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International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT)

作者： Samrin, Rafath Vasumathi, D. ISL Engn Coll Comp Sci & Engn Hyderabad Andhra Pradesh India JNTUH Comp Sci & Engn Hyderabad Andhra Pradesh India

ISBN: (纸本)9781538623619

In computer system and network, intrusion detection is an important research area. A lot of mechanisms are available for detect the network intrusion, but that is not able to identify the new kind of attacks. Various techniques have already been implemented for finding and categorizing intrusions. The intrusion detection system (IDS) is two types, namely network based IDS and Host IDS (HIDS). The manual classification of network data inspection is time consuming task, expensive as well as repetitive job. IDS mechanism is very helpful to find the network attacks and anomalies. In IDS, data mining methods is broadly used for extracting useful information from the massive amount dataset. This paper presents the investigation of different techniques and intrusion classification on KDD Cup 99 dataset. So, by classifying the different network issues a new and effective technique is implemented which can categorize and identify intrusions in the KDD Cup 99 dataset.

关键词： Anomaly detection Classification Clustering intrusion detection system network based intrusion detection system Signature based detection

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Bayesian Classifier and Snort based network intrusion detection system in Cloud Computing

Bayesian Classifier and Snort based Network Intrusion Detect...

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3rd International Conference on Computing Communication and networking Technologies (ICCCNT)

作者： Modi, Chirag N. Patel, Dhiren R. Patel, Avi Muttukrishnan, Rajarajan NIT Surat Surat Gujarat India City Univ London London England

ISBN: (纸本)9781467356930

One of the major security issues in cloud computing is to protect against network intrusions that affect confidentiality, availability and integrity of Cloud resources and offered services. To address this issue, we design and integrate Bayesian Classifier and Snort based network intrusion detection system (NIDS) in Cloud. This framework aims to detect network intrusions in Cloud environment with low false positives and affordable computational cost. To ensure feasibility of our NIDS module in Cloud, we evaluate performance and quality results on KDD'99 experimental dataset.

关键词： Cloud computing network based intrusion detection system Bayesian classifier Snort

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Integrating Signature Apriori based network intrusion detection system (NIDS) in Cloud Computing

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Procedia Technology 2012年 6卷 905-912页

作者： Chirag N. Modi Dhiren R. Patel Avi Patel Muttukrishnan Rajarajan NIT Surat INDIA City University London UK

One of the major security issues in Cloud computing is to detect malicious activities at the network layer. In this paper, we propose a framework integrating network intrusion detection system (NIDS) in the Cloud. Our NIDS module consists of Snort and signature apriori algorithm. It generates new rules from captured packets. These new rules are appended in the Snort configuration file to improve efficiency of Snort. It aims to detect known attacks and derivative of known attacks in Cloud by monitoring network traffic, while ensuring low false positive rate with reasonable computational cost. We also recommend the positioning of NIDS in Cloud. We present experimental setup and discuss the design goals expected from proposed framework.

关键词： Cloud computing network based intrusion detection system Snort Signature apriori algorithm

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Signature based Semantic intrusion detection system on Cloud 2

Signature Based Semantic Intrusion Detection System on Cloud

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2nd International Conference on Information systems Design and Intelligent Applications (INDIA)

作者： Sangeetha, S. Devi, B. Gayathri Ramya, R. Dharani, M. K. Sathya, P. Avinashilingam Univ Fac Engn Dept Comp Sci & Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9788132222507;9788132222491

Now a days, many enterprise applications are using cloud platform. Security is the most sensitive issue in cloud platform. intrusion detection system is used to protect the Virtual machine from threats. This paper proposes Application level Signature based Semantic intrusion detection system, which concentrates on the application level to detect application specific attacks. A packet sniffer is placed between cloud user and Virtual cloud provider. The packets of various protocols are captured by packet sniffer and dispatch it to its corresponding parser. The parser translates a sequence of packets into protocol messages and dispatches the packet to the corresponding state machine which consists of message parsing grammar. The message parsing grammar analyses the messages and checks with the semantic rules. If any signature does not matches with the rule-base and found to be malicious. The IDS interpreter generates alert to the cloud provider. The Signature based semantic intrusion detection system reduces the false alarm rate. So, the accuracy of the detection rate gets increased.

关键词： Signature based detection network based intrusion detection system HTTP FTP HTML attacks

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An efficacious intellectual framework for host based intrusion detection system 2nd

An efficacious intellectual framework for host based intrusi...

