Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
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Detection of Metasploit Attacks Using RAM Forensic on Proprietary Operating Systems
Get PDFInformation technology has become an essential thing in the digital era as it is today. With the support of computer networks, information technology is used as a medium for exchanging data and information. Much information is confidential. Therefore, security is also essential. Metasploit is one of the frameworks commonly used by penetration testers to audit or test the security of a computer system legally, but it does not rule out the possibility that Metasploit can also be used for crime. For this reason, it is necessary to carry out a digital forensic process to uncover these crimes. In this study, a simulation of attacks on Windows 10 will be carried out with Metasploit. Then the digital forensics process uses live forensics techniques on computer RAM, where the computer RAM contains information about the processes running on the computer. The live forensic technique is important because information on RAM will be lost if the computer is off. This research will use FTK Imager, Dumpit, and Magnet RAM Capture as the RAM acquisition tool and Volatility as the analysis tool. The results of the research have successfully shown that the live forensics technique in RAM is able to obtain digital evidence in the form of an attacker's IP, evidence of exploits/Trojans, processes running on RAM, operating system profiles used and the location of the exploits/Trojan when executed by the victim
Performance Comparisson Human Activity Recognition Using Simple Linear Method
Get PDFHuman activity recognition (HAR) with daily activities have become leading problems in human physical analysis. HAR with wide application in several areas of human physical analysis were increased along with several machine learning methods. This topic such as fall detection, medical rehabilitation or other smart appliance in physical analysis application has increase degree of life. Smart wearable devices with inertial sensor accelerometer and gyroscope were popular sensor for physical analysis. The previous research used this sensor with a various position in the human body part. Activities can classify in three class, static activity (SA), transition activity (TA), and dynamic activity (DA). Activity from complexity in activities can be separated in low and high complexity based on daily activity. Daily activity pattern has the same shape and patterns with gathering sensor. Dataset used in this paper have acquired from 30 volunteers. Seven basic machine learning algorithm Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosted and K-Nearest Neighbor. Confusion activities were solved with a simple linear method. The purposed method Logistic Regression achieves 98% accuracy same as SVM with linear kernel, with same result hyperparameter tuning for both methods have the same accuracy. LR and SVC its better used in SA and DA without TA in each recognizing
Low-cost and Efficient Fault Detection and Protection System for Distribution Transformer
Get PDFDistribution transformers are a vital component of electrical power transmission and distribution system. Frequent Monitoring transformers faults before it occurs can help prevent transformer faults which are expensive to repair and result in a loss of energy and services. The present method of the routine manual check of transformer parameters by the electricity board has proven to be less effective. This research aims to develop a low-cost protection system for the distribution transformer making it safer with improved reliability of service to the users. Therefore, this research work investigated transformer fault types and developed a microcontroller-based system for transformer fault detection and protection system using GSM (the Global System of Mobile Communication) technology for fault reporting. The developed prototype system was tested using voltage, current and temperature, which gave a threshold voltage higher than 220 volts to be overvoltage, a load higher than 200 watts to be overload and temperature greater than 39 degrees Celsius to be over temperature was measured. From the results, there was timely detection of transformer faults of the system, the transformer protection circuits were fully functional, and fault reporting was achieved using the GSM device. Overall, 99% accuracy was achieved. The system can thus be recommended for use by the Electricity Distribution Companies to protect distribution transformers for optimal performance, as the developed system makes the transformers more robust, and intelligent. Hence, a real-time distribution transformer fault monitoring and prevention system is achieved and the cost of transformer maintenance is reduced to an extent
SDN-Honeypot Integration for DDoS Detection Scheme Using Entropy
