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Relevant bibliographies by topics / Intrusion Prevention System

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Academic literature on the topic 'Intrusion Prevention System'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 June 2025

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Journal articles on the topic "Intrusion Prevention System"

1

Kaur, Harpreet. "NETWORK INTRUSION DETECTION AND PREVENTION ATTACKS." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2, no. 3 (2012): 21–23. http://dx.doi.org/10.24297/ijct.v2i3a.2669.

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Intrusion detection is an important technology in business sector as well as an active area of research. It is an important tool for information security. A Network Intrusion Detection System is used to monitor networks for attacks or intrusions and report these intrusions to the administrator in order to take evasive action. Today computers are part of networked; distributed systems that may span multiple buildings sometimes located thousands of miles apart. The network of such a system is a pathway for communication between the computers in the distributed system. The network is also a pathway for intrusion. This system is designed to detect and combat some common attacks on network systems. It follows the signature based IDs methodology for ascertaining attacks. A signature based IDS will monitor packets on the network and compare them against a database of signatures or attributes from known malicious threats. In this system the attack log displays the list of attacks to the administrator for evasive action. This system works as an alert device in the event of attacks directed towards an entire network.

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Ninawe, Shreyash, Vilas Bariyekar, and Ranjita Asati. "Network Intrusion Prevention System." IJARCCE 8, no. 2 (2019): 196–99. http://dx.doi.org/10.17148/ijarcce.2019.8235.

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Farhaoui, Yousef. "Intrusion Prevention System Inspired Immune Systems." Indonesian Journal of Electrical Engineering and Computer Science 2, no. 1 (2016): 168. http://dx.doi.org/10.11591/ijeecs.v2.i1.pp168-179.

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<p>In view of new communication and information technologies that appeared with the emergence of networks and Internet, the computer security became a major challenge, and works in this research axis are increasingly numerous. Various tools and mechanisms are developed in order to guarantee a safety level up to the requirements of modern life. Among them, intrusion detection and prevention systems (IDPS) intended to locate activities or abnormal behaviors suspect to be detrimental to the correct operation of the system. The purpose of this work is the design and the realization of an IDPS inspired from natural immune systems. The study of biological systems to get inspired from them for the resolution of computer science problems is an axis of the artificial intelligence field which gave rise to robust and effective methods by their natural function, the immune systems aroused the interest of researchers in the intrusion detection field, taking into account the similarities of NIS (Natural Immune System) and IDPS objectives. Within the framework of this work, we conceived an IDPS inspired from natural immune system and implemented by using a directed approach. A platform was developed and tests were carried out in order to assess our system performances.</p>

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Stiawan, Deris, Abdul Hanan Abdullah, and Mohd Yazid Idris. "Characterizing Network Intrusion Prevention System." International Journal of Computer Applications 14, no. 1 (2011): 11–18. http://dx.doi.org/10.5120/1811-2439.

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Singh, Neha, Deepali Virmani, and Xiao-Zhi Gao. "A Fuzzy Logic-Based Method to Avert Intrusions in Wireless Sensor Networks Using WSN-DS Dataset." International Journal of Computational Intelligence and Applications 19, no. 03 (2020): 2050018. http://dx.doi.org/10.1142/s1469026820500182.

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Intrusion is one of the biggest problems in wireless sensor networks. Because of the evolution in wired and wireless mechanization, various archetypes are used for communication. But security is the major concern as networks are more prone to intrusions. An intrusion can be dealt in two ways: either by detecting an intrusion in a wireless sensor network or by preventing an intrusion in a wireless sensor network. Many researchers are working on detecting intrusions and less emphasis is given on intrusion prevention. One of the modern techniques for averting intrusions is through fuzzy logic. In this paper, we have defined a fuzzy rule-based system to avert intrusions in wireless sensor network. The proposed system works in three phases: feature extraction, membership value computation and fuzzified rule applicator. The proposed method revolves around predicting nodes in three categories as “red”, “orange” and “green”. “Red” represents that the node is malicious and prevents it from entering the network. “Orange” represents that the node “might be malicious” and marks it suspicious. “Green” represents that the node is not malicious and it is safe to enter the network. The parameters for the proposed FzMAI are packet send to base station, energy consumption, signal strength, a packet received and PDR. Evaluation results show an accuracy of 98.29% for the proposed system. A detailed comparative analysis concludes that the proposed system outperforms all the other considered fuzzy rule-based systems. The advantage of the proposed system is that it prevents a malicious node from entering the system, thus averting intrusion.

