Intrusion Detection And Prevention Research Articles

F-TLBO-ID: Fuzzy fed teaching learning based optimisation algorithm to predict the number of [formula omitted]-barriers for intrusion detection

Ensuring fast and efficient Intrusion Detection and Prevention (IDP) at international borders is crucial for maintaining security and safeguarding nations. In this study, we propose an innovative approach that harnesses the power of machine learning and Wireless Sensor Networks (WSNs) to achieve faster and more accurate IDP. Our novel Fuzzy fed Teaching Learning Based Optimisation regression algorithm (F-TLBO-ID) revolutionises the prediction of the required number of k-barriers for rapid IDP. To develop and validate our approach, we synthetically generated pertinent features using Monte-Carlo simulations. These features encompass essential parameters such as the concerned region’s area, effective transmission range, effective sensing range, number of sensor nodes, and the fading parameter. Training the F-TLBO-ID algorithm with these features yielded exceptional results, accurately predicting the required number of k-barriers with an impressive correlation coefficient (R = 0.99), minimal Root Mean Square Error (RMSE = 11.32), and negligible bias (−3.66). To benchmark the performance of our F-TLBO-ID algorithm, we conducted comprehensive comparisons with fine-tuned benchmark algorithms, including AutoML, GPR, GRNN, RF, RNN, SVM, and ANN. Additionally, we evaluated the algorithm against 11 different variants of nature-inspired algorithms. Remarkably, our F-TLBO-ID algorithm outperformed all these methods in terms of accuracy, firmly establishing its superiority. Finally, we validated the performance of the F-TLBO-ID algorithm using publicly available datasets. The results were highly satisfactory, exhibiting a strong correlation coefficient (R = 0.84), acceptable RMSE (36.24), and minimal bias (−7.17). This study offers a robust and reliable algorithm to predict the required barriers for fast IDP, surpassing the accuracy of existing benchmark algorithms. By implementing our proposed algorithm, the efficiency of IDP systems at international borders can be significantly improved, ultimately enhancing security and facilitating smooth border operations.

Intrusion detection and prevention of web service attacks for software as a service: Fuzzy association rules vs fuzzy associative patterns

Cloud computing inherits all the systems, networks as well asWeb Services’ security vulnerabilities, in particular for software as a service (SaaS), where business applications or services are provided over the Cloud as Web Service (WS). Hence, WS-based applications must be protected against loss of integrity, confidentiality and availability when they are deployed over to the Cloud environment. Many existing IDP systems address only attacks mostly occurring at PaaS and IaaS. In this paper, we present our fuzzy association rule-based (FAR) and fuzzy associative pattern-based (FAP) intrusion detection and prevention (IDP) systems in defending against WS attacks at the SaaS level. Our experimental results have validated the capabilities of these two IDP systems in terms of detection of known attacks and prediction of newvariant attacks with accuracy close to 100%. For each transaction transacted over the Cloud platform, detection, prevention or prediction is carried out in less than five seconds. For load and volume testing on the SaaS where the system is under stress (at a work load of 5000 concurrent users submitting normal, suspicious and malicious transactions over a time interval of 300 seconds), the FAR IDP system provides close to 95% service availability to normal transactions. Future work involves determining more quality attributes besides service availability, such as latency, throughput and accountability for a more trustworthy SaaS.

SCADA Framework Incorporating MANET and IDP for Cyber Security of Residential Microgrid Communication Network

This paper presents a reliable and secure supervisory control and data acquisition (SCADA) system equipped with advanced communication technologies (ACT) to enhance the operation and cyber security of the communication network in residential microgrid. The proposed approach uses the mobile ad hoc networks (MANET) for collecting data of power consumption from smart meters of residential areas and electric vehicles (EVs), and also for connecting mobile system operators to the network. Moreover, by understanding the dynamic nature of MANET and their exposure to cyber-attacks, we propose an intrusion detection and prevention (IDP) technology with secure knowledge algorithm and anomaly detection for preventing the black hole attacks, and other unknown attacks that result into packet dropping. Test results obtained by using Network Simulator (NS-2) demonstrate the effectiveness of the proposed IDP technology in preventing the cyber-attacks in the proposed residential microgrid communication network.

Analyzing Security and Performance Issue in Web Data Mining Technology

Since as the internet and web application emerges security is the most challenging issue which we are facing, leads possibility of being easily damaged. Currently we based application structure is designed only by considering little security but avoid Performance issue. After the detailed study of web services architecture it is analyzed that it is not suitable in counter-tracing the WS attack, an adaptive intrusion detection and prevention (ID/IP) framework to protect The WS against attacks related to WSDL/JSON/SQL is thus introduced. Through Explanation by examples, the framework Verified that by making use of agents that act as Sensors, data mining techniques such as clustering, association and sequential rule coupled with fuzzy logic to further analyze and identify anomalies, is able to exhibit the adaptive nature of capturing anomalies and avoiding false alarm. Also the log files which contain User Name, IP Address, Visiting Path, Time Stamp, Page last visited , number of Bytes Transferred, Result Status, URL which can effectively supervise the network attack. In this paper we will discuss elaborately about several security problem and performance issue related to web application and their possible solutions.

A vulnerabilities analysis and corresponding middleware security extensions for securing NGN applications

International standard bodies such as the Parlay Group, 3GPP (Third Generation Partnership Project), and ETSI TISPAN describe an applications middleware in the form of open service access (OSA)/Parlay Application Programming Interfaces and Parlay X Web Services which allow multimedia applications to be implemented on top of different fixed and mobile network types. These established middleware services are also applicable to the new IP Multimedia Subsystem (IMS) forming the heart of emerging next generation networks. The main objective of this kind of middleware services is to simplify and unify service creation and - as applications are realized in so-called application servers which can be flexibly connected to dedicated network gateways - also to expose available network capabilities to third parties. This results in an inherent increase of security threats and increases the risk of attacks on network resources. This article describes the security requirements and challenges to Web services-based NGN middleware. Based on this analysis the paper presents the middleware security mechanisms at application level providing end-to-end security based on standard such as XML Digital Signatures, XML Encryption and SAML (Security Assertion Markup Language). Furthermore, we propose additional security means in the form of intrusion detection and prevention (IDP) system protecting applications middleware against SQL injection attacks which are not mitigated by existing solutions.