A Laboratory Set-Up for Cyber Attacks Simulation Using Protocol Analyzer and RTU Hardware Applying Semi-Supervised Detection Algorithm

2021 ◽  
Author(s):  
Ali Parizad ◽  
Constantine Hatziadoniu
Keyword(s):  
Detection Algorithm ◽  
Cyber Attacks ◽  
Set Up ◽  
Protocol Analyzer

scholarly journals Algorithm to Image Identification and Artix-7 FPGA Implementation for Adequate Edge Detection.

2020 ◽  
Vol 8 (5) ◽  
pp. 1656-1660
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Low Contrast ◽  
Image Identification ◽  
Canny Edge ◽  
Set Up ◽  
Canny Edge Detection Algorithm

For any image identification based applications, edge detection is the primary step. The intention of the edge detection in image processing is to minimize the information that is not required in the analysis of identification of an image. In the process of reduction of insignificant data in the image, it may lead to some loss in information which in turn raise some problems like missing of boundaries with low contrast, false edge detection and some other noise affected problems. In order to reduce the effects due to noise, a modified version of popular edge detection algorithm “Canny edge detection algorithm” is proposed. Artix 7 FPGA board set up is used to implement, by using Xilinx platform the image that is obtained as output is displayed on monitor which is connected with FPGA board using connector port DVI. MATLAB Simulink is used for algorithm simulation and then it is executed on FPGA board using Xilinx platform. The results provide good motivation to use in different edge detection applications.

scholarly journals PSO Supported Ensemble Algorithm for Bad Data Detection Against Intelligent Hacking Algorithm

2021 ◽  
Vol 9 ◽  
Author(s):  
Levent Yavuz ◽  
Ahmet Soran ◽  
Ahmet Onen ◽  
SM Muyeen
Keyword(s):  
Machine Learning ◽  
Power System ◽  
Detection Algorithm ◽  
Cyber Attacks ◽  
Data Detection ◽  
Particle Swarm Optimizer ◽  
Bad Data Detection ◽  
Detection Mechanisms ◽  
Bad Data ◽  
Advanced Computer

Power system cybersecurity has recently become important due to cyber-attacks. Due to advanced computer science and machine learning (ML) applications being used by malicious attackers, cybersecurity is becoming crucial to creating sustainable, reliable, efficient, and well-protected cyber-systems. Power system operators are needed to develop sophisticated detection mechanisms. In this study, a novel machine-learning-based detection algorithm that combines the five most popular ML algorithms with Particle Swarm Optimizer (PSO) is developed and tested by using an intelligent hacking algorithm that is specially developed to measure the effectiveness of this study. The hacking algorithm provides three different types of injections: random, continuous random, and slow injections by adaptive manner. This would make detection harder. Results shows that recall values with the proposed algorithm for each different type of attack have been increased.

scholarly journals A Real-time Anomaly-based Intrusion Detection System for Automotive Controller Area Networks

2020 ◽  
Author(s):  
Luís Felipe Prado D'Andrada ◽  
Paulo Freitas de Araujo-Filho ◽  
Divanilson Rodrigo Campelo
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
True Positive Rate ◽  
Detection Algorithm ◽  
Cyber Attacks ◽  
Area Network ◽  
Controller Area Networks ◽  
Positive Rate ◽  
Promising Solution

The Controller Area Network (CAN) is the most pervasive in-vehiclenetwork technology in cars. However, since CAN was designed with no securityconcerns, solutions to mitigate cyber attacks on CAN networks have been pro-posed. Prior works have shown that detecting anomalies in the CAN networktraffic is a promising solution for increasing vehicle security. One of the mainchallenges in preventing a malicious CAN frame transmission is to be able todetect the anomaly before the end of the frame. This paper presents a real-timeanomaly-based Intrusion Detection System (IDS) capable of meeting this dead-line by using the Isolation Forest detection algorithm implemented in a hardwaredescription language. A true positive rate higher than 99% is achieved in testscenarios. The system requires less than 1μs to evaluate a frame’s payload, thusbeing able to detect the anomaly before the end of the frame.

The Study Found that the Intelligent Mobile Phone Technology of Malicious Code

2013 ◽  
Vol 765-767 ◽  
pp. 1263-1266
Author(s):  
Ya Qin Fan ◽  
Ge Zhang ◽  
Miao Liu ◽  
Xin Zhang
Keyword(s):  
Mobile Phone ◽  
Development Trend ◽  
Detection Algorithm ◽  
Malicious Code ◽  
Propagation Model ◽  
Propagation Mechanism ◽  
Mobile Phone Technology ◽  
Detection Technology ◽  
Set Up ◽  
Regular Networks

This paper studies the development trend of intelligent mobile phone, confirmed the necessity of research on intelligent mobile phone malicious code. Study on the detection technology, proposed intelligent mobile phone regular networks and random networks based on malicious code propagation model, propagation mechanism is studied. Set up a perfect malicious code discovery and defense system model, at different levels is put forward that different, prove the necessity of scanning algorithm and Semantic Detection Algorithm for eigenvalue. To improve the security of the whole communication network.

