744 \ub300\ub9ac\uc778\uc758 \uc758\ub3c4\ub098 \ubaa9\uc801\uc5d0 \ub300\ud55c \uc798\ubabb\ub41c \ubbff\uc74c\uc73c\ub85c \ubab0\uc544\ub123\ub294 \uc804\ub7b5\uc744 \uacc4\uc0b0
    \uc758\ub3c4 \uae30\ub9cc(intention deception)\uacfc \uad00\ub828\ub41c \ud655\ub960\uc801 \uacc4\ud68d \ubb38\uc81c\ub97c \uc5f0\uad6c
    Markov decision process (MDP)\uc73c\ub85c \uc218\uc815\ub41c \ud655\ub960 \uc2dc\uc2a4\ud15c\uc5d0\uc11c \uacf5\uaca9 \uacc4\ud68d \ubaa8\ub378\ub9c1
    \uacf5\uaca9\uc790\ub294 \uc2dc\uc2a4\ud15c\uc758 \uc548\uc804\ud558\uc9c0 \uc54a\uc740 \uc0c1\ud0dc\ub97c \ud53c\ud558\uba74\uc11c \uc77c\ubd80 \ubaa9\ud45c \uc0c1\ud0dc\uc5d0 \ub3c4\ub2ec\ud574\uc57c \ud568<\/p>\n\n\n\n
    \uacf5\uaca9\uc790\uac00 \uc120\ud55c \uc758\ub3c4(benign intention)\ub97c \uac00\uc9c4 \ud569\ubc95\uc801\uc778 \ub300\ub9ac\uc778\uc778 \ucc99 \ud558\ub294 \uc758\ub3c4\uc801 \uc18d\uc784\uc218\uc758 \ud074\ub798\uc2a4 \uc5f0\uad6c
    – \uacf5\uaca9\uc790: \ud0d0\uc9c0\ub418\uc9c0 \uc54a\uace0 \uc801\ub300\uc801\uc778 \ubaa9\ud45c\ub97c \ub2ec\uc131\ud558\uae30 \uc704\ud568<\/p>\n\n\n\n
    The success of the intention deception attacks may depend on three factors:<\/p>\n\n\n\n
      \n
    1. \ubc29\uc5b4\uc790\ub294 \uacf5\uaca9\uc790\uc758 \uc874\uc7ac\uc640 \uc758\ub3c4\uc5d0 \ub300\ud574 incomplete knowledge\ub97c \uac00\uc9d0<\/li>\n\n\n\n
    2. \ubc29\uc5b4\uc790\ub294 active attack \uc911 imperfect information\uc744 \uac00\uc9d0, \uc815\ubcf4\uc758 \ubd80\uc871\uc740 \uacf5\uaca9\uc744 \ud0d0\uc9c0\ud558\uae30 \uc704\ud55c \uc81c\ud55c<\/li>\n\n\n\n
    3. \uacf5\uaca9\uc790\ub294 \ubc29\uc5b4\uc790 \uad00\uc810\uc5d0\uc11c, \uc815\uc0c1\/\uc815\ub2f9\ud55c(normal\/legitimate) \uac83\uc73c\ub85c \uac04\uc8fc\ub418\ub294 \ud589\ub3d9 \ub4a4\uc5d0 \ubcf8\uc778\uc758 \uc758\ub3c4\ub97c \uc228\uae38 \uc218 \uc788\uc74c<\/li>\n<\/ol>\n\n\n\n
      intention deception attack strategies\ub97c \uc885\ud569\ud558\uae30 \uc704\ud55c formal-methods \uc811\uadfc \ubc29\uc2dd\uc744 \uac1c\ubc1c\ud568
      attacker\uacfc targeted system \uc0ac\uc774\uc758 \uad00\uacc4\ub97c Markov Decision Process (MDP)\ub85c \ubaa8\ub378\ub9c1\ud568<\/p>\n\n\n\n
      players<\/td>actions<\/td><\/tr>
      \ubc29\uc5b4\uc790<\/td>\uacf5\uaca9 \ud589\ub3d9\uc774 \uc815\uc0c1\uc801\uc778 \uc0ac\uc6a9\uc790 \ud589\ub3d9\uc5d0\uc11c \ubc97\uc5b4\ub098, \uacf5\uaca9\uc774 \uc131\uacf5\ud558\uae30 \uc804\uc5d0 \uc778\uc2dd\ub420 \uc218 \uc788\ub2e4\ub294 promise\uc5d0 \uae30\ubc18\ud55c \ud0d0\uc9c0 \uccb4\uc81c(detection mechanism)\ub97c \uc0ac\uc6a9<\/td><\/tr>
