• International Journal of Computer Science & Network Security
• /
• v.23 no.12
• /
• pp.1-12
• /
• 2023

Ensuring the security of Supervisory Control and Data Acquisition (SCADA) and Industrial Control Systems (ICS) is paramount to safeguarding the reliability and safety of critical infrastructure. This paper addresses the significant threat posed by reconnaissance attacks on SCADA/ICS networks and presents an innovative methodology for enhancing their protection. The proposed approach strategically employs imbalance dataset handling techniques, ensemble methods, and feature engineering to enhance the resilience of SCADA/ICS systems. Experimentation and analysis demonstrate the compelling efficacy of our strategy, as evidenced by excellent model performance characterized by good precision, recall, and a commendably low false negative (FN). The practical utility of our approach is underscored through the evaluation of real-world SCADA/ICS datasets, showcasing superior performance compared to existing methods in a comparative analysis. Moreover, the integration of feature augmentation is revealed to significantly enhance detection capabilities. This research contributes to advancing the security posture of SCADA/ICS environments, addressing a critical imperative in the face of evolving cyber threats.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.5
• /
• pp.457-464
• /
• 2009

The weak classifier of AdaBoost algorithm is a central classification element that uses a single criterion separating positive and negative learning candidates. Finding the best criterion to separate two feature distributions influences learning capacity of the algorithm. A common way to classify the distributions is to use the mean value of the features. However, positive and negative distributions of Haar-like feature as an image descriptor are hard to classify by a single threshold. The poor classification ability of the single threshold also increases the number of boosting operations, and finally results in a poor classifier. This paper proposes a weak classifier that uses multiple criterions by adding a probabilistic criterion of the positive candidate distribution with the conventional mean classifier: the positive distribution has low variation and the values are closer to the mean while the negative distribution has large variation and values are widely spread. The difference in the variance for the positive and negative distributions is used as an additional criterion. In the learning procedure, we use a new classifier that provides a better classifier between them by selective switching between the mean and standard deviation. We call this new type of combined classifier the "Mixed Weak Classifier". The proposed weak classifier is more robust than the mean classifier alone and decreases the number of boosting operations to be converged.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.17 no.6
• /
• pp.546-552
• /
• 2012

This paper presents an active anti-islanding detection method using negative sequence voltage injection to the grid through a three-phase photovoltaic inverters. Because islanding operation mode can cause a variety of problems, the islanding detection of grid-connected photovoltaic inverter is the mandatory feature. The islanding mode is detected by measuring the magnitude of negative sequence impedance calculated by the negative sequence voltage and current at the point of common coupling. Simulation and experimental test are performed to verify the effectiveness of the proposed method which can detect the islanding mode in the specified time. The test has been done in accordance with the condition on IEEE Std 929-2000.

• Smart Structures and Systems
• /
• v.21 no.5
• /
• pp.653-668
• /
• 2018

This work proposes and investigates re-centering negative stiffness dampers (NSDs) for vibration suppression in high-speed trains. The merit of the negative stiffness feature is demonstrated by active controllers on a high-speed train. This merit inspires the replacement of active controllers with re-centering NSDs, which are more reliable and robust than active controllers. The proposed damper design consists of a passive magnetic negative stiffness spring and a semi-active positioning shaft for re-centering function. The former produces negative stiffness control forces, and the latter prevents the amplification of quasi-static spring deflection. Numerical investigations verify that the proposed re-centering NSD can improve ride comfort significantly without amplifying spring deflection.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.5
• /
• pp.2484-2498
• /
• 2017

Various types of social media make the people share their personal experience in different ways. In some social networking sites. Some users post their reviews, some users can support these reviews with comments, and some users just rate the reviews as kind of support or not. Unfortunately, there is rare explicit negative comments towards other reviews. This means if there is a link between two users, it must be positive link. Apparently, the negative link is invisible in these social network. Or in other word, the negative links are redundant to positive links. In this work, we first discuss the feature extraction from social media data and propose new method to compute the distance between each pair of comments or reviews on social media. Then we investigate whether we can predict negative links via regression analysis when only positive links are manifested from social media data. In particular, we provide a principled way to mathematically incorporate multi-facet data in a novel framework, Constructing Negative Links, CsNL to predict negative links for discovering the hidden information. Additionally, we investigate the ways of solution to general negative link predication problems with CsNL and its extension. Experiments are performed on real-world data and results show that negative links is predictable with multi-facet of social media data by the proposed framework CsNL. Essentially, high prediction accuracy suggests that negative links are redundant to positive links. Further experiments are performed to evaluate coefficients on different kernels. The results show that user generated content dominates the prediction performance of CsNL.