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Safana Hyder Abbas, Wedad Abdul Khuder Naser, and Amal Abbas Kadhim. "Subject review: Intrusion Detection System (IDS) and Intrusion Prevention System (IPS)." Global Journal of Engineering and Technology Advances 14, no. 2 (2023): 155–58. http://dx.doi.org/10.30574/gjeta.2023.14.2.0031.

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Intrusion detection system (IDS) is the process of monitoring the events occurring in a computer system or network and analyzing them for signs of possible incidents, which are violations or imminent threats of violation of computer security policies. An intrusion prevention system (IPS) is software that has all the capabilities of an intrusion detection system and can also attempt to stop possible incidents. If anomaly traffic pass through the network IDS would generate a false positive which means it only detects the malicious traffic, takes no action and generates only alerts but IPS detects the malicious traffic or suspicious activity, takes the actions like terminate, block or drop the connections. This paper provides an explanation of network intrusion, detection, and prevention to overcome them.

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Safana, Hyder Abbas, Abdul Khuder Naser Wedad, and Abbas Kadhim Amal. "Subject review: Intrusion Detection System (IDS) and Intrusion Prevention System (IPS)." Global Journal of Engineering and Technology Advances 14, no. 2 (2023): 155–58. https://doi.org/10.5281/zenodo.7931783.

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Intrusion detection system (IDS) is the process of monitoring the events occurring in a computer system or network and analyzing them for signs of possible incidents, which are violations or imminent threats of violation of computer security policies. An intrusion prevention system (IPS) is software that has all the capabilities of an intrusion detection system and can also attempt to stop possible incidents. If anomaly traffic pass through the network IDS would generate  a false positive which means it only detects the malicious traffic, takes no action and generates only alerts but IPS detects the malicious traffic or suspicious activity, takes the actions like terminate, block or drop the connections. This paper provides an explanation of network intrusion, detection, and prevention to overcome them.

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Sharma, Himanshu, Prabhat Kumar, and Kavita Sharma. "Recurrent Neural Network based Incremental model for Intrusion Detection System in IoT." Scalable Computing: Practice and Experience 25, no. 5 (2024): 3778–95. http://dx.doi.org/10.12694/scpe.v25i5.3004.

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The security of Internet of Things (IoT) networks has become a integral problem in view of the exponential growth of IoT devices. Intrusion detection and prevention is an approach ,used to identify, analyze, and block cyber threats to protect IoT from unauthorized access or attacks. This paper introduces an adaptive and incremental intrusion detection and prevention system based on RNNs, to the ever changing field of IoT security. IoT networks require advanced intrusion detection systems that can identify emerging threats because of their various and dynamic data sources. The complexity of IoT network data makes it difficult for traditional intrusion detection techniques to detect potential threats. Using the capabilities of RNNs, a model for creating and deploying an intrusion detection and prevention system (IDPS) is proposed in this paper. RNNs work particularly well for sequential data processing, which makes them an appropriate choice for IoT network traffic monitoring. NSL-KDD dataset is taken, pre-processed, features are extracted, and RNN-based model is built as a part of the proposed work. The experimental findings illustrate how effective the suggested approach is at identifying and blocking intrusions in Internet of Things networks. This paper not only demonstrates the effectiveness of RNNs in enhancing IoT network security but also opens avenues for further exploration in this burgeoning field. It presents a scalable, adaptive intrusion detection and prevention solution, responding to the evolving landscape of IoT security. As IoT networks continue to expand, the research enriches the discourse on developing resilient security strategies to combat emerging threats in scalable computing environments.

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Su, Thawda Win. "Survival of an Intrusion Tolerance Database System." International Journal of Trend in Scientific Research and Development 3, no. 5 (2019): 1748–51. https://doi.org/10.5281/zenodo.3591410.

