Emre Erturk

Emre Erturk, Mayank Kumar

First, this case study explores an Intrusion Detection System package called Snort (provided by Cisco Systems) in a cloud environment. Snort is an open source and highly scalable signature-based intrusion detection system. Here, Snort is deployed on Ubuntu Server 16.0.4 running on a virtual machine within a Microsoft Azure cloud system. This paper provides details on installing Snort on the virtual machine and configuring it for intrusion detection. The architecture here is based on a VM integrated IDS on Azure and demonstrates how a VM instance in the cloud can be secured through an IDS. Firewalls may be considered the first line of defense but they fail to secure systems from inside attacks. Next, two other areas (where Snort is less widely used) are briefly explored, namely library systems and mobile devices. Finally, this paper makes further recommendations on how a cloud network can be secured by distributed placement of the IDS and on each VM instances.

Emre Erturk

The goal of this paper is to analyze the behavior and intent of recent types of privacy invasive Android adware. There are two recent trends in this area: more financial motives instead of ego motives, and the development of more dynamic analysis tools. This paper starts with a review of Android mobile operating system security, and also addresses the pros and cons of open source operating system security. Static analysis of malware provides high quality results and leads to a good understanding as shown in this paper. However, as malware grows in number and complexity, there have been recent efforts to automate the detection mechanisms and many of the static tasks. As Android's market share is rapidly growing around the world. Android security will be a crucial area of research for IT security professionals and their academic counterparts. The upside of the current situation is that malware is being quickly exposed, thanks to open source software development tools. This cooperation is important in curbing the widespread theft of personal information with monetary value.

Emre Erturk, Angel Rajan

Cloud security is one of the biggest concerns for many companies. The growth in the number and size of websites increases the need for better securing those websites. Manual testing and detection of web vulnerabilities can be very time consuming. Automated Web Vulnerability Scanners (WVS) help with the detection of vulnerabilities in web applications. Acunetix is one of the widely used vulnerability scanners. Acunetix is also easy to implement and to use. The scan results not only provide the details of the vulnerabilities, but also give information about fixing the vulnerabilities. AcuSensor and AcuMonitor (technologies used by Acunetix) help generate more accurate potential vulnerability results. One of the purposes of this paper is to orient current students of computer security with using vulnerability scanners. Secondly, this paper provides a literature review related to the topic of security vulnerability scanners. Finally, web vulnerabilities are addressed from the mobile device and browser perspectives.

Emre Erturk, Hong Shi

Natural language processing, as a data analytics related technology, is used widely in many research areas such as artificial intelligence, human language processing, and translation. At present, due to explosive growth of data, there are many challenges for natural language processing. Hadoop is one of the platforms that can process the large amount of data required for natural language processing. KOSHIK is one of the natural language processing architectures, and utilizes Hadoop and contains language processing components such as Stanford CoreNLP and OpenNLP. This study describes how to build a KOSHIK platform with the relevant tools, and provides the steps to analyze wiki data. Finally, it evaluates and discusses the advantages and disadvantages of the KOSHIK architecture, and gives recommendations on improving the processing performance.

Emre Erturk

In order to effectively prepare the next generation of IT professionals and systems analysts, it is important to incorporate cloud based online collaboration tools into the coursework for developing the students' cooperative skills as well as for storing and sharing content. For these pedagogical and practical reasons, Google Drive has been used at a medium-sized institution of higher education in New Zealand during the Systems Analysis and Design course. Ongoing and successful use of any learning technology requires gathering meaningful feedback from students, and acting as a mentor during their learning journey. This study has been developed and implemented to help students enjoy the collaborative technology and to help increase their satisfaction and commitment. In order to overcome the obstacles that may prevent students from using Google Drive optimally, an initial survey has been conducted to better understand the influential factors and issues. Furthermore, this study aims at promoting various types of collaboration and sharing: seeing and learning from other students' work, receiving direct suggestions from others, and allowing others to edit documents that belong to them. Following the results of the first quantitative survey, numerous teaching strategies were formulated and implemented. A final qualitative survey was done at the end of the course for students to evaluate their project work. The results of this study also provide original practical and theoretical implications that may be of interest to other researchers, course designers, and teachers.