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2nd International Conference on Recent Trends in Advanced Computing, Disruptive Innovation (ICRTAC-DTI)

作者： Selvamani, D. Selvi, V Sivet Coll Chennai 600073 Tamil Nadu India Mother Teresa Womens Univ Kodaikanal 624101 India

intrusion detection systems (IDS) are indispensible for all types of networks to protect them from the intruders. The IDS have to process millions of network packets with many features, which delay the detection of anomalies. To understand the attacks of the past and to design proper tools to defeat their impending peril, Host based IDS or HIDS, establishes to be a robust design. An Efficacious Intellectual Framework for Host based intrusion detection with Rule Structure Generation and Pattern Matching algorithm sets the rule structure for the unknown attack generated by using Association Rule Mining in the Map Reduce Framework. It is accomplished in two stages. In the first stage, an efficacious Rule structure is generated using Intellectual method. In the second stage, Brute Force algorithm pattern matching algorithm is utilized in the proposed framework. It is proper to audit and review logs for malicious activity. Notably intrusions are rare after proven analysis to prevent the attacks to happen. The present HIDS establishes to be a robust design for understanding of attacks of the past and determining effective methods to defeat their future threats. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： Data Mining MapReduce network based intrusion detection system Association Rule Mining Brute Force algorithm

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Machine Learning-based intrusion detection system using Wireless Sensor networks 4

Machine Learning-based Intrusion Detection System using Wire...

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4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Pande, Priyanka Mathur, Harsh Gupta, Lalit Kumar Rabindranath Tagore University Department of Computer Science and Engineering M.P. Bhopal464993 India Bundelkhand University Department of Computer Science and Engineering Uttar Pradesh Jhansi284128 India

ISBN: (纸本)9798350343670

Cybersecurity has grown to be a top priority for both businesses and people in today's networked and digitally driven society. It is essential to put in place efficient security measures to protect sensitive data and important systems from hostile breaches given the constantly changing environment of cyber threats. The intrusion detection system (IDS) is one of these crucial cybersecurity tools. The essential ideas, categorizations, and detection techniques of intrusion detection systems are explored in detail in this work. The paper examines the network-based intrusion detection system (NIDS) and the Host-based intrusion detection system (HIDS), which are the two main types of IDS. It talks about their unique features and how they work together to provide a strong defence against online dangers. The IDS works by continually watching network traffic or the activity of specific hosts, analysing trends, and spotting unusual or suspicious activity. The study emphasises the significance of anomaly-based and signature-based detection methods while highlighting the advantages and disadvantages of each. In addition, the possibility for behaviour-based detection algorithms to discover hazards that were not recognised before is investigated. The article emphasises the need to incorporate IDS within a more comprehensive cybersecurity plan, even if it is a useful tool for spotting possible security breaches. Working together with an IPS strengthens the entire security posture by ensuring that threats are not only identified but also mitigated or stopped in real-time. This study emphasises the need of timely updates, appropriate setup, and continuous monitoring to preserve IDS's effectiveness against developing threats via a thorough examination of IDS. It also describes recommended practises to improve the effectiveness and dependability of IDS installations, highlighting the need of qualified security analysts to properly analyse and react to alarms. An intrusion detection sy

关键词： cybersecurity intrusion detection system intrusion Prevention system Machine learning network based intrusion detection system

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STROP: Static Approach for detection of Return-Oriented Programming Attack in network

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IEICE TRANSACTIONS ON COMMUNICATIONS 2015年第1期E98B卷 242-251页

作者： Choi, YoungHan Lee, DongHoon ETRI Attached Inst Taejon 305600 South Korea Korea Univ Grad Sch Informat & Secur Seoul 136701 South Korea

Recently, a malicious user attacks a web browser through a malicious page that exploits the vulnerability of the browser and that executes malicious code. To prevent this attack, some methods have been devised such as DEP (Data Execution Prevention) that prevents data in stack frame or heap region from being executed. However, to evade these defense techniques, return-oriented programming (ROP) is introduced. ROP executes arbitrary code indirectly using gadget, which is group of instructions including ret instruction in a module that doesn't apply ASLR (Address Space Layout Randomization). In this paper, we propose a static approach to detect ROP payload in a network irrespective of the environment of the system under attack. Most studies have tried to detect ROP attacks using dynamic analysis, because ROP has various addresses of gadgets according to loaded modules. These methods have a limitation that must consider the environment of system to operate ROP, such as the version of OS and modules including gadgets. To overcome this limitation, our method detects ROP payload using static analysis without preliminary knowledge about the environment. We extract five characteristics of ROP and then propose a novel algorithm, STROP, to detect ROP in payload without execution. Our idea is as follows: STROP makes stack frame using input payload statically. It extracts addresses suspected as indicating gadgets and makes groups using the addresses. And then, STROP determine whether the payload includes ROP based on static characteristics. We implement a prototype using snort (network-based intrusion system) and evaluate it. Experiments show that our technique can detect ROP payload with a low number of false alarms. False positive (FP) is 1.3% for 2,239 benign files and 0.05-0.51% for 1GB packet dump file. Among 68 ROP payloads, STROP detects 51 payloads. This research can be applied to existing systems that collect malicious codes, such as Honeypot.