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While traditional secure database systems rely on prevention control and are very limited in surviving malicious attack, an intrusion tolerant database system can operate through attacks in such a way that the system can continue delivering essential services in the face of attacks. The emphasis of survivability is on continuity of operations, with the understanding that the security precautions cannot guarantee that systems will not be penetrated and compromised. In this paper, we propose a framework of model based evaluation of the survivable intrusion tolerant database system. We focus on modeling the behaviors of an intrusion tolerant database system which can detect intrusions, isolate attacks, contain, assess, rejuvenate and repair limited in surviving malicious attacks. We contain the necessary quantitative metrics to measure the availability, integrity, and survivability. Quantitative measures are proposed to characterize the capability of a resilient database system surviving intrusions. Su Thawda Win "Survival of an Intrusion Tolerance Database System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26748.pdf

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Tasneem, Aaliya, Abhishek Kumar, and Shabnam Sharma. "Intrusion Detection Prevention System using SNORT." International Journal of Computer Applications 181, no. 32 (2018): 21–24. http://dx.doi.org/10.5120/ijca2018918280.

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Dissertations / Theses on the topic "Intrusion Prevention System"

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Tamagna-Darr, Lucas. "Evaluating the effectiveness of an intrusion prevention system-honeypot hybrid /." Online version of thesis, 2009. http://hdl.handle.net/1850/10837.

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Dubell, Michael, and David Johansson. "Nätverkssäkerhet med IPS : Förbättrad nätverkssäkerhet med Intrusion Prevention Systems." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-23347.

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Att skydda sin IT-miljö mot olika typer av intrång och attacker som till exempel trojaner,skadliga Java applets eller DoS attacker med hjälp av brandväggar och antivirusprogramär två viktiga lager i skalskyddet. I den här uppsatsen undersöks hur väl ett Intrusion Prevention System skulle kunna fungera som ett ytterligare lager i skalskyddet. Fokus ligger på hur väl IPS-systemet klarar av att avvärja attacker, hur mycket tid som går åt till konfigurering och drift för att få ett fungerande IPS samt hur prestandan i nätverket påverkas av implementationen. För att mäta hur väl IPS systemet klarar av att upptäcka och blockera attacker utförs två experiment där ett mindre nätverk attackeras på olika sätt. I det första experimentet skyddas infrastrukturen av en brandvägg och klienterna är utrustade med antivirusprogram. I det andra experimentet genomförs samma attacker igen fast med ett Snort IPS implementerat i nätverket. Resultatet av de genomförda experimenten visar att en IPS klarar att blockera ca 87% av attackerna, men nätverksprestandan påverkas negativt. Slutsatsen är att endast brandväggar och antivirusprogram inte ger ett fullgott skydd.

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Strnad, Matěj. "Návrh zabezpečení průmyslového řídícího systému." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2019. http://www.nusl.cz/ntk/nusl-399322.

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The subject of the master's thesis is a design of security measures for securing of an industrial control system. It includes an analysis of characteristics of communication environment and specifics of industrial communication systems, a comparison of available technological means and a design of a solution according to investor's requirements.

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Pagna, Disso Jules F. "A novel intrusion detection system (IDS) architecture. Attack detection based on snort for multistage attack scenarios in a multi-cores environment." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/5248.

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Recent research has indicated that although security systems are developing, illegal intrusion to computers is on the rise. The research conducted here illustrates that improving intrusion detection and prevention methods is fundamental for improving the overall security of systems. This research includes the design of a novel Intrusion Detection System (IDS) which identifies four levels of visibility of attacks. Two major areas of security concern were identified: speed and volume of attacks; and complexity of multistage attacks. Hence, the Multistage Intrusion Detection and Prevention System (MIDaPS) that is designed here is made of two fundamental elements: a multistage attack engine that heavily depends on attack trees and a Denial of Service Engine. MIDaPS were tested and found to improve current intrusion detection and processing performances. After an intensive literature review, over 25 GB of data was collected on honeynets. This was then used to analyse the complexity of attacks in a series of experiments. Statistical and analytic methods were used to design the novel MIDaPS. Key findings indicate that an attack needs to be protected at 4 different levels. Hence, MIDaPS is built with 4 levels of protection. As, recent attack vectors use legitimate actions, MIDaPS uses a novel approach of attack trees to trace the attacker¿s actions. MIDaPS was tested and results suggest an improvement to current system performance by 84% whilst detecting DDOS attacks within 10 minutes.

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Pagna, Disso Jules Ferdinand. "A novel intrusion detection system (IDS) architecture : attack detection based on snort for multistage attack scenarios in a multi-cores environment." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/5248.