Tracking Multiple Fishes Using Colour Changes Identification and Enhanced Object Tracking Algorithm

2013 ◽  
Vol 284-287 ◽  
pp. 1528-1532 ◽  
Author(s):  
Wong Poh Lee ◽  
Mohd Azam Osman ◽  
Abdullah Zawawi Talib ◽  
Khairun Yahya
Keyword(s):  
Detection Algorithm ◽  
Movement Speed ◽  
Prototype System ◽  
Swimming Pattern ◽  
Cultured Fish ◽  
Water Ph ◽  
Identification Technique ◽  
Colour Changes ◽  
Set Up ◽  
Fish Tank

Tracking multiple fishes using computational methods have become a research endeavor among researchers. Different concepts have been taken such as installing water sensors and video cameras to identify movement speed, colours, shapes and swimming patterns displayed by the fishes. In this research, an enhanced algorithm consisting of motion detection algorithm and condensation algorithm is proposed. This algorithm is further integrated with colour changes identification technique which considers the changes in colour on fishes. This is to identify overlapping fishes and to detect the distance between the camera and the fishes in the water. In our case study, a cultured fish tank installed with water sensors to monitor water pH, dissolved oxygen and temperature is set up together with two network cameras. Koi fishes are chosen due to their active swimming behaviour, variety of colours and easy-to-adapt habitat in the water. A real-time prototype system which models the fish swimming pattern consisting of the enhanced algorithm and the colour changes identification is developed.

Software Crucial Functions Ranking and Detection in Dynamic Execution Sequence Patterns

2020 ◽  
Vol 30 (05) ◽  
pp. 695-719
Author(s):  
Bing Zhang ◽  
Chun Shan ◽  
Munawar Hussain ◽  
Jiadong Ren ◽  
Guoyan Huang
Keyword(s):  
Detection Algorithm ◽  
Decision Function ◽  
Test Cases ◽  
Distribution Law ◽  
Execution Sequence ◽  
Novel Approach ◽  
Software Network ◽  
Set Up ◽  
Dynamic Execution ◽  
Occurrence Times

Because of the sequence and number of calls of functions, software network cannot reflect the real execution of software. Thus, to detect crucial functions (DCF) based on software network is controversial. To address this issue, from the viewpoint of software dynamic execution, a novel approach to DCF is proposed in this paper. It firstly models, the dynamic execution process as an execution sequence by taking functions as nodes and tracing the stack changes occurring. Second, an algorithm for deleting repetitive patterns is designed to simplify execution sequence and construct software sequence pattern sets. Third, the crucial function detection algorithm is presented to identify the distribution law of the numbers of patterns at different levels and rank those functions so as to generate a decision-function-ranking-list (DFRL) by occurrence times. Finally, top-k discriminative functions in DFRL are chosen as crucial functions, and similarity the index of decision function sets is set up. Comparing with the results from Degree Centrality Ranking and Betweenness Centrality Ranking approaches, our approach can increase the node coverage to 80%, which is proven to be an effective and accurate one by combining advantages of the two classic algorithms in the experiments of different test cases on four open source software. The monitoring and protection on crucial functions can help increase the efficiency of software testing, strength software reliability and reduce software costs.

scholarly journals Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 902 ◽  
Author(s):  
Aaron Martínez ◽  
Rüdiger Jahnel ◽  
Michael Buchecker ◽  
Cory Snyder ◽  
Richard Brunauer ◽  
...  
Keyword(s):  
Detection Algorithm ◽  
Simple System ◽  
Sensor Technology ◽  
Alpine Skiing ◽  
Video Recordings ◽  
Recent Developments ◽  
Set Up ◽  
Insight Into ◽  
Anterior Posterior

In order to gain insight into skiing performance, it is necessary to determine the point where each turn begins. Recent developments in sensor technology have made it possible to develop simpler automatic turn detection methodologies, however they are not feasible for regular use. The aim of this study was to develop a sensor set up and an algorithm to precisely detect turns during alpine ski, which is feasible for a daily use. An IMU was attached to the posterior upper cuff of each ski boot. Turn movements were reproduced on a ski-ergometer at different turn durations and slopes. Algorithms were developed to analyze vertical, medio-lateral, anterior-posterior axes, and resultant accelerometer and gyroscope signals. Raw signals, and signals filtered with 3, 6, 9, and 12 Hz cut-offs were used to identify turn switch points. Video recordings were assessed to establish a reference turn-switch and precision (mean bias = 5.2, LoA = 51.4 ms). Precision was adjusted based on reference and the best signals were selected. The z-axis and resultant gyroscope signals, filtered at 3Hz are the most precise signals (0.056 and 0.063 s, respectively) to automatically detect turn switches during alpine skiing using this simple system.

