JP7223579B2 - 予測されるサイバー防御 - Google Patents
予測されるサイバー防御 Download PDFInfo
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- JP7223579B2 JP7223579B2 JP2019001900A JP2019001900A JP7223579B2 JP 7223579 B2 JP7223579 B2 JP 7223579B2 JP 2019001900 A JP2019001900 A JP 2019001900A JP 2019001900 A JP2019001900 A JP 2019001900A JP 7223579 B2 JP7223579 B2 JP 7223579B2
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/1466—Active attacks involving interception, injection, modification, spoofing of data unit addresses, e.g. hijacking, packet injection or TCP sequence number attacks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1425—Traffic logging, e.g. anomaly detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/55—Detecting local intrusion or implementing counter-measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/57—Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
- G06F21/577—Assessing vulnerabilities and evaluating computer system security
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
- G06N20/20—Ensemble learning
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1433—Vulnerability analysis
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/18—Network architectures or network communication protocols for network security using different networks or channels, e.g. using out of band channels
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/20—Network architectures or network communication protocols for network security for managing network security; network security policies in general
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/03—Indexing scheme relating to G06F21/50, monitoring users, programs or devices to maintain the integrity of platforms
- G06F2221/034—Test or assess a computer or a system
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- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- General Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Data Mining & Analysis (AREA)
- Artificial Intelligence (AREA)
- Medical Informatics (AREA)
- Mathematical Physics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Debugging And Monitoring (AREA)
Description
・ターゲットシステムが同一又は類似する攻撃に屈することがある可能性、P(システム)202;
・資産が同一又は類似する攻撃に屈することがある可能性、P(資産)204;
・異なる資産間の接続経路が同一又は類似する攻撃に屈することがある可能性、P(経路)206;又は
・システムへの侵入点が同一又は類似する攻撃に屈することがある可能性、P(侵入)208。
- 情報抽出サブシステム300により識別される資産に最も近く一致する保護システム内で動作される資産(インシデントレポートにおいて、他の場所で現在攻撃を受けている資産に最も近く一致する保護システムの資産)の識別(例えばリスト)。
- 一又は複数のキーワードが、情報抽出サブシステム300によって出力されたキーワードに対する保護資産の関連付け310と一致する、脅威シナリオ又は過去の異常の識別。
・一連の異常事象、根本原因、侵入点、脅威の軌跡等の、情報抽出サブシステム300の任意の他の形態の出力についてのパターンマッチング。
- 例えば保守要員がラップトップを航空機のシステム又はワイヤレスアクセスポイントに接続するときに、サブシステム300及びサブシステム400によって導き出された概念を含む、異常挙動の最も重要な要因の視覚的表現。
- 将来的な参照及び/又は分析のための更新。
Claims (10)
- 複数のネットワーク資産(200)の予想されるサイバー防御のコンピュータにより実施される方法であって、
複数のサイバーインシデントレポート(302、902)を受領すること(1102);
前記複数のサイバーインシデントレポートからキーワードを抽出すること(300、1104);
前記複数のネットワーク資産の少なくとも前記キーワード及び識別に浅層機械学習技術(400、1106)を適用して、少なくとも第1の脅威シナリオに対して脆弱な前記ネットワーク資産の第1のサブセットの識別及び前記第1の脅威シナリオの識別を得ること;
前記第1の脅威シナリオに対して脆弱な前記ネットワーク資産の第1のサブセットの少なくとも前記識別、前記第1の脅威シナリオの前記識別、前記キーワード、及び前記複数のネットワーク資産の識別に、深層機械学習技術(600、1108)を適用して、少なくとも第2の脅威シナリオに対して脆弱な前記ネットワーク資産の第2のサブセットの識別及び前記第2の脅威シナリオの識別を得ること;
前記複数のネットワーク資産及び前記第2の脅威シナリオをシミュレートして、少なくとも第3の脅威シナリオに対して脆弱な前記複数のネットワーク資産を通る少なくとも一つの経路を識別すること(700、1110);並びに
前記複数のネットワーク資産を通る前記少なくとも一つの経路の識別及び前記少なくとも第3の脅威シナリオの識別を出力すること(1112)
を含む、方法。 - 少なくとも前記第3の脅威シナリオに対する改善策を取ることをさらに含む、請求項1に記載の方法。
- 前記浅層機械学習技術が最近傍技術を含む、請求項1又は2に記載の方法。
- 前記深層機械学習技術が、ニューラルネットワーク技術、相関ルールマイニング技術、又は語埋め込み技術を含む、請求項1から3のいずれか一項に記載の方法。