关键词： return-oriented programming exploit code network based intrusion detection system

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Intercept the Cloud network From Brute Force and DDoS Attacks via intrusion detection and Prevention system

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IEEE ACCESS 2021年 9卷 152300-152309页

作者： Nadeem, Muhammad Arshad, Ali Riaz, Saman Band, Shahab S. Mosavi, Amir Abasyn Univ Dept Comp Islamabad 75660 Pakistan Inst Space & Technol Dept Comp Sci Islamabad 44000 Pakistan Natl Univ Technol Dept Comp Sci Islamabad 44000 Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr Touliu 64002 Yunlin Taiwan Tech Univ Dresden Fac Civil Engn D-01069 Dresden Germany Obuda Univ John von Neumann Fac Informat H-1034 Budapest Hungary

Cloud computing is considered to be the best technique for storing data online instead of using a hard drive. It includes three different types of computing services that are provided to remote users via the Internet. Cloud computing offers its end users a variety of options, such as cost savings, access to online resources and performance, but as the number of users in cloud computing grows, so does the likelihood of an attack. Various researchers have researched and provided many solutions to prevent these attacks. One of the best ways to detect an attack is through an intrusion detection system. This article will develop an efficient framework in which will use and discuss various security solutions for a network. Every device on the network will be attacked and the attack rate of the entire network will be monitored. After that, various solutions will be provided to protect the cloud server from attacks. Different principles will be used at the end of the article to test the accuracy of the results and from each conclusion it will be concluded to what extent the results of this paper are better than others.

关键词： Cloud computing Servers intrusion detection Computational modeling Security Monitoring Denial-of-service attack intrusion detection system network based intrusion detection system host based intrusion detection system spam DDoS Bot cloud security

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An efficacious intellectual framework for host based intrusion detection system

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Procedia Computer Science 2019年 165卷 9-17页

作者： D. Selvamani V. Selvi SIVET COLLEGE GOWRIVAKKAM CHENNAI -600073 INDIA MOTHER TERESA WOMEN’S UNIVERSITY KODAIKANAL- 624101 INDIA

intrusion detection systems (IDS) are indispensible for all types of networks to protect them from the intruders. The IDS have to process millions of network packets with many features, which delay the detection of anomalies. To understand the attacks of the past and to design proper tools to defeat their impending peril, Host-based IDS or HIDS, establishes to be a robust design. An Efficacious Intellectual Framework for Host based intrusion detection with Rule Structure Generation and Pattern Matching algorithm sets the rule structure for the unknown attack generated by using Association Rule Mining in the Map Reduce Framework. It is accomplished in two stages. In the first stage, an efficacious Rule structure is generated using Intellectual method. In the second stage, Brute Force algorithm pattern matching algorithm is utilized in the proposed framework. It is proper to audit and review logs for malicious activity. Notably intrusions are rare after proven analysis to prevent the attacks to happen. The present HIDS establishes to be a robust design for understanding of attacks of the past and determining effective methods to defeat their future threats.

关键词： Data Mining MapReduce network based intrusion detection system Association Rule Mining Brute Force algorithm

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Multivariate Linear Regression Model for Host based intrusion detection 1

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1st International Conference on Computational Intelligence in Data Mining (ICCIDM)

作者： Gautam, Sunil Kumar Om, Hari Indian Sch Mines Dept Comp Sci & Engn Dhanbad 826004 Bihar India

ISBN: (纸本)9788132222026;9788132222019

Computer security is an important issue for an organization due to increasing cyber-attacks. There exist some intelligent techniques for designing intrusion detection systems which can protect the computer and network systems. In this paper, we discuss multivariate linear regression model (MLRM) to develop an anomaly detection system for outlier detection in hardware profiles. We perform experiments on performance logfiles taken from a personal computer. Simulation results show that our model discovers intrusion effectively and efficiently.

关键词： intrusion detection system Multivariate linear regression model Mean square error Host based intrusion detection system network based intrusion detection system

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