Get PDFLimitations on traditional networks contributed to the development of a new paradigm called Software Defined Network (SDN). The separation of control and data plane provides an advantage as well as a security gap on the SDN network because all controls are centralized on the controller so when the compilation of attacks are directed the controller, the controller will be overburdened and eventually dropped. One of the attacks that can be used is the DDoS attack - ICMP Flood. ICMP Flood is an attack intended to overwhelm the target with a large number of ICMP requests. To overcome this problem, this paper proposes detection and mitigation using the Modern Honey Network (MHN) integration in SDN and then makes reactive applications outside the controller using the entropy method. Entropy is a statistical method used to calculate the randomness level of an incoming packet and use header information as a reference for its calculation. In this study, the variables used are the source of IP, the destination of IP and protocol. The results show that detection and mitigation were successfully carried out with an average value of entropy around 10.830. Moreover, CPU usage either in normal packet delivery or attacks showed insignificant impact from the use of entropy. In addition, it can be concluded that the best data collected in 30 seconds in term of the promptness of mitigation flow installation
Image Retrieval Based on Texton Frequency-Inverse Image Frequency
Get PDFIn image retrieval, the user hopes to find the desired image by entering another image as a query. In this paper, the approach used to find similarities between images is feature weighting, where between one feature with another feature has a different weight. Likewise, the same features in different images may have different weights. This approach is similar to the term weighting model that usually implemented in document retrieval, where the system will search for keywords from each document and then give different weights to each keyword. In this research, the method of weighting the TF-IIF (Texton Frequency-Inverse Image Frequency) method proposed, this method will extract critical features in an image based on the frequency of the appearance of texton in an image, and the appearance of the texton in another image. That is, the more often a texton appears in an image, and the less texton appears in another image, the higher the weight. The results obtained indicate that the proposed method can increase the value of precision by 7% compared to the previous method
Prediction of Biochemical Oxygen Demand Using Radial Basis Function Network
Get PDFBiochemical oxygen demand shows the amount of oxygen needed by microorganisms to decompose dissolved organic substances suspended in water. This variable determines water quality. The higher value indicates lower water quality. Obtaining this value requires a lengthy procedure of five days in typical laboratories. This paper proposes to predict biochemical oxygen demand using a radial basis function network with improvement relational fuzzy c-means clustering to set centroid by using 11 parameters that come from water quality records. The dataset used in testing consisting of weekly parameters between 2014-2019. Testing results show performance measurement of mean absolute error, mean square error, root mean square error, mean absolute percentage error, and accuracy using centroid with improvement relational fuzzy c-means 0.15016, 0.3677, 0.19082, 21.64490 and 78.35510 comparing with centroid from fuzzy c-means 0.16002, 0.04021, 0.19963, 22.83184, and 77.16816
ANP and ELECTRE Methods for Determine New Student Admissions
Get PDFHigher Education is a level of education after High School which selects new students based on achievement, report cards, and tests. Admission selection was based on report cards. Number of indicators and who register make it difficult for determine which students are accepted in education. Multi criteria Group Decision Making (MCGDM) is decision-making method to determine best alternative from a number of alternatives based on certain criteria. In this study, MCGDM used is Analytic Network Process (ANP) and Elimination and Choice Expression Reality (ELECTRE). ANP model is a development of AHP and requires linkages between criteria using a network. ELECTRE is method based concept of ranking through pairwise comparisons between alternatives on the appropriate criteria. Contribution is integration ANP and ELECTRE methods based on group, by determining decisions based on consistency ratio. The results of testing level consistency ratio, group-based ANP-ELECTRE can be applied to assessment selection at Electrical Engineering with highest accuracy of 86.36%
Reduced Overshoot of The Electroforming Jewellery Process Using PID
Get PDFThe electroforming jewellery is the electrodeposition process of coating metal on an insulator object to make a jewellery product. The problems are burnt and uneven results in their products, it happened because electrical currents while the process increased. So, too many metal particles attached to object. The problems of electroforming process can fix with a control system, where controller must makes constant electrical currents while the process. In this paper, the problems was changed to the equation by the polynomial regression method as a plant. Secondly the characteristic of current sensor was found by the linier regression method as a feedback system. The system used buck converter as the actuator, where it was written to the equation by the state space method. The controller was chosen by comparison 4 types controller, they are a conventional controller, proportional controller, proportional – integral (PI) controller, and proportional – integral – derivative (PID) controller. Xcos Scilab used to simulated the system and got the system with a proportional – integral – derivative controller is the best controller. The system with a proportional – integral – derivative controller have a Rise time 1.3687 Seconds and Overshoot 2.5420%. The result of research will be base to makes hardware system where it will help the advancement of the creative economy industry in Malang City