scholarly journals Design and Implementation of Automated Steganography Image-Detection System for the KakaoTalk Instant Messenger

Computers ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 103
Author(s):  
Jun Park ◽  
Youngho Cho
Keyword(s):  
Detection System ◽  
Automated Detection ◽  
Automated System ◽  
Detection Methods ◽  
Image Detection ◽  
Social Network Service ◽  
Detection Algorithms ◽  
Instant Messenger ◽  
And Control ◽  
Better Than

As the popularity of social network service (SNS) messengers (such as Telegram, WeChat or KakaoTalk) grows rapidly, cyberattackers and cybercriminals start targeting them, and from various media, we can see numerous cyber incidents that have occurred in the SNS messenger platforms. Especially, according to existing studies, a novel type of botnet, which is the so-called steganography-based botnet (stego-botnet), can be constructed and implemented in SNS chat messengers. In the stego-botnet, by using various steganography techniques, every botnet communication and control (C&C) messages are secretly embedded into multimedia files (such as image or video files) frequently shared in the SNS messenger. As a result, the stego-botnet can hide its malicious messages between a bot master and bots much better than existing botnets by avoiding traditional botnet-detection methods without steganography-detection functions. Meanwhile, existing studies have focused on devising and improving steganography-detection algorithms but no studies conducted automated steganography image-detection system although there are a large amount of SNS chatrooms on the Internet and thus may exist many potential steganography images on those chatrooms which need to be inspected for security. Consequently, in this paper, we propose an automated system that detects steganography image files by collecting and inspecting all image files shared in an SNS chatroom based on open image steganography tools. In addition, we implement our proposed system based on two open steganography tools (Stegano and Cryptosteganography) in the KakaoTalk SNS messenger and show our experimental results that validate our proposed automated detection system work successfully according to our design purposes.

Self-Powered Wireless Corrosion Detection System

Aerospace ◽  
2006 ◽  
Author(s):  
Gerardo Pen˜a ◽  
Kenneth Hunziker ◽  
Christopher Davis ◽  
Matthew Malkin
Keyword(s):  
Visual Inspection ◽  
Detection System ◽  
Detection Methods ◽  
Sensing Element ◽  
Wireless Transceivers ◽  
Corrosion Detection ◽  
Control Programs ◽  
Require Power ◽  
Self Powered ◽  
And Control

Corrosion affects the maintenance of metal aircraft. Because the onset of corrosion is unpredictable, sensing corrosion is a challenge and scheduled inspections are mandated by corrosion prevention and control programs. Visual inspection is the most common method of corrosion detection. Visual inspections of aircraft structures that are difficult to access are costly and invasive. Beyond visual inspection, several non-destructive corrosion detection methods exist, such as ultrasonic scanners and pulsed eddy current systems. The functionality of these systems, however, does not minimize the invasiveness of inspections. Access to the structure under inspection is required to use these systems or to perform visual inspections. This paper describes a self-powered, wireless corrosion detection system which could enable modification of existing inspection schemes in difficult-to-access areas where corrosion is expected to develop, for example, on structure beneath an aircraft galley or lavatory. The system consists of an energy harvester, an energy storage and conditioning circuit, a corrosion sensing element, and a wireless transceiver network. Advances in energy harvesting and low-power wireless transceivers have enabled the design. The system allows users to download corrosion data from a sensor through a wireless connection, without the need for costly structural disassembly. Because the device is self-powered and wireless, it operates indefinitely without battery replacement, and does not require power or data wiring from the aircraft.

scholarly journals A Framework for Detecting Vehicle Occupancy Based on the Occupant Labeling Method

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jooyoung Lee ◽  
Jihye Byun ◽  
Jaedeok Lim ◽  
Jaeyun Lee
Keyword(s):  
Detection System ◽  
Automated Detection ◽  
Detection Accuracy ◽  
Occupancy Detection ◽  
Single Side ◽  
Binary Case ◽  
Left And Right ◽  
Hov Lanes ◽  
Labeling Method ◽  
Better Than

High-occupancy vehicle (HOV) lanes or congestion toll discount policies are in place to encourage multipassenger vehicles. However, vehicle occupancy detection, essential for implementing such policies, is based on a labor-intensive manual method. To solve this problem, several studies and some companies have tried to develop an automated detection system. Due to the difficulties of the image treatment process, those systems had limitations. This study overcomes these limits and proposes an overall framework for an algorithm that effectively detects occupants in vehicles using photographic data. Particularly, we apply a new data labeling method that enables highly accurate occupant detection even with a small amount of data. The new labeling method directly labels the number of occupants instead of performing face or human labeling. The human labeling, used in existing research, and occupant labeling, this study suggested, are compared to verify the contribution of this labeling method. As a result, the presented model’s detection accuracy is 99% for the binary case (2 or 3 occupants or not) and 91% for the counting case (the exact number of occupants), which is higher than the previously studied models’ accuracy. Basically, this system is developed for the two-sided camera, left and right, but only a single side, right, can detect the occupancy. The single side image accuracy is 99% for the binary case and 87% for the counting case. These rates of detection are also better than existing labeling.

