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Ceron, J. M., Scholten, C., Pras, A., Santanna, J..  2020.  MikroTik Devices Landscape, Realistic Honeypots, and Automated Attack Classification. NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium. :1—9.

In 2018, several malware campaigns targeted and succeed to infect millions of low-cost routers (malwares e.g., VPN-Filter, Navidade, and SonarDNS). These routers were used, then, for all sort of cybercrimes: from DDoS attacks to ransomware. MikroTik routers are a peculiar example of low-cost routers. These routers are used to provide both last mile access to home users and are used in core network infrastructure. Half of the core routers used in one of the biggest Internet exchanges in the world are MikroTik devices. The problem is that vulnerable firmwares (RouterOS) used in homeusers houses are also used in core networks. In this paper, we are the first to quantify the problem that infecting MikroTik devices would pose to the Internet. Based on more than 4 TB of data, we reveal more than 4 million MikroTik devices in the world. Then, we propose an easy-to-deploy MikroTik honeypot and collect more than 17 millions packets, in 45 days, from sensors deployed in Australia, Brazil, China, India, Netherlands, and the United States. Finally, we use the collected data from our honeypots to automatically classify and assess attacks tailored to MikroTik devices. All our source-codes and analysis are publicly available. We believe that our honeypots and our findings in this paper foster security improvements in MikroTik devices worldwide.

Bhargavi, US., Gundibail, Shivaprasad, Manjunath, KN., Renuka, A..  2019.  Security of Medical Big Data Images using Decoy Technique. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). :310–314.

Tele-radiology is a technology that helps in bringing the communication between the radiologist, patients and healthcare units situated at distant places. This involves exchange of medical centric data. The medical data may be stored as Electronic Health Records (EHR). These EHRs contain X-Rays, CT scans, MRI reports. Hundreds of scans across multiple radiology centers lead to medical big data (MBD). Healthcare Cloud can be used to handle MBD. Since lack of security to EHRs can cause havoc in medical IT, healthcare cloud must be secure. It should ensure secure sharing and storage of EHRs. This paper proposes the application of decoy technique to provide security to EHRs. The EHRs have the risk of internal attacks and external intrusion. This work addresses and handles internal attacks. It also involves study on honey-pots and intrusion detection techniques. Further it identifies the possibility of an intrusion and alerts the administrator. Also the details of intrusions are logged.

Yasrebi, P., Monfared, S., Bannazadeh, H., Leon-Garcia, A..  2015.  Security function virtualization in software defined infrastructure. 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM). :778–781.

In this paper we present an approach to implement security as a Virtualized Network Function (VNF) that is implemented within a Software-Defined Infrastructure (SDI). We present a scalable, flexible, and seamless design for a Deep Packet Inspection (DPI) system for network intrusion detection and prevention. We discuss how our design introduces significant reductions in both capital and operational expenses (CAPEX and OPEX). As proof of concept, we describe an implementation for a modular security solution that uses the SAVI SDI testbed to first detect and then block an attack or to re-direct it to a honey-pot for further analysis. We discuss our testing methodology and provide measurement results for the test cases where an application faces various security attacks.