      \uacf5\uaca9\uc790<\/td>\ubc29\uc5b4\uc790\uac00 \ubd88\uc644\uc804\ud55c \uac10\uc9c0 \ub2a5\ub825(imperfect sensing capability)\uc744 \uac00\uc9c0\uace0 \uc788\uc744 \ub54c,
      \uacf5\uaca9\uc790\ub294 \uc790\uc2e0\uc758 \ud589\ub3d9\uc774 \uc815\uc0c1\uc774\ub77c\uace0 \uc0dd\uac01\ud558\ub3c4\ub85d \ubc29\uc5b4\uc790\ub97c \uc18d\uc774\uba74\uc11c
      \ubaa9\ud45c\ub97c \ub2ec\uc131\ud558\uae30 \uc704\ud55c \uc740\ubc00\ud55c \uc758\ub3c4 \uc18d\uc784\uc218 \uc804\ub7b5(stealthy intention deception strategy)\uc744 \uac00\uc9c0\uace0 \uc788\ub294\uc9c0<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      Definition 1 (Markov decision process (MDP) with a reach-avoid objective)
      Definition 2 (Almost-sure winning strategy and region)
      Definition 3 (State-observation function)
      Definition 4 (Action-observation function)
      Definition 5 (Observation-equivalent histories and strategies)<\/p>\n\n\n\n
      <\/p>\n\n\n\n
      Using Deception in Markov Game to Understand Adversarial Behaviors Through a Capture-The-Flag Environment
      Siddhant Bhambri, Purv Chauhan, Frederico Araujo, Adam Doupe, and Subbarao Kambhampati<\/mark><\/strong><\/h5>\n\n\n\n
      arxiv.org<\/a><\/p>\n\n\n\n
      Keywords: Adversarial Behavior \u00b7 Markov Games \u00b7 Capture-The-Flag.<\/p>\n\n\n\n
      stochastic game
      we model attacker-defender engagements as Markov Games and search for their Bayesian Stackelberg Equilibrium.<\/p>\n\n\n\n
      Section 2: CTF \ud658\uacbd, \ub9c8\ub974\ucf54\ud504 \uac8c\uc784 \ubc0f \uc2dc\uc2a4\ud15c \ucde8\uc57d \ub2a5\ub825\uc5d0 \ub300\ud55c \ubc30\uacbd\uc744 \uc81c\uacf5
      Section 3: \uc801\uc758 \ud589\ub3d9\uc5d0 \ub300\ud55c \uac00\uc124\uc744 \uc81c\uc2dc, \ub9c8\ub974\ucf54\ud504 \uac8c\uc784 \ubaa8\ub378\ub9c1\uacfc \ud568\uaed8 \uc0ac\uc6a9\uc790 \uc5f0\uad6c \uc124\uc815\uc744 \uc124\uba85
      Section 4: \uc0ac\ub840\ubcc4 \ud3c9\uac00\uc640 \uad00\ucc30\uc5d0 \ub300\ud55c \ub17c\uc758\ub97c \ud3ec\ud568\ud558\ub294 \uc2e4\ud5d8\uc801 \uc138\ubd80 \uc0ac\ud56d\uacfc \uacb0\uacfc
      Section 5: \uad00\ub828 \uc791\uc5c5\uc5d0 \ub300\ud574 \uc774\uc57c\uae30
      Section 6: \uacb0\uacfc, \ud5a5\ud6c4 \ubc29\ud5a5<\/p>\n\n\n\n
      * Markov game = Stochastic game : \ud655\ub960\uc801 \uac8c\uc784