scholarly journals Image Detection System for Schmidt Plates

1984 ◽  
Vol 78 ◽  
pp. 169-171 ◽  
Author(s):  
Hideo Maehara ◽  
Tomohiko Yamagata
Keyword(s):  
Magnetic Tape ◽  
Detection System ◽  
Automated Detection ◽  
The Other ◽  
Image Detection ◽  
Alternative Method ◽  
Intermediate Medium

A 14-inch Schmidt plate contains 109 photographic grains and 105 to 106 images of stars and galaxies on it. Such a quantity of data is too large to be handled in a conventional way even for a big computer.There is, in general, an alternative method to solve this problem; one is to store the data of all pixels on intermediate medium (e.g., magnetic tape), and reduce them into image parameters afterwards. The other method is to do all the processing simultaneously with the measurement. The latter is very useful for the automated detection of celestial images on large Schmidt plates.

scholarly journals Design of Meteorological Element Detection Platform for Atmospheric Boundary Layer Based on UAV

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yonghong Zhang ◽  
Tiantian Dong ◽  
Yunping Liu
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Detection System ◽  
Structure Design ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Meteorological Element ◽  
Local Storage ◽  
And Control

Among current detection methods of the atmospheric boundary layer, sounding balloon has disadvantages such as low recovery and low reuse rate, anemometer tower has disadvantages such as fixed location and high cost, and remote sensing detection has disadvantages such as low data accuracy. In this paper, a meteorological element sensor was carried on a six-rotor UAV platform to achieve detection of meteorological elements of the atmospheric boundary layer, and the influence of different installation positions of the meteorological element sensor on the detection accuracy of the meteorological element sensor was analyzed through many experiments. Firstly, a six-rotor UAV platform was built through mechanical structure design and control system design. Secondly, data such as temperature, relative humidity, pressure, elevation, and latitude and longitude were collected by designing a meteorological element detection system. Thirdly, data management of the collected data was conducted, including local storage and real-time display on ground host computer. Finally, combined with the comprehensive analysis of the data of automatic weather station, the validity of the data was verified. This six-rotor UAV platform carrying a meteorological element sensor can effectively realize the direct measurement of the atmospheric boundary layer and in some cases can make up for the deficiency of sounding balloon, anemometer tower, and remote sensing detection.

Road crack detection and quantification based on segmentation network using architecture of matrix

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gang Li ◽  
Yongqiang Chen ◽  
Jian Zhou ◽  
Xuan Zheng ◽  
Xue Li
Keyword(s):  
Crack Detection ◽  
Detection Method ◽  
Detection Methods ◽  
Content Type ◽  
The Road ◽  
Detection Algorithms ◽  
Model Training ◽  
Relative Errors ◽  
Detection Effect ◽  
Better Than

PurposePeriodic inspection and maintenance are essential for effective pavement preservation. Cracks not only affect the appearance of the road and reduce the levelness, but also shorten the life of road. However, traditional road crack detection methods based on manual investigations and image processing are costly, inefficiency and unreliable. The research aims to replace the traditional road crack detection method and further improve the detection effect.Design/methodology/approachIn this paper, a crack detection method based on matrix network fusing corner-based detection and segmentation network is proposed to effectively identify cracks. The method combines ResNet 152 with matrix network as the backbone network to achieve feature reuse of the crack. The crack region is identified by corners, and segmentation network is constructed to extract the crack. Finally, parameters such as the length and width of the cracks were calculated from the geometric characteristics of the cracks and the relative errors with the actual values were 4.23 and 6.98% respectively.FindingsTo improve the accuracy of crack detection, the model was optimized with the Adam algorithm and mixed with two publicly available datasets for model training and testing and compared with various methods. The results show that the detection performance of our method is better than many excellent algorithms, and the anti-interference ability is strong.Originality/valueThis paper proposed a new type of road crack detection method. The detection effect is better than a variety of detection algorithms and has strong anti-interference ability, which can completely replace traditional crack detection methods and meet engineering needs.

An Insider Threat Detection Method Based on Business Process Mining

2017 ◽  
Vol 13 (2) ◽  
pp. 83-98 ◽  
Author(s):  
Taiming Zhu ◽  
Yuanbo Guo ◽  
Ankang Ju ◽  
Jun Ma ◽  
Xuan Wang
Keyword(s):  
Business Process ◽  
Process Mining ◽  
Detection System ◽  
Detection Methods ◽  
Insider Threat ◽  
Threat Detection ◽  
Detection Algorithms ◽  
Business Cases ◽  
Business Process Mining ◽  
And Performance

Current intrusion detection systems are mostly for detecting external attacks, but the “Prism Door” and other similar events indicate that internal staff may bring greater harm to organizations in information security. Traditional insider threat detection methods only consider the audit records of personal behavior and failed to combine it with business activities, which may miss the insider threat happened during a business process. The authors consider operators' behavior and correctness and performance of the business activities, propose a business process mining based insider threat detection system. The system firstly establishes the normal profiles of business activities and the operators by mining the business log, and then detects specific anomalies by comparing the content of real-time log with the corresponding normal profile in order to find out the insiders and the threats they have brought. The relating anomalies are defined and the corresponding detection algorithms are presented. The authors have performed experimentation using the ProM framework and Java programming, with five synthetic business cases, and found that the system can effectively identify anomalies of both operators and business activities that may be indicative of potential insider threat.