- 前記シミュレートすることが離散事象シミュレーション(DES)エンジン(704)により実施される、請求項1から4のいずれか一項に記載の方法。
- 前記シミュレートすることにより識別される多くの経路を制限することをさらに含む、請求項1から5のいずれか一項に記載の方法。
- 前記複数のサイバーインシデントレポートからキーワードを抽出することが、前記複数のサイバーインシデントレポートから、少なくとも一つの履歴異常のデータベースから、少なくとも一つの脅威シナリオデータベースから、且つ資産データベースからキーワードを抽出することをさらに含む、請求項1から6のいずれか一項に記載の方法。
- 複数のネットワーク資産(200)の予測されるサイバー防御のためのシステム(1200)であって、
複数のサイバーインシデントレポート(302、902)を受領すること(1102);
前記複数のサイバーインシデントレポートからキーワードを抽出すること(300、1104);
前記複数のネットワーク資産の少なくとも前記キーワード及び識別に浅層機械学習技術(400、1106)を適用して、少なくとも第1の脅威シナリオに対して脆弱な前記ネットワーク資産の第1のサブセットの識別及び前記第1の脅威シナリオの識別を得ること;
前記第1の脅威シナリオに対して脆弱な前記ネットワーク資産の第1のサブセットの少なくとも前記識別、前記第1の脅威シナリオの前記識別、前記キーワード、及び前記複数のネットワーク資産の識別に、深層機械学習技術(600、1108)を適用して、少なくとも第2の脅威シナリオに対して脆弱な前記ネットワーク資産の第2のサブセットの識別及び前記第2の脅威シナリオの識別を得ること;
前記複数のネットワーク資産及び前記第2の脅威シナリオをシミュレートして、少なくとも第3の脅威シナリオに対して脆弱な前記複数のネットワーク資産を通る少なくとも一つの経路を識別すること(700、1110);並びに
前記複数のネットワーク資産を通る前記少なくとも一つの経路の識別及び前記少なくとも第3の脅威シナリオの識別を出力すること(1112)
を実施するよう構成された少なくとも一つの電子プロセッサを含む、システム(1200)。 - 前記少なくとも一つの電子プロセッサが、少なくとも前記第3の脅威シナリオに対する改善策を取るようさらに構成されている、請求項8に記載のシステム。
- 前記浅層機械学習技術が最近傍技術を含む、請求項8又は9に記載のシステム。
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
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US15/870,275 | 2018-01-12 | ||
US15/870,275 US10812510B2 (en) | 2018-01-12 | 2018-01-12 | Anticipatory cyber defense |
Publications (2)
Publication Number | Publication Date |
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JP2019145091A JP2019145091A (ja) | 2019-08-29 |
JP7223579B2 true JP7223579B2 (ja) | 2023-02-16 |
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JP2019001900A Active JP7223579B2 (ja) | 2018-01-12 | 2019-01-09 | 予測されるサイバー防御 |
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US (1) | US10812510B2 (ja) |
EP (1) | EP3512176B1 (ja) |
JP (1) | JP7223579B2 (ja) |
KR (1) | KR102590773B1 (ja) |
CN (1) | CN110035049B (ja) |
AU (1) | AU2018250491B2 (ja) |
BR (1) | BR102018074362A2 (ja) |
CA (1) | CA3021168C (ja) |
RU (1) | RU2018136768A (ja) |
Families Citing this family (23)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20190318223A1 (en) * | 2018-04-12 | 2019-10-17 | Georgia Tech Research Corporation | Methods and Systems for Data Analysis by Text Embeddings |
US10749890B1 (en) | 2018-06-19 | 2020-08-18 | Architecture Technology Corporation | Systems and methods for improving the ranking and prioritization of attack-related events |
US10817604B1 (en) | 2018-06-19 | 2020-10-27 | Architecture Technology Corporation | Systems and methods for processing source codes to detect non-malicious faults |
US11601442B2 (en) | 2018-08-17 | 2023-03-07 | The Research Foundation For The State University Of New York | System and method associated with expedient detection and reconstruction of cyber events in a compact scenario representation using provenance tags and customizable policy |
US11429713B1 (en) * | 2019-01-24 | 2022-08-30 | Architecture Technology Corporation | Artificial intelligence modeling for cyber-attack simulation protocols |
US11128654B1 (en) | 2019-02-04 | 2021-09-21 | Architecture Technology Corporation | Systems and methods for unified hierarchical cybersecurity |
US11675915B2 (en) * | 2019-04-05 | 2023-06-13 | International Business Machines Corporation | Protecting data based on a sensitivity level for the data |
US11301578B2 (en) | 2019-04-05 | 2022-04-12 | International Business Machines Corporation | Protecting data based on a sensitivity level for the data |
US11652839B1 (en) * | 2019-05-02 | 2023-05-16 | Architecture Technology Corporation | Aviation system assessment platform for system-level security and safety |
