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インシデント 509: Scammers Deepfaked Videos of Victims' Loved Ones Asking for Funds over Facebook in Vietnam

概要: In Vietnam, to convince victims of their disguises when prompted, scammers deepfaked audios and videos of victims' friends and families asking them over Facebook to send over thousands of dollars.

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組織

すべての組織を表示
Alleged: unknown developed an AI system deployed by scammers, which harmed Vietnamese Facebook users.

インシデントのステータス

インシデントID
509
レポート数
2
インシデント発生日
2023-03-23
エディタ
Khoa Lam
Applied Taxonomies
CSETv1, MIT

CSETv1 分類法のクラス

分類法の詳細

Incident Number

The number of the incident in the AI Incident Database.
 

509

Special Interest Intangible Harm

An assessment of whether a special interest intangible harm occurred. This assessment does not consider the context of the intangible harm, if an AI was involved, or if there is characterizable class or subgroup of harmed entities. It is also not assessing if an intangible harm occurred. It is only asking if a special interest intangible harm occurred.
 

maybe

Date of Incident Year

The year in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the year, estimate. Otherwise, leave blank. Enter in the format of YYYY
 

2023

Date of Incident Month

The month in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the month, estimate. Otherwise, leave blank. Enter in the format of MM
 

03

Date of Incident Day

The day on which the incident occurred. If a precise date is unavailable, leave blank. Enter in the format of DD
 

Estimated Date

“Yes” if the data was estimated. “No” otherwise.
 

No

MIT 分類法のクラス

Machine-Classified
分類法の詳細

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

4.3. Fraud, scams, and targeted manipulation

Risk Domain

The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
 
  1. Malicious Actors & Misuse

Entity

Which, if any, entity is presented as the main cause of the risk
 

Human

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Post-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Intentional

インシデントレポート

レポートタイムライン

Incident OccurrenceNở rộ chiêu thức ghép mặt, giả giọng để mượn tiền bằng ứng dụng DeepfakeDeepfake posing grave danger as scamming tool
Nở rộ chiêu thức ghép mặt, giả giọng để mượn tiền bằng ứng dụng Deepfake

Nở rộ chiêu thức ghép mặt, giả giọng để mượn tiền bằng ứng dụng Deepfake

dttc.sggp.org.vn

Deepfake posing grave danger as scamming tool

Deepfake posing grave danger as scamming tool

vietnamnet.vn

Nở rộ chiêu thức ghép mặt, giả giọng để mượn tiền bằng ứng dụng Deepfake
dttc.sggp.org.vn · 2023

(ĐTTCO) - Sau trò lừa đảo bằng tin nhắn nhờ chuyển tiền, hiện các đối tượng lừa đảo nhanh chóng áp dụng chiêu thức khác tinh vi hơn, thông qua cuộc gọi video giả mạo nhờ công nghệ Deepfake.

Đánh lừa người dùng

Sau gần một tuần bị lừa mất số…

Deepfake posing grave danger as scamming tool
vietnamnet.vn · 2023

After being detected with tricks of sending messages to appropriate money, scammers are now using an even more sophisticated tool called Deepfake to make fake video calls to victims and ask for money transfer.

Nearly a week after discoverin…

バリアント

「バリアント」は既存のAIインシデントと同じ原因要素を共有し、同様な被害を引き起こし、同じ知的システムを含んだインシデントです。バリアントは完全に独立したインシデントとしてインデックスするのではなく、データベースに最初に投稿された同様なインシデントの元にインシデントのバリエーションとして一覧します。インシデントデータベースの他の投稿タイプとは違い、バリアントではインシデントデータベース以外の根拠のレポートは要求されません。詳細についてはこの研究論文を参照してください

よく似たインシデント

テキスト類似度による

Did our AI mess up? Flag the unrelated incidents

Reported AI-Cloned Voice Used to Deceive Hong Kong Bank Manager in Purported $35 Million Fraud Scheme

Bank Robbers Steal $35 Million by Deepfaking Boss's Voice

Jan 2020 · 6 レポート
A Chinese Tech Worker at Zhihu Fired Allegedly via a Resignation Risk Prediction Algorithm

Chinese tech workers outraged by surveillance tool that flags employees who look likely to quit

Feb 2022 · 4 レポート
Picture of Woman on Side of Bus Shamed for Jaywalking

Chinese AI caught out by face in bus ad

Nov 2018 · 24 レポート
前のインシデント次のインシデント

よく似たインシデント

テキスト類似度による

Did our AI mess up? Flag the unrelated incidents

Reported AI-Cloned Voice Used to Deceive Hong Kong Bank Manager in Purported $35 Million Fraud Scheme

Bank Robbers Steal $35 Million by Deepfaking Boss's Voice

Jan 2020 · 6 レポート
A Chinese Tech Worker at Zhihu Fired Allegedly via a Resignation Risk Prediction Algorithm

Chinese tech workers outraged by surveillance tool that flags employees who look likely to quit

Feb 2022 · 4 レポート
Picture of Woman on Side of Bus Shamed for Jaywalking

Chinese AI caught out by face in bus ad

Nov 2018 · 24 レポート

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