      \ud55c \uba85 \uc774\uc0c1\uc758 \ud50c\ub808\uc774\uc5b4, \ud655\ub960\ub860\uc801 \uc804\ud658\uc774 \ubc18\ubcf5, \ubb34\uc791\uc704 \uc0c1\ud0dc\ub85c \uc774\ub3d9(\uc774\uc804 \uc120\ud0dd\ud55c \uc791\uc5c5\uc5d0 \ub530\ub77c \ubd84\ud3ec\uac00 \ub2ec\ub77c\uc9d0)
      \uc720\ud55c\/\ubb34\ud55c \ub2e8\uacc4\ub85c \ud50c\ub808\uc774 \uc9c0\uc18d<\/p>\n\n\n\n
      \uc560\ud50c\ub9ac\ucf00\uc774\uc158 \ucde8\uc57d\uc810<\/p>\n\n\n\n
        \n
      1. backup: \uc0ac\uc6a9\uc790 \uc785\ub825\uacfc \ubb38\uc790\uc5f4 \uc5f0\uacb0 \u2192 \ud574\ub2f9 \ubb38\uc790\uc5f4\uc744 C \ud568\uc218 system()\uc5d0 \uc804\ub2ec \u2192 \uc0ac\uc6a9\uc790\uc758 \uc785\ub825\uc740 \uc0ad\uc81c\ub418\uc9c0 \uc54a\uc74c \u2192 \uba85\ub839 \uc8fc\uc785 \ucde8\uc57d\uc810 \ubc1c\uc0dd<\/li>\n\n\n\n
      2. sampleak: \uc0ac\uc6a9\uc790 \uc785\ub825\uc73c\ub85c \ube44\ubc00\ubc88\ud638 \uc81c\uacf5, \ubc84\ud37c\ub97c \uc0ac\uc6a9\ud574\uc11c \uc560\ud50c\ub9ac\ucf00\uc774\uc158 \uba54\ubaa8\ub9ac\uc5d0 \uc800\uc7a5\ub428, read() \ud568\uc218 – \ubc84\ud37c\uac00 \ubcf4\uc720\ud560 \uc218 \uc788\ub294 \uac83\ubcf4\ub2e4 \ub9ce\uc740 \ubc14\uc774\ud2b8\ub97c \uc77d\uc74c \u2192 \ubc84\ud37c \uc624\ubc84\ud50c\ub85c \ucde8\uc57d\uc810 \ubc1c\uc0dd<\/li>\n\n\n\n
      3. exploit-market: \uc0ac\uc6a9\uc790\uac00 \ud504\ub85c\uadf8\ub7a8\uc758 \uba54\ubaa8\ub9ac\uc5d0 \uc800\uc7a5\ub41c \ud398\uc774\ub85c\ub4dc \uc800\uc7a5, \ubc84\ud37c\uac00 \ubcc4\ub3c4\uc758 \ud568\uc218\uc5d0\uc11c \ub2e4\ub978 \ud06c\uae30\ub85c \ucd08\uae30\ud654\ub428, strcpy() \ud568\uc218\uac00 \ubc84\ud37c\uc758 \ub0b4\uc6a9\uc744 \ubcf5\uc0ac\ud558\uae30 \uc704\ud574 \ud638\ucd9c\ub420 \ub54c, \ubc84\ud37c \uc624\ubc84\ud50c\ub85c \ucde8\uc57d\uc810\uc73c\ub85c \uc774\uc5b4\uc9c8 \uc218 \uc788\uc74c<\/li>\n<\/ol>\n\n\n
        \n
        \"\"<\/figure><\/div>\n\n
        \n
        \"\"<\/figure><\/div>\n\n\n
        https:\/\/github.com\/shellphish\/ictf-framework<\/a>
        https:\/\/ictf.cs.ucsb.edu\/<\/a><\/p>\n\n\n\n
        <\/p>\n\n\n\n
        Robust Moving Target Defense Against Unknown Attacks: A Meta-reinforcement Learning Approach
        Henger Li and Zizhan Zheng<\/mark><\/strong><\/h5>\n\n\n\n
        tulane.edu<\/a><\/p>\n\n\n\n
        to model the sequential attacker- defender interactions as a two-player Markov game, and formulate the defender\u2019s problem as finding the Stackelberg equilibrium<\/p>\n\n\n\n