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Recent research has indicated that although security systems are developing, illegal intrusion to computers is on the rise. The research conducted here illustrates that improving intrusion detection and prevention methods is fundamental for improving the overall security of systems. This research includes the design of a novel Intrusion Detection System (IDS) which identifies four levels of visibility of attacks. Two major areas of security concern were identified: speed and volume of attacks; and complexity of multistage attacks. Hence, the Multistage Intrusion Detection and Prevention System (MIDaPS) that is designed here is made of two fundamental elements: a multistage attack engine that heavily depends on attack trees and a Denial of Service Engine. MIDaPS were tested and found to improve current intrusion detection and processing performances. After an intensive literature review, over 25 GB of data was collected on honeynets. This was then used to analyse the complexity of attacks in a series of experiments. Statistical and analytic methods were used to design the novel MIDaPS. Key findings indicate that an attack needs to be protected at 4 different levels. Hence, MIDaPS is built with 4 levels of protection. As, recent attack vectors use legitimate actions, MIDaPS uses a novel approach of attack trees to trace the attacker's actions. MIDaPS was tested and results suggest an improvement to current system performance by 84% whilst detecting DDOS attacks within 10 minutes.

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Ivvala, Avinash Kiran. "Assessment of Snort Intrusion Prevention System in Virtual Environment Against DoS and DDoS Attacks : An empirical evaluation between source mode and destination mode." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-14056.

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Context. Cloud computing (CC) is developed as a Human-centered computing model to facilitate its users to access resources anywhere on the globe. The resources can be shared among any cloud user which mainly questions the security in cloud computing. There are Denial of Service and Distributed Denial of Service attacks which are generated by the attackers to challenge the security of CC. The Next-Generation Intrusion Prevention Systems (sometimes referred as Non-Traditional Intrusion Prevention Systems (NGIPS) are being used as a measure to protect users against these attacks. This research is concerned with the NGIPS techniques that are implemented in the cloud computing environment and their evaluation. Objectives. In this study, the main objective is to investigate the existing techniques of the NGIPS that can be deployed in the cloud environment and to provide an empirical comparison of source mode and destination mode in Snort IPS technique based on the metrics used for evaluation of the IPS systems. Methods. In this study, a systematic literature review is used to identify the existing NGIPS techniques. The library databases used to search the literature are Inspec, IEEE Xplore, ACM Digital Library, Wiley, Scopus and Google scholar. The articles are selected based on an inclusion and exclusion criteria. The experiment is selected as a research method for the empirical comparison of Source mode and destination mode of Snort NGIPS found through literature review. The testbed is designed and implemented with the Snort filter techniques deployed in the virtual machine. Results. Snort is one of the mostly used NGIPS against DoS and DDoS attacks in the cloud environment. Some common metrics used for evaluating the NGIPS techniques are CPU load, Memory usage, bandwidth availability, throughput, true positive rate, false positive rate, true negative rate, false negative rate, and accuracy. From the experiment, it was found that Destination mode performs better than source mode in Snort. When compared with the CPU load, Bandwidth, Latency, Memory Utilization and rate of packet loss metrics. Conclusions. It was concluded that many NGIPS of the cloud computing model are related to each other and use similar techniques to prevent the DoS and DDoS attacks. The author also concludes that using of source based and destination based intrusion detection modes in Snort has some difference in the performance measures.

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Hanna, Johan. "Åtgärder för att motverka säkerhetsbrister i katalogtjänster." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-39469.