US11403405B1 (en) | 2019-06-27 | 2022-08-02 | Architecture Technology Corporation | Portable vulnerability identification tool for embedded non-IP devices |
JP7074739B2 (ja) | 2019-10-21 | 2022-05-24 | 矢崎総業株式会社 | 脆弱性評価装置 |
US11444974B1 (en) | 2019-10-23 | 2022-09-13 | Architecture Technology Corporation | Systems and methods for cyber-physical threat modeling |
US11503075B1 (en) | 2020-01-14 | 2022-11-15 | Architecture Technology Corporation | Systems and methods for continuous compliance of nodes |
US12081576B2 (en) * | 2020-04-30 | 2024-09-03 | Arizona Board Of Regents On Behalf Of Arizona State University | Systems and methods for improved cybersecurity named-entity-recognition considering semantic similarity |
CN112104656B (zh) * | 2020-09-16 | 2022-07-12 | 杭州安恒信息安全技术有限公司 | 一种网络威胁数据获取方法、装置、设备及介质 |
US11924239B2 (en) | 2020-10-23 | 2024-03-05 | International Business Machines Corporation | Vulnerability and attack technique association |
KR102287394B1 (ko) * | 2020-12-21 | 2021-08-06 | 한국인터넷진흥원 | 익스플로잇 공격 유형 분류 방법 및 그 장치 |
WO2023009795A1 (en) * | 2021-07-30 | 2023-02-02 | Epiphany Systems, Inc. | Systems and methods for applying reinforcement learning to cybersecurity graphs |
US12081571B2 (en) * | 2021-07-30 | 2024-09-03 | Reveald Holdings, Inc. | Graphics processing unit optimization |
US20230141928A1 (en) * | 2021-10-13 | 2023-05-11 | Oracle International Corporation | Adaptive network attack prediction system |
KR102592624B1 (ko) * | 2021-12-14 | 2023-10-24 | (주)유엠로직스 | 사회이슈형 사이버 표적공격의 대응을 위한 인공지능 기법을 이용한 위협 헌팅 시스템 및 그 방법 |
KR102562671B1 (ko) * | 2021-12-16 | 2023-08-03 | (주)유엠로직스 | 사회이슈형 사이버 표적공격의 대응을 위한 유전 알고리즘을 이용한 위협 헌팅 시스템 및 그 방법 |
WO2023181145A1 (ja) | 2022-03-23 | 2023-09-28 | 三菱電機株式会社 | リスク抽出装置、リスク抽出方法、リスク抽出プログラム |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2014102555A (ja) | 2012-11-16 | 2014-06-05 | Ntt Docomo Inc | 判別ルール生成装置及び判別ルール生成方法 |
WO2014208427A1 (ja) | 2013-06-24 | 2014-12-31 | 日本電信電話株式会社 | セキュリティ情報管理システム及びセキュリティ情報管理方法 |
US20170228658A1 (en) | 2015-07-24 | 2017-08-10 | Certis Cisco Security Pte Ltd | System and Method for High Speed Threat Intelligence Management Using Unsupervised Machine Learning and Prioritization Algorithms |
Family Cites Families (24)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8983889B1 (en) * | 1996-03-25 | 2015-03-17 | Martin L. Stoneman | Autonomous humanoid cognitive systems |
US9027121B2 (en) * | 2000-10-10 | 2015-05-05 | International Business Machines Corporation | Method and system for creating a record for one or more computer security incidents |
US20090043637A1 (en) * | 2004-06-01 | 2009-02-12 | Eder Jeffrey Scott | Extended value and risk management system |
US7296007B1 (en) * | 2004-07-06 | 2007-11-13 | Ailive, Inc. | Real time context learning by software agents |
US8312549B2 (en) * | 2004-09-24 | 2012-11-13 | Ygor Goldberg | Practical threat analysis |
US7640583B1 (en) | 2005-04-01 | 2009-12-29 | Microsoft Corporation | Method and system for protecting anti-malware programs |
US9824609B2 (en) * | 2011-04-08 | 2017-11-21 | Wombat Security Technologies, Inc. | Mock attack cybersecurity training system and methods |
US9558677B2 (en) * | 2011-04-08 | 2017-01-31 | Wombat Security Technologies, Inc. | Mock attack cybersecurity training system and methods |
CN103312679B (zh) * | 2012-03-15 | 2016-07-27 | 北京启明星辰信息技术股份有限公司 | 高级持续威胁的检测方法和系统 |
