Language Selection

English French German Italian Portuguese Spanish

Japan cardholders 'hit' by theft

Filed under
Security

Up to 40 million credit card accounts were compromised, after the breach of security at Cardsystems.

The theft affected mostly Mastercard and Visa clients, but American Express and Discovery customers were also hit.

Fraudulent transactions have now emerged in Japan, where as many as 26 credit firms are linked to Mastercard.

The Japanese government warned that almost all 26 domestic credit firms may have been affected.
UFJ, one of Japan's biggest banks, said that there have been about 20 suspect transactions reported by customers at its credit card division.

UCS, a credit card firm affiliated with supermarket chain Uny, also said that more than 100 of its clients may have been affected, while there are concerns about cards issued by a number of regional banks.

In Hong Kong, lenders have warned their customers, but said that only a "small number" need worry.

At least 200,000 individual records are known to have been stolen, following the breach of security at Arizona-based Cardsystems.

Speaking in an interview with the New York Times on Monday, the chief executive of Cardsystems John Perry said that the firm had not followed security measures put in place by Mastercard and Visa.

It had held on to personal data for research purposes, instead of removing it once the transaction was complete, he said.
"We should not have been doing that," he told the New York Times.

Mastercard has sought to reassure customers, saying that social security numbers, the golden egg of personal information, had not been compromised.

News of the theft has prompted calls for greater regulation of the 500 or so firms that process credit card transactions in the US.

Full Story.

More in Tux Machines

today's howtos

Red Hat and Fedora

Android Leftovers

Leftovers: OSS and Sharing

  • Apache Graduates Another Big Data Project to Top Level
    For the past year, we've taken note of the many projects that the Apache Software Foundation has been elevating to Top-Level Status. The organization incubates more than 350 open source projects and initiatives, and has squarely turned its focus to Big Data and developer-focused tools in recent months. As Apache moves Big Data projects to Top-Level Status, they gain valuable community support. Only days ago, the foundation announced that Apache Kudu has graduated from the Apache Incubator to become a Top-Level Project (TLP). Kudu is an open source columnar storage engine built for the Apache Hadoop ecosystem designed to enable flexible, high-performance analytic pipelines. And now, Apache Twill has graduated as well. Twill is an abstraction over Apache Hadoop YARN that reduces the complexity of developing distributed Hadoop applications, allowing developers to focus more on their application logic.
  • Spark 2.0 takes an all-in-one approach to big data
    Apache Spark, the in-memory processing system that's fast become a centerpiece of modern big data frameworks, has officially released its long-awaited version 2.0. Aside from some major usability and performance improvements, Spark 2.0's mission is to become a total solution for streaming and real-time data. This comes as a number of other projects -- including others from the Apache Foundation -- provide their own ways to boost real-time and in-memory processing.
  • Why Uber Engineering Switched from Postgres to MySQL
    The early architecture of Uber consisted of a monolithic backend application written in Python that used Postgres for data persistence. Since that time, the architecture of Uber has changed significantly, to a model of microservices and new data platforms. Specifically, in many of the cases where we previously used Postgres, we now use Schemaless, a novel database sharding layer built on top of MySQL. In this article, we’ll explore some of the drawbacks we found with Postgres and explain the decision to build Schemaless and other backend services on top of MySQL.
  • GNU Hyperbole 6.0.1 for Emacs 24.4 to 25 is released
    GNU Hyperbole (pronounced Ga-new Hi-per-bo-lee), or just Hyperbole, is an amazing programmable hypertextual information management system implemented as a GNU Emacs package. This is the first public release in 2016. Hyperbole has been greatly expanded and modernized for use with the latest Emacs 25 releases; it supports GNU Emacs 24.4 or above. It contains an extensive set of improvements that can greatly boost your day-to-day productivity with Emacs and your ability to manage information stored across many different machines on the internet. People who get used to Hyperbole find it helps them so much that they prefer never to use Emacs without it.
  • Belgium mulls reuse of banking mobile eID app
    The Belgium government wants to reuse ‘Belgian Mobile ID’ a smartphone app for electronic identification, developed by banks and telecom providers in the country. The eID app could be used for eGovernment services, and the federal IT service agency, Fedict, is working on the app’s integration.
  • Water resilience that flows: Open source technologies keep an eye on the water flow
    Communities around the world are familiar with the devastation brought on by floods and droughts. Scientists are concerned that, in light of global climate change, these events will only become more frequent and intense. Water variability, at its worst, can threaten the lives and well-beings of countless people. Sadly, humans cannot control the weather to protect themselves. But according to Silja Hund, a researcher at the University of British Columbia, communities can build resilience to water resource stress. Hund studies the occurrence and behavior of water. In particular, she studies rivers and streams. These have features (like water volume) that can change quickly. According to Hund, it is essential for communities to understand local water systems. Knowledge of water resources is helpful in developing effective water strategies. And one of the best ways to understand dynamic water bodies like rivers is to collect lots of data.