Testing and Comparing Result Scanning Using Web Vulnerability Scanner

2015 ◽  
Vol 21 (11) ◽  
pp. 3458-3462 ◽  
Author(s):  
Albert Sagala ◽  
Elni Manurung
Keyword(s):  
Vulnerability Scanner

MoScan: a model-based vulnerability scanner for web single sign-on services

2021 ◽  
Author(s):  
Hanlin Wei ◽  
Behnaz Hassanshahi ◽  
Guangdong Bai ◽  
Padmanabhan Krishnan ◽  
Kostyantyn Vorobyov
Keyword(s):  
Single Sign On ◽  
Model Based ◽  
Vulnerability Scanner

AUTOMATED VULNERABILITY SEARCH IN A WEB APPLICATION BASED ON REINFORCEMENT LEARNING

2021 ◽  
Vol 53 (1) ◽  
pp. 91-97
Author(s):  
OLGA N. VYBORNOVA ◽  
◽  
ALEKSANDER N. RYZHIKOV ◽  
Keyword(s):  
Reinforcement Learning ◽  
Web Application ◽  
Web Applications ◽  
Subject Area ◽  
Learning Technology ◽  
Web Application Security ◽  
Vulnerability Scanner ◽  
Learning Agent ◽  
Markov Decision ◽  
Python Programming

We analyzed the urgency of the task of creating a more efficient (compared to analogues) means of automated vulnerability search based on modern technologies. We have shown the similarity of the vulnerabilities identifying process with the Markov decision-making process and justified the feasibility of using reinforcement learning technology for solving this problem. Since the analysis of the web application security is currently the highest priority and in demand, within the framework of this work, the application of the mathematical apparatus of reinforcement learning with to this subject area is considered. The mathematical model is presented, the specifics of the training and testing processes for the problem of automated vulnerability search in web applications are described. Based on an analysis of the OWASP Testing Guide, an action space and a set of environment states are identified. The characteristics of the software implementation of the proposed model are described: Q-learning is implemented in the Python programming language; a neural network was created to implement the learning policy using the tensorflow library. We demonstrated the results of the Reinforcement Learning agent on a real web application, as well as their comparison with the report of the Acunetix Vulnerability Scanner. The findings indicate that the proposed solution is promising.

scholarly journals A Study on Cyber Security Threats in a Shipboard Integrated Navigational System

2019 ◽  
Vol 7 (10) ◽  
pp. 364 ◽  
Author(s):  
Svilicic ◽  
Rudan ◽  
Jugović ◽  
Zec
Keyword(s):  
Cyber Security ◽  
Route Planning ◽  
Regulatory Compliance ◽  
Security Testing ◽  
Vulnerability Scanner ◽  
Radar Systems ◽  
Electronic Chart ◽  
Planning Status ◽  
Navigational System ◽  
Route Monitoring

The integrated navigational system (INS) enhances the effectiveness and safety of ship navigation by providing multifunctional display on the basis of integration of at least two navigational functions, the voyage route monitoring with Electronic Chart Display and Information System (ECDIS) and collision avoidance with radar. The INS is essentially a software platform for fusion of data from the major ECDIS and radar systems with sensors for the additional navigation functions of route planning, status and data display, and alert management. This paper presents a study on cyber security resilience examination of a shipboard INS installed on a RoPax ship engaged in international trade. The study was based on a mixed-method approach, combining an interview of the ship's navigational ranks and cyber security testing of the INS using an industry vulnerability scanner. The identified threats were analyzed qualitatively to study the source of cyber risks threatening the INS. The results obtained point out cyber threats related to weaknesses of the INS underlying operating system, suggesting a need for occasional preventive maintenance in addition to the regulatory compliance required.

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