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Katalogtjänster är och förblir en central och kritisk del i informationssystem. I katalogtjänsterna samlas stora mängder information om användare och behörigheter för respektive användare. I högriskmiljöer, där bland annat hemlig och annan skyddsvärd information samlas, är katalogtjänsterna i en utsatt situation. Om en katalogtjänst svarar fel på en resursförfrågan kan konsekvenserna vara stora. Arbetet grundade sig i att med hjälp av olika säkerhetshöjande åtgärder bygga upp ett mer robust system för att skydda katalogtjänsten mot att behörighetsprinciperna bryts och ger obehörig personal eller andra aktörer tillgång till skyddsvärda resurser. Arbetet syftade till att öka medvetenheten kring de hypotetiska sårbarheterna som finns i en katalogtjänst och baserat på detta resultera i hur de potentiella sårbarheterna i åtkomstprinciperna kan motverkas eller mildras. För att uppnå detta resonerades det fram två testfall varav ett teoretiskt. Dessa byggde på att ett Intrusion Prevention System (IPS) implementerades i ett av testfallen och en brandvägg i det andra teoretiska fallet. Båda åtgärderna implementerades i trafikflödets riktning i respektive nätverkssegment för att kontrollera användarnas behörigheter i realtid. Testfallen byggdes upp simulerat med hjälp av bland annat GNS3 och Virtualbox. Det experiment som upprättades med IPS:en som huvudkomponent gav ett positivt utfall där enheten med hjälp av en uppsättning regler kunde utläsa specifika trafikflöden till resurser som den avsedda användaren inte hade tillgång till och baserat på detta utföra olika typer av åtgärder. Experimentet med brandväggen gav däremot inte önskat resultat, detta berodde på att det inte fanns stöd för den eftersökta funktionaliteten i de brandväggar med öppen källkod som undersöktes för implementationen. Det resultat som genererades med hjälp av IPS:ens förmåga att analysera trafik i realtid och baserat på detta utföra fördefinierade åtgärder betyder att det effektivt kan byggas upp ytterligare en barriär av skydd utöver katalogtjänstens egna säkerhet. Vidare medför detta även att om en IPS implementeras krävs det att två av varandra oberoende säkerhetsåtgärder fallerar innan ett felsvar realiseras vilket är att användaren får tillgång till resursen.

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Stefanova, Zheni Svetoslavova. "Machine Learning Methods for Network Intrusion Detection and Intrusion Prevention Systems." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7367.

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Given the continuing advancement of networking applications and our increased dependence upon software-based systems, there is a pressing need to develop improved security techniques for defending modern information technology (IT) systems from malicious cyber-attacks. Indeed, anyone can be impacted by such activities, including individuals, corporations, and governments. Furthermore, the sustained expansion of the network user base and its associated set of applications is also introducing additional vulnerabilities which can lead to criminal breaches and loss of critical data. As a result, the broader cybersecurity problem area has emerged as a significant concern, with many solution strategies being proposed for both intrusion detection and prevention. Now in general, the cybersecurity dilemma can be treated as a conflict-resolution setup entailing a security system and minimum of two decision agents with competing goals (e.g., the attacker and the defender). Namely, on the one hand, the defender is focused on guaranteeing that the system operates at or above an adequate (specified) level. Conversely, the attacker is focused on trying to interrupt or corrupt the system’s operation. In light of the above, this dissertation introduces novel methodologies to build appropriate strategies for system administrators (defenders). In particular, detailed mathematical models of security systems are developed to analyze overall performance and predict the likely behavior of the key decision makers influencing the protection structure. The initial objective here is to create a reliable intrusion detection mechanism to help identify malicious attacks at a very early stage, i.e., in order to minimize potentially critical consequences and damage to system privacy and stability. Furthermore, another key objective is also to develop effective intrusion prevention (response) mechanisms. Along these lines, a machine learning based solution framework is developed consisting of two modules. Specifically, the first module prepares the system for analysis and detects whether or not there is a cyber-attack. Meanwhile, the second module analyzes the type of the breach and formulates an adequate response. Namely, a decision agent is used in the latter module to investigate the environment and make appropriate decisions in the case of uncertainty. This agent starts by conducting its analysis in a completely unknown milieu but continually learns to adjust its decision making based upon the provided feedback. The overall system is designed to operate in an automated manner without any intervention from administrators or other cybersecurity personnel. Human input is essentially only required to modify some key model (system) parameters and settings. Overall, the framework developed in this dissertation provides a solid foundation from which to develop improved threat detection and protection mechanisms for static setups, with further extensibility for handling streaming data.

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Cheng, Kah Wai. "Distributed deployment of Therminators in the network." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Dec%5FCheng%5Kah.pdf.

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Labbe, Keith G. "Evaluation of two host-based intrusion prevention systems." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Jun%5FLabbe.pdf.

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Books on the topic "Intrusion Prevention System"

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Toxen, Bob. Real-world Linux security: Intrusion, prevention, detection, and recovery. Prentice Hall, 2001.

