Bridge Intrusion Detection System

Question: Describe about the Bridge Intrusion Detection System? Answer: Host-based Intrusion Detection Systems Host-Based Anomaly Intrusion Detection Host-based IDS is classified within two sorts as misuse HIDS and commercial virus checking processes. The host-based anomaly includes some of the factors with networking, real-time, and computing resources (Hu 2013). The sequencing patterns are included for showing the system calls and the equivalent positions. The fundamentals of Hidden Markov Model are analyzed in this context of states and probabilities. Mimicry Attacks on Host-Based Intrusion Detection Systems The journal discusses the typical host-based IDS architecture. Then in support to one theoretical framework, the HIDS threats depicted with respect to the modeling and malicious sequences (Wagner and Soto 2014). In many cases, empirical studies show that the mimicry attacks are with shortcomings of the serial riskiness and repeated threats. The article cited some of the steady attack sequences with tools applications. Steady attacks with several system calls and their individual impact on the systems are included in tabular format in the article. Host-based Intrusion Detection and Prevention System (HIDPS) The article incorporates the IDS and prevention systems with separate types of instructions. The intrusions are identified as the attempted break-ins, masquerade attacks, and leakage of typical use in systems resources. The IDPS classification is performed for showing the types of intruders, intrusions, techniques, and detection and prevention process (Letou, Devi and Singh 2013). There were certain levels of HIDPS with several strengths and limitations in this context of the study. The advantages and disadvantages are demonstrated with signature-level, anomaly-level, and state analysis in the study. Analysis of Host-Based and Network-Based Intrusion Detection System The article discusses about the root-kit threats, misuse risks, anomaly-based problems, and architecture analysis. The host-based and network-based architecture is demonstrated with the three types of structure. The article is important about the establishment of environment with the centralized, decentralized, or hierarchical patterns (Singh and Singh 2014). The research is conducted with setting the questions along with certain constraints and topic discussion. The sniffing activity is analyzed with charts and graphs in this aspect (Modi et al. 2013). The overall study is relevant with comparison of the host and network based IDS discussion and their analysis. An Implementation of Intrusion Detection System Using Genetic Algorithm The article is on the Genetic Algorithm and its application in the HIDS implementation. The IDS implementation is incorporated with algorithm and related further works are depicted in this aspect (Hoque et al. 2012). The study is supportive with anomaly and intrusion detection system according to the networking attacks. The attacks are identified as the denial of services attack, user to root level attacks, and probing process. Knowledge-based and Behavior Intrusion Detection System A Knowledge-Based Approach to Intrusion Detection Modeling This particular article is about the intrusion detection systems analysis and architecture discussion with knowledge based implementation. The vulnerabilities stay in the situation awareness and the knowledge as in situation aware IDS architecture. The article shows the sample reasoning rules with prototype design and validation (More et al. 2012). The ontology shows how the systematic attack occurs in case of logic and input validation. The on-bound and out-bound access is shown with malicious process execution. The related works suggest that the web browsers are vulnerable with intimate attacks as unauthorized, malicious insiders and web-text situation. A Profile Based Network Intrusion Detection and Prevention System for Securing Cloud Environment This article discusses the cloud oriented aspects and the vulnerabilities incorporated with it, again, the shared access files and document needs more security for mitigating the IDS to occur (Gupta, Kumar and Abraham 2013). The present scenarios of the cloud risks are mostly showing the abstract IDS with knowledge and behavior based attacks. The identified research gaps are in this study as the existing schemes are with virtual machine profiling. The normal analysis includes the intrusion with wasting the resources with authentic virtual machines (Ou 2012). The profile based IDS is less effective than the knowledge based ones, therefore, the identified gaps are with implementation of the realistic architecture. A Survey of Intrusion Detection Techniques for Cyber-Physical Systems Cyber-Physical systems are dispersed, federated with unequal and critical with comprising