US10122747B2 (en) * | 2013-12-06 | 2018-11-06 | Lookout, Inc. | Response generation after distributed monitoring and evaluation of multiple devices |
US11122058B2 (en) * | 2014-07-23 | 2021-09-14 | Seclytics, Inc. | System and method for the automated detection and prediction of online threats |
WO2016022705A1 (en) * | 2014-08-05 | 2016-02-11 | AttackIQ, Inc. | Cyber security posture validation platform |
US9710648B2 (en) | 2014-08-11 | 2017-07-18 | Sentinel Labs Israel Ltd. | Method of malware detection and system thereof |
US10574675B2 (en) * | 2014-12-05 | 2020-02-25 | T-Mobile Usa, Inc. | Similarity search for discovering multiple vector attacks |
CN104965812B (zh) * | 2015-07-13 | 2017-12-01 | 深圳市腾讯计算机系统有限公司 | 一种深层模型处理方法及装置 |
US9699205B2 (en) * | 2015-08-31 | 2017-07-04 | Splunk Inc. | Network security system |
CN106878262B (zh) * | 2016-12-19 | 2021-04-16 | 新华三技术有限公司 | 报文检测方法及装置、建立本地威胁情报库的方法及装置 |
US10367846B2 (en) * | 2017-11-15 | 2019-07-30 | Xm Cyber Ltd. | Selectively choosing between actual-attack and simulation/evaluation for validating a vulnerability of a network node during execution of a penetration testing campaign |
CN107040795A (zh) * | 2017-04-27 | 2017-08-11 | 北京奇虎科技有限公司 | 一种直播视频的监控方法和装置 |
US10819718B2 (en) * | 2017-07-05 | 2020-10-27 | Deep Instinct Ltd. | Methods and systems for detecting malicious webpages |
CN107465667B (zh) * | 2017-07-17 | 2019-10-18 | 全球能源互联网研究院有限公司 | 基于规约深度解析的电网工控安全协同监测方法及装置 |
US10885469B2 (en) | 2017-10-02 | 2021-01-05 | Cisco Technology, Inc. | Scalable training of random forests for high precise malware detection |
US10673871B2 (en) | 2017-10-04 | 2020-06-02 | New Context Services, Inc. | Autonomous edge device for monitoring and threat detection |
US10841333B2 (en) | 2018-01-08 | 2020-11-17 | Sophos Limited | Malware detection using machine learning |
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2018
- 2018-01-12 US US15/870,275 patent/US10812510B2/en active Active
- 2018-10-16 CA CA3021168A patent/CA3021168C/en active Active
- 2018-10-18 RU RU2018136768A patent/RU2018136768A/ru unknown
- 2018-10-19 AU AU2018250491A patent/AU2018250491B2/en active Active
- 2018-11-12 KR KR1020180137811A patent/KR102590773B1/ko active IP Right Grant
- 2018-11-26 BR BR102018074362-7A patent/BR102018074362A2/pt unknown
- 2018-12-06 EP EP18210674.0A patent/EP3512176B1/en active Active
- 2018-12-06 CN CN201811487623.0A patent/CN110035049B/zh active Active
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- 2019-01-09 JP JP2019001900A patent/JP7223579B2/ja active Active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2014102555A (ja) | 2012-11-16 | 2014-06-05 | Ntt Docomo Inc | 判別ルール生成装置及び判別ルール生成方法 |
WO2014208427A1 (ja) | 2013-06-24 | 2014-12-31 | 日本電信電話株式会社 | セキュリティ情報管理システム及びセキュリティ情報管理方法 |
US20170228658A1 (en) | 2015-07-24 | 2017-08-10 | Certis Cisco Security Pte Ltd | System and Method for High Speed Threat Intelligence Management Using Unsupervised Machine Learning and Prioritization Algorithms |
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KR20190086346A (ko) | 2019-07-22 |
CA3021168C (en) | 2023-02-14 |
RU2018136768A (ru) | 2020-04-20 |
EP3512176A1 (en) | 2019-07-17 |
CN110035049A (zh) | 2019-07-19 |
JP2019145091A (ja) | 2019-08-29 |
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AU2018250491B2 (en) | 2023-09-28 |
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US10812510B2 (en) | 2020-10-20 |
AU2018250491A1 (en) | 2019-08-01 |
KR102590773B1 (ko) | 2023-10-17 |
US20190222593A1 (en) | 2019-07-18 |
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