        Security Games<\/h2>\n\n\n\n
        Synchronization in Security Games
        Stefan Rass and Sandra Konig<\/mark><\/strong><\/h5>\n\n\n\n
        Abstract<\/a><\/p>\n\n\n\n
        Keywords: Synchronization, Defense policy, Advanced persistent threats, Security game<\/p>\n\n\n\n
        <\/p>\n\n\n\n
        Multiple Oracle Algorithm to Solve Continuous Games
        Tomas Kroupa and Tomas Votroubek<\/mark><\/strong><\/h5>\n\n\n\n
        arxiv.org<\/a><\/p>\n\n\n\n
        Keywords: Non-cooperative game \u00b7 Continuous game \u00b7 Polynomial game \u00b7 Nash equilibrium<\/p>\n\n\n\n
        Continuous games: \uc804\ub7b5 \uc138\ud2b8\uac00 \uc791\uace0 \uc720\ud2f8\ub9ac\ud2f0 \uae30\ub2a5\uc774 \uc5f0\uc18d\uc801\uc778 \uba40\ud2f0\ud50c\ub808\uc774\uc5b4 \uac8c\uc784
        2\uc778\uc6a9 \uc81c\ub85c\uc12c \uac8c\uc784\uc5d0 \ub300\ud574\uc11c\ub9cc \uc218\ub834\ud558\ub3c4\ub85d \uc124\uacc4\ub418\uace0, \uc785\uc99d\ub41c \uc774\uc911 \uc624\ub77c\ud074 \uc54c\uace0\ub9ac\uc998\uc758 \uc801\uc6a9 \ubc94\uc704\ub97c \ud06c\uac8c \ud655\uc7a5\ud568
        \uc5f0\uc18d \uac8c\uc784\uc758 \ud3c9\ud615\uc5d0 \ub300\ud55c Wasserstein \uac70\ub9ac\uc5d0\uc11c \uc774 \uc54c\uace0\ub9ac\uc998\uc758 \uc218\ub834\ud558\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud310\ubcc4<\/p>\n\n\n\n
        Optimal Pursuit of Surveilling Agents Near a High Value Target
        Shivam Bajaj and Shaunak D. Bopardikar<\/mark><\/strong><\/h5>\n\n\n\n
        Abstract<\/a><\/p>\n\n\n\n
        \ub2e8\uc77c \ubaa8\ubc14\uc77c \ucd94\uc801\uc790, \ub450 \uac1c\uc758 \ubaa8\ubc14\uc77c \ucd94\uc801\uc790 \ubc0f \ud558\ub098\uc758 \uc815\uc801 \uace0\uac00\uce58 \ubaa9\ud45c\ub85c \uad6c\uc131\ub41c \ucd94\uc801 \ud68c\ud53c \uac8c\uc784\uc744 \uc18c\uac1c
        e.g., \ucd94\uc801\uae30: \ud45c\uc801\uae4c\uc9c0\uc758 \uac1c\ubcc4 \uac70\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud45c\uc801 \uc704\uce58\uc758 \uac1c\ubcc4 \uce21\uc815\uc5d0 \uc758\uc874, \ucd94\uc801\uc790\ubcf4\ub2e4 \ub290\ub9b0 \uac83\uc73c\ub85c \uac00\uc815
        \ucd94\uc801\uc790: \ucd94\uc801\uc790 \uc911 \ud558\ub098\uc5d0 \ub300\ud55c \uc21c\uac04 \uac70\ub9ac\uc758 \uc81c\uacf1\uc744 \ucd5c\uc18c\ud654\ud558\ub824\uace0 \ud558\ub294 \ubc18\uba74, \ucd94\uc801\uc790\ub294 Fisher Information Matrix\uc758 \ud589\ub82c\uc2dd\uacfc \ucd94\uc801\uc790\uc640 \ucd94\uc801\uc790 \uc0ac\uc774 \uac70\ub9ac\uc758 \uc81c\uacf1\uc758 \uac00\uc911 \uc870\ud569\uc744 \uacf5\ub3d9\uc73c\ub85c \ucd5c\ub300\ud654\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud568