scholarly journals Ultra-Wideband Indoor Positioning and IMU-Based Activity Recognition for Ice Hockey Analytics

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4650
Author(s):  
Robbe Vleugels ◽  
Ben Van Herbruggen ◽  
Jaron Fontaine ◽  
Eli De Poorter
Keyword(s):  
Detection Algorithm ◽  
Ice Hockey ◽  
Ultra Wideband ◽  
Measurement Unit ◽  
Peak Detection Algorithm ◽  
Unseen Data ◽  
Wide Range ◽  
Complete Measurement ◽  
Update Rate ◽  
Set Up

Currently, gathering statistics and information for ice hockey training purposes mostly happens by hand, whereas the automated systems that do exist are expensive and difficult to set up. To remedy this, in this paper, we propose and analyse a wearable system that combines player localisation and activity classification to automatically gather information. A stick-worn inertial measurement unit was used to capture acceleration and rotation data from six ice hockey activities. A convolutional neural network was able to distinguish the six activities from an unseen player with a 76% accuracy at a sample frequency of 100 Hz. Using unseen data from players used to train the model, a 99% accuracy was reached. With a peak detection algorithm, activities could be automatically detected and extracted from a complete measurement for classification. Additionally, the feasibility of a time difference of arrival based ultra-wideband system operating at a 25 Hz update rate was determined. We concluded that the system, when the data were filtered and smoothed, provided acceptable accuracy for use in ice hockey. Combining both, it was possible to gather useful information about a wide range of interesting performance measures. This shows that our proposed system is a suitable solution for the analysis of ice hockey.

scholarly journals Detection of Suspicious Timestamps in NTFS using Volume Shadow Copies

2021 ◽  
Vol 13 (4) ◽  
pp. 62-69
Author(s):  
ALJI Mohamed ◽  
◽  
CHOUGDALI Khalid
Keyword(s):  
Operating System ◽  
Virtual Environment ◽  
File System ◽  
Detection Algorithm ◽  
Main Role ◽  
Time Analysis ◽  
Digital Forensic ◽  
Set Up ◽  
Time Information

When a computer gets involved in a crime, it is the mission of the digital forensic experts to extract the left binary artifacts on that device. Among those artifacts, there may be some volume shadow copy files left on the Windows operating system. Those files are snapshots of the volume recorded by the system in case of a needed restore to a specific past date. Before this study, we did not know if the valuable forensic information hold within those snapshot files can be exploited to locate suspicious timestamps in an NTFS formatted partition. This study provides the reader with an intersnapshot time analysis for detecting file system timestamp manipulation. In other words, we will leverage the presence of the time information within multiples volume shadow copies to detect any suspicious tampering of the file system timestamps. A detection algorithm of the suspicious timestamps is contributed. Its main role is to assist the digital investigator to spot the manipulation if it has occurred. In addition, a virtual environment has been set up to validate the use of the proposed algorithm for the detection.

scholarly journals Disclosing Cyber Attacks on Water Distribution Systems. An Experimental Approach to the Sonification of Threats and Anomalous Data

2019 ◽  
Author(s):  
Sara Lenzi ◽  
Ginevra Terenghi ◽  
Riccardo Taormina ◽  
Stefano Galelli ◽  
Paolo Ciuccarelli
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Information Overload ◽  
Water Distribution Systems ◽  
Detection Algorithm ◽  
Anomalous Behavior ◽  
Attack Detection ◽  
Cyber Attacks ◽  
Monitoring And Control ◽  
Human Operators

Water distribution systems are undergoing a process of intensive digitalization, adopting networked devices for monitoring and control. While this transition improves efficiency and reliability, these infrastructures are increasingly exposed to cyber-attacks. Cyber-attacks engender anomalous system behaviors which can be detected by data-driven algorithms monitoring sensors readings to disclose the presence of potential threats. At the same time, the use of sonification in real time process monitoring has grown in importance as a valid alternative to avoid information overload and allowing peripheral monitoring. Our project aims to design a sonification system allowing human operators to take better decisions on anomalous behavior while occupied in other (mainly visual) tasks. Using a state-of-the-art detection algorithm and data sets from the Battle of the Attack Detection Algorithms, a series of sonification prototypes were designed and tested in the real world. This paper illustrates the design process and the experimental data collected, as well results and plans for future steps.

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