• Journal of the Korean Society of Safety
• /
• v.30 no.2
• /
• pp.70-76
• /
• 2015

This study deals with the traffic accident of circular intersections. The purpose of the study is to develop the accident models by traffic violation type. In pursuing the above, this study gives particular attention to analyzing various factors that influence traffic accident and developing such the optimal models as Poisson and Negative binomial regression models. The main results are the followings. First, 4 negative binomial models which were statistically significant were developed. This was because the over-dispersion coefficients had a value greater than 1.96. Second, the common variables in these models were not adopted. The specific variables by model were analyzed to be traffic volume, conflicting ratio, number of circulatory lane, width of circulatory lane, number of traffic island by access road, number of reduction facility, feature of central island and crosswalk.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.36 no.6
• /
• pp.418-423
• /
• 1987

In the course of the investigation to the field dependent electrical conducation mechanism in polypropylene, an abnormal conduction phenomena such as voltage controlled negative resistance charateristics has been observed at the junction of two regions charateriged by schottky effect and space charge effect respectively. This abnormal characteristics was observed initially about 110MV / m of the field strength and at 25 , however, the field strength where it observed was decreased and the apparent feature of negative charateristics was less pronounced as increasing ambient temperature. Although the observations of analogous characteristics in other materials such as polyethylene, polymethylemethactylate, and polystyrene have already been reported together with plausible explanation by Toureille and others, however, it was found that the proposed concept by those authors was little use to the present observations for quantitative discussions. Accordingly we tried to adapt another conceptual discussion based on Gibbons's formulation pertaing to the saturatio trend of the field dependent drift velocity of carriers towards the thermal velocity corresponding to the ambient temperature so that the quantitative explanatio on the observed facts has been succeeded to some estent of reasonable acceptance.

• Journal of applied mathematics & informatics
• /
• v.30 no.1_2
• /
• pp.135-145
• /
• 2012

Traditionally, ERM (Equivalent Random Method) is used to determine number of circuits in an overflow circuit group with rough traffic which has vmr(variance to mean ratio) greater than one. Recently, IPP(Interrupted Poisson Process) approximate method which represents the collective feature of the overflow has been introduced. The negative binomial loss formula can be applied to determine the required number of circuits in the overflow circuit group. In this paper, we deal with the negative binomial loss formula and determination method of number of circuits. We also analyze and compare these three loss formulas.

• Korean Journal of Remote Sensing
• /
• v.26 no.6
• /
• pp.721-730
• /
• 2010

In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. Lee (2008) proposed a feed-back system using a harmonic model of single period to adaptively reconstruct observation image series contaminated by noises resulted from mechanical problems or environmental conditions. However, the simple sinusoidal model of single period may not be appropriate for temporal physical processes of land surface. A complex model of multiple periods would be more proper to represent inter-annual and inner-annual variations of surface parameters. This study extended to use a multi-periodic harmonic model, which is expressed as the sum of a series of sine waves, for the adaptive system. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.5
• /
• pp.136-146
• /
• 2015

The active control of a vehicle based on vehicle recognition is one of key technologies for the intelligent vehicle, and the part-based image representation is necessary to recognize vehicles with only partial shapes of vehicles especially in urban scene where occlusions frequently occur. In this paper, we implemented a part-based image representation scheme using non-negative tensor factorization(NTF) and realized a robust vehicle recognition system using the NTF feature. The result shows that the proposed method gives more intuitive part-based representation and more robust recognition in urban scene.