actuators, sensors and networking components. The systems are with multiple controlling loops, strict timings, and predictable network traffics. The attack model for CPSs is shorted with long duration and concerned processes are propagated into the sophisticated and unique traits (Mitchell and Chen 2014). The core IDS functions comprised with collection of data with analysis. The performance metrics include the True Positive Rate, False-Positive Rate for measuring the effectiveness. CIDS: A framework for Intrusion Detection in Cloud Systems This particular journal includes the cloud computing security, related IDS application for mitigation of the risks. Therefore, the journal incorporates the idea of another new framework named as CIDS with several nodes, attack scheduler machine, and other components (Kholidy and Baiardi 2012). The CIDS deployment models are included with detection model as well with audit exchange and independent models. Unsupervised Network Intrusion Detection Systems: Detecting the Unknown without Knowledge The journal demonstrates the related research with problems and their mitigation process (Casas, Mazel and Owezarski 2012). The problems of the framework are with non-supervision and therefore the network design is related with anomaly detection and the relevant change detection process. Summary Host-based IDS is classified within two sorts as misuse HIDS and commercial virus checking processes. Some of the journal discusses the typical host-based IDS architecture comparing the network-based IDS architecture. Some researchers cited the steady attack sequences with tools applications. Steady attacks with several system calls and their individual impact on the systems are included in tabular format in the article. Analysts incorporated the IDS and prevention systems with separate types of instructions. Researchers have identified and specified about the root-kit threats, misuse risks, anomaly-based problems, and architecture analysis. The overall study is relevant with comparison of the host and network based IDS discussion and their analysis. The study is supportive with anomaly and intrusion detection system according to the networking attacks. The attacks are identified as the denial of services attack, user to root level attacks, and probing process. This particular articl e is about the intrusion detection systems analysis and architecture discussion with knowledge based implementation. The vulnerabilities stay in the situation awareness and the knowledge as in situation aware IDS architecture. The CIDS deployment models are included with detection model as well with audit exchange and independent models. References Casas, P., Mazel, J. and Owezarski, P., 2012. Unsupervised network intrusion detection systems: Detecting the unknown without knowledge.Computer Communications,35(7), pp.772-783. Gupta, S., Kumar, P. and Abraham, A., 2013. A profile based network intrusion detection and prevention system for securing cloud environment.International Journal of Distributed Sensor Networks,2013. Hoque, M.S., Mukit, M., Bikas, M. and Naser, A., 2012. An implementation of intrusion detection system using genetic algorithm.arXiv preprint arXiv:1204.1336. Hu, J., 2013. Host-Based Anomaly Intrusion Detection. [online] https://goanna.cs.rmit.edu.au. Available at: https://goanna.cs.rmit.edu.au/~jiankun/Sample_Publication/Host_Based.pdf [Accessed 26 Feb. 2016]. Kholidy, H.A. and Baiardi, F., 2012, April. CIDS: a framework for intrusion detection in cloud systems. InInformation Technology: New Generations (ITNG), 2012 Ninth International Conference on(pp. 379-385). IEEE. Letou, K., Devi, D. and Singh, Y.J., 2013. Host-based Intrusion Detection and Prevention System (HIDPS).International Journal of Computer Applications,69(26). Mitchell, R. and Chen, I.R., 2014. A survey of intrusion detection techniques for cyber-physical systems.ACM Computing Surveys (CSUR),46(4), p.55. Modi, C., Patel, D., Borisaniya, B., Patel, H., Patel, A. and Rajarajan, M., 2013. A survey of intrusion detection techniques in cloud.Journal of Network and Computer Applications,36(1), pp.42-57. More, S., Matthews, M., Joshi, A. and Finin, T., 2012, May. A knowledge-based approach to intrusion detection modeling. InSecurity and Privacy Workshops (SPW), 2012 IEEE Symposium on(pp. 75-81). IEEE. Ou, C.M., 2012. Host-based intrusion detection systems adapted from agent-based artificial immune systems.Neurocomputing,88, pp.78-86. Singh, A.P. and Singh, M.D., 2014. Analysis of Host-Based and Network-Based Intrusion Detection System.International Journal of Computer Network and Information Security,6(8), p.41. Wagner, D. and Soto, P., 2014. Mimicry Attacks on Host-Based Intrusion Detection Systems. [online] https://www.eecs.berkeley.edu. Available at: https://www.eecs.berkeley.edu/~daw/papers/mimicry.pdf [Accessed 26 Feb. 2016].