        \u2192 \ucea1\ucc98\ub97c \uc9c0\uc5f0\uc2dc\ud0a4\uba74\uc11c \ub300\uc0c1\uc5d0 \ub300\ud574 \uc218\uc9d1\ub41c \uc815\ubcf4\ub97c \ucd5c\ub300\ud654\ud558\ub294 \ucd94\uc801\uae30\uc758 \ubaa9\ud45c\ub97c \ubaa8\ub378\ub9c1<\/p>\n\n\n\n
        <\/p>\n\n\n\n
        Adversarial Learning and Optimization<\/h2>\n\n\n\n
        On Poisoned Wardrop Equilibrium in Congestion Games
        Yunian Pan and Quanyan Zhu<\/mark><\/strong><\/h5>\n\n\n\n
        arxiv.org<\/a><\/p>\n\n\n\n
        Keywords: Congestion Games \u00b7 Adversarial Attack \u00b7 Stackelberg Game \u00b7 Sensitivity Analysis<\/p>\n\n\n\n
        \uad50\ud1b5 \ub124\ud2b8\uc6cc\ud06c\uc5d0 \ub300\ud55c \uacf5\uaca9 \ubca1\ud130 \uc99d\uac00\uc5d0 \ub530\ub978 \uc601\ud5a5 \uc5f0\uad6c
        Stackelbergh game – Wardrop \ud2b8\ub798\ud53d \ud3c9\ud615\uc5d0 \uc758\ud574 \uc608\uce21\ub41c \ud2b8\ub798\ud53d \ud328\ud134\uc744 \ubcc0\uacbd\ud558\uae30 \uc704\ud574 \ud2b8\ub798\ud53d \uc870\uac74\uc744 \uc704\uc870\ud558\ub294 \uac8c\uc784 \uc774\ub860\uc801 \ud504\ub808\uc784\uc6cc\ud06c \uc81c\uc548<\/p>\n\n\n\n
        * Wardrop<\/em>. (1952)\uc758 \uade0\ud615\uc740 2\uac00\uc9c0 \ud615\ud0dc\ub85c \uc81c1\uc6d0\ub9ac\ub294 \uad50\ud1b5\ub9dd\uc744. \uc774\uc6a9\ud558\ub294 \uc0ac\uc6a9\uc790\ub4e4\uac04\uc758 \uade0\ud615(User equilibrium)\uc5d0 \uad00. \ud55c \uac83\uc774\uba70 2\ubc88\uc9f8 \uc6d0\ub9ac\ub294 \uad50\ud1b5\ub9dd\uc744 \ucd5c\uc801\ud654\uc2dc\ud0a4\ub294 \uccb4\uacc4.<\/p>\n\n\n\n
        <\/p>\n\n\n\n
        Reward Delay Attacks on Deep Reinforcement Learning
        Anindya Sarkar, Jiarui Feng, Yevgeniy Vorobeychik, Christopher Gill, and Ning Zhang<\/mark><\/strong><\/h5>\n\n\n\n
        arxiv.org<\/a><\/p>\n\n\n\n
        Keywords: Deep Reinforcement Learning \u00b7 Adversarial Attack \u00b7 Reward Delay Attack.<\/p>\n\n\n\n
        \ub450 \uac00\uc9c0 \uc720\ud615\uc758 \uacf5\uaca9 \ubaa9\ud45c\ub97c \uace0\ub824
        1) \ubaa9\ud45c \uc815\ucc45\uc744 \ubc30\uc6b0\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud558\ub294 \ud45c\uc801 \uacf5\uaca9
        – \ubaa9\ud45c\uac00 \ub2e8\uc21c\ud788 \ubcf4\uc0c1\uc744 \ucd5c\uc18c\ud654\ud558\ub294 \uac83\uc77c \ub54c \ubcf4\uc0c1 \uc9c0\uc5f0 \uacf5\uaca9\uc774 \ub9e4\uc6b0 \ud6a8\uacfc\uc801