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Peter, Mell, and National Institute of Standards and Technology (U.S.), eds. Guide to intrusion detection and prevention systems (IDPS): Recommendations of the National Institute of Standards and Technology. U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 2007.

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Saxena, Manish. Next Generation Intelligent Network Intrusion Prevention System. Lulu Press, Inc., 2017.

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Toxen, Bob. Real World Linux Security: Intrusion Prevention, Detection and Recovery. Prentice Hall PTR, 2000.

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Toxen, Bob. Real World Linux Security: Intrusion Prevention, Detection and Recovery. Prentice Hall PTR, 2000.

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Lammle, Todd, John Gay, and Alexis B. Tatistcheff. SSFIPS Securing Cisco Networks with Sourcefire Intrusion Prevention System: Exam 500-285. Wiley & Sons, Incorporated, John, 2015.

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Rajib, Nazmul. CCNP Security Cisco Secure Firewall and Intrusion Prevention System Official Cert Guide. Pearson Education, Limited, 2022.

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Rajib, Nazmul. CCNP Security Cisco Secure Firewall and Intrusion Prevention System Official Cert Guide. Pearson Education, Limited, 2022.

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Lammle, Todd, John Gay, and Alex Tatistcheff. SSFIPS Securing Cisco Networks with Sourcefire Intrusion Prevention System Study Guide: Exam 500-285. Wiley & Sons, Incorporated, John, 2015.

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Lammle, Todd, John Gay, and Alex Tatistcheff. SSFIPS Securing Cisco Networks with Sourcefire Intrusion Prevention System Study Guide: Exam 500-285. Wiley & Sons, Incorporated, John, 2015.

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Book chapters on the topic "Intrusion Prevention System"

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Wang, Zongjian, and Xiaobo Li. "Intrusion Prevention System Design." In Lecture Notes in Electrical Engineering. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4847-0_47.

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Kizza, Joseph Migga. "System Intrusion Detection and Prevention." In Guide to Computer Network Security. Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-6654-2_13.

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Kizza, Joseph Migga. "System Intrusion Detection and Prevention." In Texts in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38141-7_13.

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Kizza, Joseph Migga. "System Intrusion Detection and Prevention." In Guide to Computer Network Security. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4543-1_13.

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Kizza, Joseph Migga. "System Intrusion Detection and Prevention." In Guide to Computer Network Security. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55606-2_13.

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Jin, Hai, Zhiling Yang, Jianhua Sun, Xuping Tu, and Zongfen Han. "CIPS: Coordinated Intrusion Prevention System." In Information Networking. Convergence in Broadband and Mobile Networking. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-30582-8_10.

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Erete, Ikpeme. "Browser-Based Intrusion Prevention System." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04342-0_29.

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Kizza, Joseph Migga. "System Intrusion Detection and Prevention." In Texts in Computer Science. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-47549-8_13.

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Thoma, Jan Philipp, Florian Stolz, and Tim Güneysu. "Cips: The Cache Intrusion Prevention System." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70903-6_1.

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Ashoor, Asmaa Shaker, and Sharad Gore. "Difference between Intrusion Detection System (IDS) and Intrusion Prevention System (IPS)." In Advances in Network Security and Applications. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22540-6_48.

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Conference papers on the topic "Intrusion Prevention System"

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Shitole, Ruturaj Ramchandra, Sai Kumar Nekkanti, and Timothy Wood. "Poster: eBPF-Based Intrusion Prevention System for Database Servers." In 2024 IEEE Cloud Summit. IEEE, 2024. http://dx.doi.org/10.1109/cloud-summit61220.2024.00031.

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P, Sarumathy, Rajasree S, and Chandrasekar A. "An AI-Based Intrusion Prevention System to Enhance Cloud Security." In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE, 2025. https://doi.org/10.1109/icsadl65848.2025.10933485.

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Ramachandran, Raji, Divya Gopan, and M. S. Harsha. "Intrusion Prevention System In RDBMS." In 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT). IEEE, 2019. http://dx.doi.org/10.1109/icicict46008.2019.8993333.

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Vasudeo, Sarode Harshal, Pravin Patil, and R. Vinoth Kumar. "IMMIX-intrusion detection and prevention system." In 2015 International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM). IEEE, 2015. http://dx.doi.org/10.1109/icstm.2015.7225396.

