IDS Based Network Security Architecture with TCP/IP Parameters Using Machine Learning
| Title | IDS Based Network Security Architecture with TCP/IP Parameters Using Machine Learning |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Ponmaniraj, S., Rashmi, R., Anand, M. V. |
| Conference Name | 2018 International Conference on Computing, Power and Communication Technologies (GUCON) |
| Keywords | authentic data, authentication, authorisation, Classification algorithms, Communication networks, composability, computer access, Computer architecture, computer network security, computer security, Confidentiality and Vulnerabilities, crypto algorithms, cryptography, data confidentiality, data reliability, data set, Internet, Intrusion detection, IoT (Internet of Things), IP networks, IPsec, KNN classification, kNN classification algorithm, learning (artificial intelligence), machine learning, network access, Network Security Architecture, networks, normal threats data sets, pattern classification, privacy, Protocols, pubcrawl, regular traffic pattern, Reinforcement algorithm, reliability, resilience, Resiliency, securities threats, security, security actions, security devices, security of data, security problems, server based access, TCP-IP packets, TCP-IP parameters, TCP/IP Protocols, TCPIP, telecommunication traffic, transport protocols, vulnerable sites, WEKA and Snoor tools |
| Abstract | This computer era leads human to interact with computers and networks but there is no such solution to get rid of security problems. Securities threats misleads internet, we are sometimes losing our hope and reliability with many server based access. Even though many more crypto algorithms are coming for integrity and authentic data in computer access still there is a non reliable threat penetrates inconsistent vulnerabilities in networks. These vulnerable sites are taking control over the user's computer and doing harmful actions without user's privileges. Though Firewalls and protocols may support our browsers via setting certain rules, still our system couldn't support for data reliability and confidentiality. Since these problems are based on network access, lets we consider TCP/IP parameters as a dataset for analysis. By doing preprocess of TCP/IP packets we can build sovereign model on data set and clump cluster. Further the data set gets classified into regular traffic pattern and anonymous pattern using KNN classification algorithm. Based on obtained pattern for normal and threats data sets, security devices and system will set rules and guidelines to learn by it to take needed stroke. This paper analysis the computer to learn security actions from the given data sets which already exist in the previous happens. |
| URL | https://ieeexplore.ieee.org/document/8674974 |
| DOI | 10.1109/GUCON.2018.8674974 |
| Citation Key | ponmaniraj_ids_2018 |
- security actions
- networks
- normal threats data sets
- pattern classification
- privacy
- Protocols
- pubcrawl
- regular traffic pattern
- Reinforcement algorithm
- Reliability
- resilience
- Resiliency
- securities threats
- security
- Network Security Architecture
- security devices
- security of data
- security problems
- server based access
- TCP-IP packets
- TCP-IP parameters
- TCP/IP Protocols
- TCPIP
- telecommunication traffic
- transport protocols
- vulnerable sites
- WEKA and Snoor tools
- data confidentiality
- authentication
- authorisation
- Classification algorithms
- Communication networks
- composability
- computer access
- computer architecture
- computer network security
- computer security
- Confidentiality and Vulnerabilities
- crypto algorithms
- Cryptography
- authentic data
- data reliability
- data set
- internet
- Intrusion Detection
- IoT (Internet of Things)
- IP networks
- IPsec
- KNN classification
- kNN classification algorithm
- learning (artificial intelligence)
- machine learning
- network access