        2) \ub0ae\uc740 \ubcf4\uc0c1\uc73c\ub85c \uc815\ucc45\uc744 \uc720\ub3c4\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud558\ub294 \ud45c\uc801\uc774 \uc5c6\ub294 \uacf5\uaca9
        – \uc81c\uc548\ub41c \uc811\uadfc \ubc29\uc2dd\uc774 \uacf5\uaca9\uc790\uc758 \ubaa9\ud45c\ub97c \ub2ec\uc131\ud558\ub294 \ub370 \ub9e4\uc6b0 \ud6a8\uacfc\uc801<\/p>\n\n\n\n
        <\/p>\n\n\n\n
        An Exploration of Poisoning Attacks on Data-Based Decision Making
        Sarah Eve Kinsey, Wong Wai Tuck, Arunesh Sinha, and Thanh H. Nguyen<\/mark><\/strong><\/h5>\n\n\n\n
        ix.cs.uoregon.edu<\/a><\/p>\n\n\n\n
        \uc801\uc5d0 \ub300\ud55c \uc608\uce21 \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uace0 \uadf8\uc5d0 \ub530\ub77c \uacb0\uc815<\/p>\n\n\n\n
        <\/p>\n\n\n\n
        Novel Applications and New Game Models<\/h2>\n\n\n\n
        A Network Centrality Game for Epidemic Control
        Olivier Tsemogne, Willie Kouam, Ahmed H. Anwar, Yezekael Hayel, Charles Kamhoua, and Gabriel Deugoue<\/mark><\/strong><\/h5>\n\n\n\n
        Abstract | dl.acm.org<\/a><\/p>\n\n\n\n
        epidemic networks(\uc804\uc5fc\ubcd1 \ub124\ud2b8\uc6cc\ud06c): \uc778\uad6c\ub97c \uc138 \ubd80\ubd84\uc73c\ub85c \ub098\ub214(\ucde8\uc57d, \uac10\uc5fc, \uc81c\uac70\ub41c \uac1c\uc778)
        \uc704\ud611\uc744 \uc804\ud30c\ud558\ub294 \uc8fc\uccb4 \u2194\ufe0e \uc804\ud30c\uc758 \uc911\uc694\uc131\uc744 \uc81c\ud55c\ud558\ub824\ub294 \ubc29\uc5b4\uc790
        \ud655\ub960\ub860\uc801 \uac8c\uc784\uc73c\ub85c \ubaa8\ub378\ub9c1, \ub124\ud2b8\uc6cc\ud06c \ud1a0\ud3f4\ub85c\uc9c0\ub97c \uace0\ub824\ud55c \uc0c8\ub85c\uc6b4 \ud504\ub808\uc784\uc6cc\ud06c\ub97c \uc81c\uc548
        \uac01 \uae30\uac04\uc758 \uac01 \ud50c\ub808\uc774\uc5b4\uac00 \uc804\ubc18\uc801\uc778 \uacb0\uacfc\ub97c \ucd5c\uc801\ud654\ud558\uae30 \uc704\ud55c \ucd5c\uc120\uc758 \uc804\ub7b5\uc740 \uac00\uc7a5 \uc601\ud5a5\ub825 \uc788\ub294 \ub178\ub4dc \uc9d1\ud569\uc5d0 \uc9d1\uc911\ud558\ub294 \uac83\uc784\uc744 \ubcf4\uc5ec\uc90c<\/p>\n\n\n\n
        <\/p>\n\n\n\n
        Optimizing Intrusion Detection Systems Placement Against Network Virus Spreading Using a Partially Observable Stochastic Minimum-Threat Path Game
        Olivier Tsemogne, Yezekael Hayel, Charles Kamhoua, and Gabriel Deugoue<\/mark><\/strong><\/h5>\n\n\n\n
        Abstract<\/a><\/p>\n\n\n\n