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Mukhopadhyay, Indraneel, Kirit Sankar Gupta, Diptarshi Sen, and Piyali Gupta. "Heuristic Intrusion Detection and Prevention System." In 2015 International Conference and Workshop on Computing and Communication (IEMCON). IEEE, 2015. http://dx.doi.org/10.1109/iemcon.2015.7344479.

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Abdulrezzak, Sarah, and Firas A. Sabir. "Enhancing Intrusion Prevention in Snort System." In 2023 15th International Conference on Developments in eSystems Engineering (DeSE). IEEE, 2023. http://dx.doi.org/10.1109/dese58274.2023.10099757.

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Prasad, Romesh, and Young Moon. "Adaptive Intrusion Detection System for Cyber-Manufacturing System." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-70017.

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Abstract While Cyber-Manufacturing System security must involve three separate yet interrelated processes (prediction, detection, and prevention), the detection process is the focus of research presented in this paper. Current intrusion detection systems often result in high false positive and false negative rates. Also, the actual detection time may take long time-up to several months. The current intrusion detection systems rely heavily on the network data, but do not utilize the physical data such as side channel, sensor reading, image, keystrokes., which are generated during manufacturing processes. An adaptive intrusion detection system composed of two security layers is proposed to detect cyber-physical intrusions. Model-free deep reinforcement learning is used in the two security layers: the network layer and the physical layer. The capability of reinforcement learning through trial and error and a course of actions based on observations in an environment makes it more robust to the continuously changing attack vectors in current manufacturing industry. The proposed intrusion detection system demonstrates that it can reduce the false positive rate and generate alerts to a wide range of attack patterns.

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Lomotey, Richard K., and Ralph Deters. "Intrusion Prevention in Asterisk-Based Telephony System." In 2014 IEEE International Conference on Mobile Services (MS) . IEEE, 2014. http://dx.doi.org/10.1109/mobserv.2014.25.

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Stiawan, Deris, Abdul Hanan Abdullah, and Mohd Yazid Idris. "The trends of Intrusion Prevention System network." In 2010 2nd International Conference on Education Technology and Computer (ICETC). IEEE, 2010. http://dx.doi.org/10.1109/icetc.2010.5529697.

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Lih-Chyau Wuu, Yen-Hung Chen, Chih-Chieh Ma, and I-Tao Lung. "A practice of the intrusion prevention system." In TENCON 2007 - 2007 IEEE Region 10 Conference. IEEE, 2007. http://dx.doi.org/10.1109/tencon.2007.4428862.

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Reports on the topic "Intrusion Prevention System"

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Frish. PR-319-084511-R01 Advanced Development of Proactive Infrasonic Gas Pipeline Evaluation Network (PIGPEN). Pipeline Research Council International, Inc. (PRCI), 2014. http://dx.doi.org/10.55274/r0010816.

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A third party damage prevention warning system must have the following important attributes; the ability to accurately detect excavating activity in dense, noisy and high traffic areas, low maintenance requirements, be relatively easy to install, provide 24/7 coverage, and exhibit a low rate of false alarms. Systems that detect and quickly notify of encroachment or insufficient practices near gas pipelines would enable pipeline operators to take actions to avoid damage incidents. Early warning provides pipeline owners the ability to respond to an intrusion in time to prevent pipeline damage, and preclude incurring the additional cost and risk of repairs. The pipeline intrusion warning system being developed in this project addresses this need. Its benefits will include: 1) increased safety, 2) reduced number of third party damages to pipelines, 3) reduced system downtime and customer disruption, 4) reduced costs of damage repair, 5) improved communication between the equipment operators and the utility operators, and 6) longer life and improved integrity of the pipeline infrastructure. This report summarizes and documents a program completed by Physical Sciences Inc., Heath Consultants, American Innovations Inc. and NYSEARCH/Northeast Gas Association with co-funding from the US Department of Transportation Pipeline and Hazardous Materials Safety Administration (PHMSA) and the Pipeline Research Council International (PRCI-Year 1 only). The report is also available from DOT PHMSA Contract # DTPH56-08-T-000019

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Scarfone, K. A., and P. M. Mell. Guide to Intrusion Detection and Prevention Systems (IDPS). National Institute of Standards and Technology, 2007. http://dx.doi.org/10.6028/nist.sp.800-94.

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