Research on the Roller Intelligent Detection System Based on LabVIEW

2013 ◽  
Vol 438-439 ◽  
pp. 1084-1088
Author(s):  
Ummin Okumura ◽  
Yu Jie Qi ◽  
Yun Long ◽  
Tian Hang Zhang
Keyword(s):  
Nondestructive Testing ◽  
Real Time ◽  
Detection System ◽  
Detection Methods ◽  
Intelligent Detection ◽  
Speed Up ◽  
Compaction Control ◽  
And Control ◽  
Compaction Degree

Based on the platform of LabVIEW, a set of roller intelligent detecting system is developed. With this system, it is easy to realize functions of fast nondestructive testing of subgrade compaction degree, roller speed, rollers compaction trajectory, compaction times, GPS real-time positioning as well as saving and printing report forms. Compared with traditional detection methods, this detecting system can test and control on-site compaction quality much more easily, in order to speed up the construction progress, improve the quality of subgrade compaction, control and manage compaction work better.

scholarly journals On-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques

2008 ◽  
Vol 12 (2) ◽  
pp. 111-115
Author(s):  
Chrissanthi Angeli ◽  
◽  
Avraam Chatzinikolaou ◽  
Keyword(s):  
Fault Detection ◽  
Detection System ◽  
Detection Methods ◽  
Time Data ◽  
Actual System ◽  
Incipient Faults ◽  
On Line ◽  
Modelling Techniques ◽  
Drive And Control ◽  
And Control

The development of on-line fault detection methods for drive and control systems is of main importance for the modern production technology. Modelling information improves the reliability of the diagnostic method when it is involved in a fault detection system. In this paper, the use of modelling information for the fault detection of hydraulic driven machines as well as for the compensation of incipient faults is presented. For this purpose a suitable implementation environment was developed that allows the on line interaction of real time data and simulation results and makes possible their direct effect to the actual system.

scholarly journals A Combined Anomaly and Trend Detection System for Industrial Robot Gear Condition Monitoring

2021 ◽  
Vol 11 (21) ◽  
pp. 10403
Author(s):  
Corbinian Nentwich ◽  
Gunther Reinhart
Keyword(s):  
Anomaly Detection ◽  
Condition Monitoring ◽  
Production Systems ◽  
Detection System ◽  
Industrial Robot ◽  
Health Indicators ◽  
Automated System ◽  
Trend Detection ◽  
Detection Methods ◽  
Application Data

Conditions monitoring of industrial robot gears has the potential to increase the productivity of highly automated production systems. The huge amount of health indicators needed to monitor multiple gears of multiple robots requires an automated system for anomaly and trend detection. In this publication, such a system is presented and suitable anomaly detection and trend detection methods for the system are selected based on synthetic and real world industrial application data. A statistical test, namely the Cox-Stuart test, appears to be the most suitable approach for trend detection and the local outlier factor algorithm or the long short-term neural network performs best for anomaly detection in the application of industrial robot gear condition monitoring in the presented experiments.

scholarly journals Optimum design of a microstrip ring resonator sensor to determine the moisture content in oil palm fruits and seeds

BioResources ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. 1819-1837
Author(s):  
Ahmad Fahad Ahmad ◽  
Zulkifly Abbas ◽  
Hameda Ali Abrass ◽  
Kok Yeow You
Keyword(s):  
Moisture Content ◽  
Oil Palm ◽  
Ring Resonator ◽  
Detection System ◽  
Automated Detection ◽  
Detection Methods ◽  
Fresh Fruit Bunch ◽  
Palm Fruit ◽  
Microstrip Ring ◽  
Microstrip Ring Resonator

Oil palm fresh fruit bunch (OPFFB) is the main export product of the oil palm industry. A good oil palm is between 17 to 18 weeks of age with full fruitless maturity. An automated detection system should be implemented to determine the OPFFB’s maturity and expedite the harvesting process. Various automated detection methods have been proposed for conventional method replacement. In a preliminary study, a new oil palm fruit sensor was proposed for detecting the maturity of OPFFB, and a microstrip ring resonator was designed for determining the moisture content in oil palm fruit. The coaxial feeder of the microstrip ring was a Sub-Miniature A (SMA) stub contact panel with outer and inner conductors of 4.1 mm and 1.3 mm, respectively. The measurement system consisted of a sensor and a PC controlled network analyzer. This system was tested successfully on seeds and fruits of oil palm with various degrees of maturity. The microstrip ring resonator operated between 2.2 and 3 GHz and required low frequency that enabled the electromagnetic field in the first half of the ring resonator to be transferred to the second half and subsequently cause the collinearity of the maximum field points in the feed lines and resonator.

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