        \ubc14\uc774\ub7ec\uc2a4\ub098 malware\uc758 \uc804\ud30c\ub294 \ub3d9\uc801\uc774\uace0 \uacf5\uaca9\uc790\uac00 \uc804\ub7b5\uc801\uc73c\ub85c \uc81c\uc5b4\ud560 \uc218 \uc788\uc73c\ubbc0\ub85c \ub124\ud2b8\uc6cc\ud06c\uc5d0\uc11c IDS \uc704\uce58\ub97c \ucd5c\uc801\uc73c\ub85c \uacb0\uc815\ud558\ub294 \ubb38\uc81c\ub97c \ubd80\ubd84\uc801\uc73c\ub85c \uad00\ucc30 \uac00\ub2a5\ud55c \uc81c\ub85c\uc12c \ud655\ub960\ub860\uc801 \ucd5c\uc18c \uc704\ud611 \uacbd\ub85c \uac8c\uc784(POSMPG)\uc73c\ub85c \ubaa8\ub378\ub9c1<\/p>\n\n\n\n
        \uacf5\uaca9\uc790\uc758 \ubaa9\ud45c: \uc8fc\uc5b4\uc9c4 \uc21c\uac04\uc5d0 \ucd5c\ub300 \uac1c\uc218\uc758 \ub178\ub4dc\ub97c \uac10\uc5fc\uc2dc\ud0a4\ub294 \uac83, \ucd5c\uc801 \ubc29\uc815\uc2dd\uc744 \uc5bb\uae30 \uc704\ud574 \uc0c1\ud0dc \ud655\uc7a5 \ud655\ub960\ub860\uc801 \uac8c\uc784 \ud504\ub808\uc784\uc6cc\ud06c\ub97c \uc81c\uc548
        \u2192 POSMPG\uc758 \ucd5c\uc801 \uc194\ub8e8\uc158\uc744 \uacb0\uc815\ud558\uace0 \uadf8 \uacb0\uacfc\ub97c \ub124\ud2b8\uc6cc\ud06c\uc758 \ubc14\uc774\ub7ec\uc2a4 \uc804\ud30c\uc5d0 \ub300\ud55c \uc801\ub300\uc801 \uc81c\uc5b4\uc5d0 \uc801\uc6a9<\/p>\n\n\n\n
        * \uce68\uc785 \ud0d0\uc9c0 \uc2dc\uc2a4\ud15c(IDS): \uc0c1\ud638 \uc5f0\uacb0\ub41c \ub450 \uc7a5\uce58 \uac04\uc758 \ubc14\uc774\ub7ec\uc2a4 \uc804\ud30c \uac00\ub2a5\uc131\uc744 \ud0d0\uc9c0\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud558\ub294 \ubcf4\uc548 \ub3c4\uad6c<\/p>\n\n\n\n
        Voting Games to Model Protocol Stability and Security of Proof-of-Work Cryptocurrencies
        Sanjay Bhattacherjee and Palash Sarkar<\/mark><\/strong><\/h5>\n\n\n\n
        Abstract | dl.acm.org<\/a><\/p>\n\n\n\n
        \ud504\ub85c\ud1a0\ucf5c \uc548\uc815\uc131\uacfc \ubcf4\uc548\uc744 \ubaa8\ub378\ub9c1
        \uc554\ud638\ud654\ud3d0 \ucc44\uad74\uc790\uac00 \uc554\ud638\ud654\ud3d0 \ud504\ub85c\ud1a0\ucf5c \ubcc0\uacbd \uc81c\uc548\uc744 \uc218\ub77d\ud558\uac70\ub098 \uac70\ubd80\ud558\uae30 \uc704\ud574 \ud22c\ud45c \uc808\ucc28\uc5d0 \ucc38\uc5ec\ud558\ub294 \uc2dc\ub098\ub9ac\uc624\uc640 \uad00\ub828
        \ub450 \ubc88\uc9f8 \uac8c\uc784\uc740 \ucc44\uad74\uc790 \uadf8\ub8f9\uc774 \uc5f0\ud569\uc744 \ud615\uc131\ud558\uc5ec \uc2dc\uc2a4\ud15c\uc5d0 \ub300\ud55c \uacf5\uaca9\uc744 \uc2dc\uc791\ud558\uace0 \uacb0\uacfc\uc801\uc73c\ub85c \uae30\ubcf8 \ube14\ub85d\uccb4\uc778 \uae30\ub85d\uc758 \uc77c\ubd80\ub97c \ubcc0\uacbd\ud558\uc5ec \ubd88\ubcc0\uc131\uc5d0 \ub300\ud55c \uc57d\uc18d\uc744 \ubb34\ub108\ub728\ub9b4 \uc218 \uc788\ub294 \uc2dc\ub098\ub9ac\uc624
