Evaluating Hybrid Model Performance in Predicting the Impact of Lockdown on Controlling Covid-19 Cases Progression in Middle Income Settings
A Method for the Identification of Denial of Service (DoS) Attack in Network Traffic using Machine Learning Techniques
Agriculture Management System
Unveiling Sentiment Analysis: A Comparative Study of LSTM and Logistic Regression Models with XAI Insights
Resume Screener System
Efficient Agent Based Priority Scheduling and LoadBalancing Using Fuzzy Logic in Grid Computing
A Survey of Various Task Scheduling Algorithms In Cloud Computing
Integrated Atlas Based Localisation Features in Lungs Images
A Computational Intelligence Technique for Effective Medical Diagnosis Using Decision Tree Algorithm
A Viable Solution to Prevent SQL Injection Attack Using SQL Injection
A Web Information System (WIS) that spans across more than one industrial sector not only can offer a greater wealth of information, but also can allow incorporation of more innovative features. For instance, a WIS may offer a wide range of services to scholars by assisting them with details concerning books and their publishers. Central to this is the need for web aggregation capability to be incorporated in such a WIS. This would rely on the use of sound web data extraction tool as the basic underlying technology. In this paper, the authors present the various publication web portals on a comparison perspective.
In this paper, the authors wish to report some further computational results related to two algorithms proposed earlier for the multi-processor job scheduling problem. Here, they have compared the performance of an FCFS-based algorithm for multi-processor scheduling with a greedy-based algorithm known as Decreasing-Ascend algorithm. They have considered the random nature of job completion times, to get a deeper insight into the performance of the algorithms. More than 20,000 data sets were created with varying combinations of jobs with shorter job lengths and longer job lengths. They keep the total execution time (sum of individual job durations) as fixed for all the instances considered and have showed that even if we consider this random situation, the performance level of the algorithms reported earlier is still applicable.
The huge development of computer science, escorted by another vast development in the hiding techniques, has created great possibilities, in which it is difficult to break traditional techniques. Those techniques were classified depending on the method of embedding like inserting, replacing or exchanging the positions. In this paper, a data (video) hiding scheme by simple LSB substitution is proposed so as to hide complete secret video inside cover video. Both secret video and cover video is segmented into frames, which is a three dimensional image of RGB (Red-Green-Blue) type and each frame of secret video is embedded with each frame of cover video, resulting in complete secret video hiding (Stego-Video). The proposed algorithm followed in this research paper led to get a video segment in which it is difficult to find the embedded video within.
Intrusion Detection system has become the main research focus in the area of information security. Last few years have witnessed a large variety of technique and model to provide increasingly efficient intrusion detection solutions. Traditional Network IDS are limited and do not provide a comprehensive solution for these serious problems which are causing many types of security breaches and IT service impacts. They search for potential malicious abnormal activities on the network traffics; and sometimes succeed to find true network attacks and anomalies (true positive). However, in many cases, systems fail to detect malicious network behaviors (false negative) or they fire alarms when there is nothing wrong in the network (false positive). In accumulation, they also require extensive and meticulous manual processing and interference. The authors advocate here applying Data Mining (DM) techniques on the network traffic data is a potential solution that helps in design and development of a better efficient intrusion detection system. Data mining methods have been used to build the automatic intrusion detection systems. The central idea is to utilize auditing programs to extract the set of features that describe each network connection or session, and apply data mining programs, to learn that capture intrusive and non-intrusive behavior. In this research paper, the authors are focusing on Data Mining based intrusion detection system.
The RSA system is widely employed in networking applications for good performance and high security. It supports the multiple key sizes like 128 bits, 256 bits, 512 bits. In this paper, The authors use Verilog code to implement a 16-bit RSA block cipher system. Therefore it can easily be fit into the different systems requiring different levels of security. The whole implementation includes three parts: key generation, encryption and decryption process. The key generation stage aims to generate a pair of public key and private key, and then the private key will be distributed to receiver according to certain key distribution schemes. The memory usage and overhead associated with the key generation is eliminated by the proposed system model. The cipher text can be decrypted at receiver side by RSA secret key. Verilog code is synthesized and simulated using Xilinx-ISE 12.1. It is verified that this architecture supports for multiple key of 128bits, 256bits, and 512 bits. Net list generated from RTL Compiler will be used to generate the IC layout. In this work, they have also developed an algorithm using LabVIEW 2010. LabVIEW (Laboratory Virtual Instrument Engineering Workbench) is a graphical programming language that uses icons instead of lines of text to create programs. Unlike text based programming language, LabVIEW uses the data flow programming, where the flow of data determines the execution. The flexibility, modular nature and ease to use programming is possible with LabVIEW, making it less complex.
Extensible Markup Language (XML) has become a de facto standard for storing, sharing and exchanging information across heterogeneous platforms. The XML content is growing day-by-day in rapid pace. Enterprises need to make queries on XML databases frequently. As huge XML data is available, it is a challenging task to extract required data from the XML database. It is computationally expensive to answer queries without any support. In this paper, the authors have presented a technique known as Tree-based Association Rules (TARs) mined rules that provide required information on structure and content of XML file and the TARs are also stored in XML format. The mined knowledge (TARs) is used later for XML query answering support. This enables quick and accurate answering. Distributed query processing is used to relate two or more databases using sedna tool. To search information from xml document, an algorithm called path-join algorithm is used. They also developed a prototype application to demonstrate the efficiency of the proposed system. The empirical results are very positive and query answering is expected to be useful in real time applications.
