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Gootloader infection cleaned up

Dear blog owner and visitors,

This blog had been infected to serve up Gootloader malware to Google search victims, via a common tactic known as SEO (Search Engine Optimization) poisioning. Your blog was serving up 72 malicious pages. Your blogged served up malware to 0 visitors.

I tried my best to clean up the infection, but I would do the following:

  • Upgrade WordPress to the latest version (one way the attackers might have gained access to your server)
  • Upgrade all WordPress themes to the latest versions (another way the attackers might have gained access to your server)
  • Upgrade all WordPress plugins (another way the attackers might have gained access to your server), and remove any unnecessary plugins.
  • Verify all users are valid (in case the attackers left a backup account, to get back in)
  • Change all passwords (for WordPress accounts, FTP, SSH, database, etc.) and keys. This is probably how the attackers got in, as they are known to brute force weak passwords
  • Run antivirus scans on your server
  • Block these IPs ( and, either in your firewall, .htaccess file, or in your /etc/hosts file, as these are the attackers command and control servers, which send malicious commands for your blog to execute
  • Check cronjobs (both server and WordPress), aka scheduled tasks. This is a common method that an attacker will use to get back in. If you are not sure, what this is, Google it
  • Consider wiping the server completly, as you do not know how deep the infection is. If you decide not to, I recommend installing some security plugins for WordPress, to try and scan for any remaining malicious files. Integrity Checker, WordPress Core Integrity Checker, Sucuri Security,
    and Wordfence Security, all do some level of detection, but not 100% guaranteed
  • Go through the process for Google to recrawl your site, to remove the malcious links (to see what malicious pages there were, Go to Google and search site:your_site.com agreement)
  • Check subdomains, to see if they were infected as well
  • Check file permissions

Gootloader (previously Gootkit) malware has been around since 2014, and is used to initally infect a system, and then sell that access off to other attackers, who then usually deploy additional malware, to include ransomware and banking trojans. By cleaning up your blog, it will make a dent in how they infect victims. PLEASE try to keep it up-to-date and secure, so this does not happen again.


The Internet Janitor

Below are some links to research/further explaination on Gootloader:





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Invited talk about Flipped Classroom

Who: Professor Ljiljana Stevovic-Brankovic, The University of Newcastle, Australia

Title: “Flipped Classroom, Dynamic Worked Examples and Gamification of Computer Science Courses”

When: Thursday, 28th April, 12:30-13:30
Where: Acm15 C1/2.1.009 (25 pers)

Abstract:  Flipped classroom is a teaching method in which the students watch pre-recorded lectures before actually coming to the class. It is a type of blended, learner-centred model that enables skills such as teamwork, problem solving and higher order thinking. Flipped Classroom is now becoming more widespread and has found its way into many universities in USA, Australia and world-wide. In computer science and software engineering programs, many students many students already work part time in their second or third year.  Therefore, their opportunities for attending all lectures and tutorials are greatly reduced. In such an environment, it is important to provide a blended learning environment to give equal opportunities to bot working and studying-only student cohorts. Gamification refers to the use of elements of games in non-game contexts and has been applied in workplace, marketing, health programs and other areas, with mounting evidence of increased interest, involvement, satisfaction and performance of the participants. More recently gamification has been emerging as a teaching method that has a great potential to improve students’ motivation and engagement. Gamification in education should not be confused with playing educational games, as it only uses concepts such as points, leader boards, etc, rather than computer games themselves.

In this talk we describe our experience with introducing flipped classroom, dynamic worked examples and gamification in  two theoretical computer science courses, namely Introduction to Algorithmic and data Security. Majority of the students felt that Flipped Classroom is helpful and should be introduced into other computer science and software engineering courses.  They also thought that the quizzes both motivated them to watch the lecture recordings before coming to the class,  and were helpful for their learning. In addition to student perception, it appears that Flipped Classroom helps improve the learning outcomes. In both courses, the percentage of High Distinctions remained similar after introducing Flipped Classroom, while the percentage of Distinctions,  or Distinctions and Credits increased. In both courses the percentages of Passes and Fails dropped.  Through the Games we observed improved student motivation, engagement and commitment.  It was almost always hard to get students to submit their work and leave the classroom at the end of Game sessions as they always worked to the last minute and felt they had more to add to their papers. Anonymous student surveys that we conducted indicated that gamification supported their learning and motivation, and that these outcomes improved with second and third Games implementations as we learned what worked and what did not.

Professor Ljiljana Brankovic
Assistant Dean (Student Engagement)
Faculty of Engineering & Built Environment
The University of Newcastle
Callaghan NSW 2308

E-mail: Ljiljana.Brankovic@newcastle.edu.au
Tel: 61 2 4921 6054
Fax: 61 2 4921 6929

Student Project exploring Musical Museum Experience accepted to NIME Conference

“A Mobile Music Museum Experience for Children”
(Video: http://youtu.be/grPzyDW6G_Q)

by Mikkel Helleberg Jørgensen, Aske Sønderby Knudsen, Thomas Michael Wilmot, Kasper Duemose Lund, Stefania Serafin, Hendrik Purwins
has been accepted as a demo at The International Conference on New Interfaces for Musical Expression (NIME) 2015:

Talk by Mads Græsbøll Christensen & Hendrik Purwins

Mads Græsbøll Christensen & Hendrik Purwins, Audio Analysis Lab, Aalborg University gave talk at the Danish Neuroscience Center in connection with the Music in the Brain Seminars.

The Audio Analysis Lab, Modelling Musical Category Formation, and Neural Correlates of Musical Attention.


The talk has three parts:
I. The Audio Analysis Lab was founded in 2012 and is located at the Dept. of Architecture, Design & Media Technology at Aalborg University in Denmark. The lab conducts basic and applied research in signal processing theory and methods aimed at or involving analysis of audio signals. The research currently focuses on audio processing for communication systems (VoIP, cellphones, etc.), hearing aids, music equipment, surveillance, and audio archives (e.g., compression and information retrieval). In this talk, we will present the lab, its members and our ongoing major projects and highlight our biggest contributions so far.
II. We present a system that learns the rhythmical structure of percussion sequences from an audio example in an unsupervised manner, providing a representation that can be used for the generation of stylistically similar and musically interesting variations. The procedure consists of segmentation and symbolization (feature extraction, clustering, sequence structure analysis, temporal alignment). In a top-down manner, an entropy-based regularity measure determines the number of clusters into which the samples are grouped. A variant of that system that adjusts the number of (timbre) clusters instantaneously to the audio input. A sequence learning algorithm adapts its structure to a dynamically changing clustering tree. The prediction of the entire system is evaluated using the adjusted Rand Index, yielding good results.
III. In a multi-streamed oddball experiment, we had participants shift selective attention to one out of three different instruments in music audio clips. Contrasting attended versus unattended instruments, ERP analysis shows subject- and instrument-specific responses including P300 and early auditory components. The attended instrument can be classified online with a mean accuracy of 91% across 11 participants. This is a proof of concept that attention paid to a particular instrument in polyphonic music can be inferred from ongoing EEG, a finding that is potentially relevant for both brain-computer interface and music research.