        \uaddc\uce59 \uac8c\uc784\uacfc \uacf5\uaca9 \uac8c\uc784 \ubaa8\ub450\uc5d0 \ub300\ud574 \ube44\ud2b8\ucf54\uc778\uc5d0 \ub300\ud55c \uc2e4\uc81c \ub370\uc774\ud130\uc758 \uc2a4\ub0c5\uc0f7\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud22c\ud45c \uac8c\uc784 \uc774\ub860 \ub3c4\uad6c\uc758 \uc2e4\uc81c \uc801\uc6a9 \uac00\ub2a5\uc131\uc744 \ubcf4\uc5ec\uc90c – \uacf5\uaca9\uacfc \uad00\ub828\ud558\uc5ec \ube44\ud2b8\ucf54\uc778 \u200b\u200b\ubcf4\uc548\uc758 \ucde8\uc57d\uc131\uc744 \uac15\uc870\ud568<\/p>\n\n\n\n
        <\/p>\n\n\n\n
        Cyber Deception Against Zero-Day Attacks: A Game Theoretic Approach
        Md Abu Sayed, Ahmed H. Anwar, Christopher Kiekintveld, Branislav Bosansky, and Charles Kamhoua<\/mark><\/strong><\/p>\n\n\n\n
        Using Deception in Markov Game to Understand Adversarial Behaviors Through a Capture-The-Flag Environment
        Siddhant Bhambri, Purv Chauhan, Frederico Araujo, Adam Doupe, and Subbarao Kambhampati<\/mark><\/strong>
        <\/p>\n\n\n\n
        References<\/h3>\n\n\n\n
        Decision and Game Theory for Security: 13th International Conference, GameSec 2022 Pittsburgh, PA, USA, October 26-28, 2022 Proceedings<\/a><\/p>\n\n\n\n
        <\/p>","protected":false},"excerpt":{"rendered":"
        Decision and Game Theory for Security: 13th International Conference, GameSec 2022 Pittsburgh, PA, USA, October 26-28, 2022 Proceedings<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[138],"tags":[135,4,134,136,133],"class_list":["post-2615","post","type-post","status-publish","format-standard","hentry","category-conference","tag-conference","tag-game-theory","tag-gamesec","tag-security","tag-sep-17-2023"],"_links":{"self":[{"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/posts\/2615"}],"collection":[{"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/comments?post=2615"}],"version-history":[{"count":37,"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/posts\/2615\/revisions"}],"predecessor-version":[{"id":2776,"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/posts\/2615\/revisions\/2776"}],"wp:attachment":[{"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/media?parent=2615"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/categories?post=2615"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saraheee.com\/ko\/wp-json\/wp\/v2\/tags?post=2615"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}