Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/11029
Title: Secure Socket Shell Bruteforce Attack Detection with Petri Net Modeling
Authors: Tiwari, Namrata;Hubballi, Neminath;
Keywords: Feature extraction; Internet protocols; Network security; Petri nets; Attack detection; Bruteforcing; Features extraction; IP-network; Password; Petri net models; Remote users; Secure socket shell; Secure sockets; Socket; Authentication
Issue Date: 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Tiwari, N., & Hubballi, N. (2022). Secure socket shell bruteforce attack detection with petri net modeling. IEEE Transactions on Network and Service Management, , 1-1. doi:10.1109/TNSM.2022.3212591
Abstract: Secure Socket Shell exposes a secure interface for login to remote users. Password baseThis is a gentle reminder for today’s Teachers Day Celebration at Nalanda Auditorium at 04:00 PM.d authentication mechanism used by remote users is vulnerable to bruteforcing. In this attack an adversary systematically tries many passwords. These attacks can either be generated from a single source or collectively from a set of sources. In this paper we propose a method to detect such bruteforcing attacks and subsequently classify these attempts into three types as originating from single source, single domain and distributed attacks. We develop Petri-Net based model which identifies SSH connections corresponding to failed login attempts using network flow characteristics. The model also keeps track of sources of failed login attempts using which it subsequently labels a time interval as experiencing bruteforcing or not and if the interval is experiencing bruteforcing which type of attack it is. We experiment with network traffic collected from a production level server and also generated within a testbed setup and show that our model can detect attacks and also classify them. We also experiment with stealth attack variant where attacker keeps a low profile of attacks and suggest methods to handle such attack instances. IEEE
URI: https://doi.org/10.1109/TNSM.2022.3212591
https://dspace.iiti.ac.in/handle/123456789/11029
ISSN: 1932-4537
Type of Material: Journal Article
Appears in Collections:Department of Computer Science and Engineering

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