Empowering Cybersecurity: A Deep Dive into AI-Driven Security Intelligence Modelling
Smart Incubator for Empowering Poultry Farmers by Maximizing Egg Hatching Success
Early Disease Detection of Black Gram Plant Leaf using Cloud Computing Based YOLO V8 Model
Data Retrieval in Cancer Documents using Various Weighting Schemes
Securing Healthcare Data in Smart Cities: A Machine Learning Approach
Gender classification has been one of the emerging issues in the field of security due to increase of women-only floors. For security purpose, this paper presents two biological features extracted from the neck region in a profile image. One is extracted the bump of the neck formed by the laryngeal prominence. Another is the width of the neck that tends to be wider in males than in females. Evaluation experiments for the proposed two features were performed on 50 male and 39 female profile images. The experimental result shows that the proposed method achieved over 95.0% accuracy for both of the male and female images, which overcomes a state-of-the-art method based on Local Binary Patterns for gender classification.
In ISs, resource objects like databases are distributed and replicated in order to increase the performance, reliability and availability. In an earlier work, we extended the earlier existing taxonomy of ISs [10]. In this paper, we have revised the taxonomy further by including WIS, SWIS and MMIS. We shall discuss various characteristics of MMIS and the effect of the network on required quality of presentation for MMIS. MMIS input strings provide an efficient means for iconic temporal/spatial relations of media streams and semantic objects. Today more information sources become available as MMISs. Hence, the development of abstract semantic models for video, audio, text, graphics and image data became very important. In this paper, we have tabulated a comparison feature study of a variety of MMISs web sites. It is found that most of the modern web sites use maximum degree of multimedia support.
Cross-Site Request Forgery (CSRF) attack occurs when a malicious web site causes a user’s web browser to perform an unwanted action on a trusted site. These attacks have been called the “sleeping giant” of web-based vulnerabilities, because many sites on the internet fail to protect against them because they have been largely ignored by the web development and security communities. The impact of a successful cross-site request forgery attack is limited to the capabilities exposed by the vulnerable application. This attack could result in a transfer of funds, changing a password, or purchasing an item in the user's context.
Depending upon who you ask, the IDS may be a simple audit trail process, or a filter process using a traffic control system, like screening routers, packet filters, firewalls, etc. Some people use IDS to mean a logging utility. This paper studies improving Internet security with Network Security combined authentication and intrusion detection (NS-IDS) secure data transmission in such MANETs. Security is deployed to work with intrusion detection systems (IDSs) to alleviate the shortcomings of uni-modal biometric systems. Since each device in the network has measurement and estimation limitations, more than one device needs to be chosen, and observations can be fused to increase observation accuracy using for the system decides whether user authentication (or IDS input) is required and which (or IDSs) should be chosen, depending on the security posture. The decisions are made Network in fully secured manner by each authentication device and IDS. Simulation results are presented to show the effectiveness of the proposed scheme.
Due to extensive growth of the Internet and increasing availability of tools and methods for intruding and attacking networks, intrusion detection has become a critical component of network security parameters. Intrusion detection in large data is one of the major challenge for the researchers in this area. Anomaly detection using data mining techniques has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks and KDDCUP’99 is the mostly widely used data set for the evaluation of these systems. In this paper we have conducted an comprehensive study and statistical analysis on KDD dataset. We also provide description of features and instances of the dataset. The another important challenge for the researchers in this area is to select an appropriate data mining tool for the analysis. The paper disusses two important and popular tools in this area, weka, Oracle data mining and tanagara. We hope that study carried out in his paper is useful for the reasearcheres in the area of intrusion detection.
World Wide Web is growing every day, people searching for a information can be easily lost in the web. People use search engine to find relevant information from the web. So it is very challenging for search engine to find relevant and quality information from the huge collection of hyperlinked data on World Wide Web. This paper gives an introduction of web search engine with its architecture. It also describes web mining techniques and page ranking algorithm in detail. Some very important page ranking algorithms like PageRank algorithm, Weighted Pagerank algorithm and Hyperlink induced topic search (HITS) algorithm are discussed and Compared on the bases of various parameters like mining techniques, input parameter, working process, complexity, limitation and search engine using algorithm.
