Component and Classification tables – 1st draft

Completed 1st draft of Component and Classification tables.

further things to be completed next week

  • add on diagrams and tables from papers and attach to document
  • do papers 13-18 or how many applicable, add to the document
  • review tables

Information Security and Local Area Networks

Table 1 – Component Table

Factor Attributes Instances
Type of study or review Type Qualitative, Quantitative
Aim Increase WLAN security, Increased data security, Prototype data security scheme, increase data privacy, Wireless Network security survey. ETA threats, Malicious insider threats. Network security and growing threats, Multi mode  and smart terminals
Data collection methods Research, experimental testing, Online survey questionnaire, Analyses and survey datasets used.
Settings/ countries Finland, China, India, Pakistan, Australia, New Zealand
Outputs  & Aims Problems identified Review of WLAN current landscape, wireless vulnerabilities. Open network. E Documents, List of security threats for WBAN and networks, current WLAN/Wireless architecture/protocols, Categorization of WLAN security, Future WLAN threats. Review of Wi-Fi applications, challenges of WLAN technology, Wifi security issues. Specific threats for wireless LANS – evil twin attack (ETA). Problem with existing ETA detection methods. Cyber attacks in WLANS. Intrusion detection technology.

Malicious insider threats and motivation – identification, privacy and data loss

Current network assessment methods NSSA (network security situational awareness

Taxonomy of threats in wireless networks. Identification of network threats. OSI model

Complexity of network, threats, and infectiveness of current tools. Gaps in research and tools used. Eavesdropper risk –in wireless communication and risk in wireless  network and mufti mode application

 

Schemes proposed Wardriving, passive scanning RC4 and Advanced Encryption Standard algorithm, Virtual private network encryption, Fusion data security protection scheme (FDSPSFSED), certificate-based group authentication scheme. Current security measure available for use (encryption, Securing WAP, minimise risk of DOS, Signal hiding, Soft computing, Fuzzy logic)

Add a decentralized wireless AP to an alliance of third parties, Build a C/S model, the client-server model. Multmodel mechanism scheme called BiRe (Bidirectional TCP SYN Reflection). Design a detection mechanism – CBDN (Condition Deep Belief Network)

detect cyber attacks to WLANS quicker. It uses a detection scheme based on CDBN (Condition Deep belief Network) intrusion, in ‘real time. Available security controls

New network assessment approach based on  using stack auto encoding network and back propagation neural networks.’ TM-STS scheme for a wireless network, consisting of multiple smart terminals, communicating with two kinds of wireless modes

 

Diagrams / visualization Data Security (Scheme framework ). List of Threats to ETL (Table 1).

ETA detection architecture (fig 4)

Overview of the proposed detection mechanism. (Figure 1)

Importance of determining malicious behaviour (table 6)

Taxonomy of threats (Figure 4)

 

Software /Hardware Tools Techniques used Wardriving, passive scanning, use of encryption schemes ((FDSPSFSED), designing two different network authentication programs.

“SamSelect” algorithm, Stacked Contractive Auto-encoder (SCAE) algorithm.’

NSSA technology. SAE-BPNN tech Network Intrusion Detection Systems (NIDS) and Intrusion Detection Systems (IDS)

Applications / Usage WLAN New applications and mechanisms for WLAN security, Wireless sensor nodes (WSN), Future threats for WLANS with no solutions
LAN LAN, WBANs
Data Security Data in network transmission, data access, data privacy
Issues/problems Limited to IPv4. Not Government organisation data, Not WLAN or LAN research or specific applications

 

 

 

Table 2 – Classification Table

S/N   Type of study/ review Outputs/ Aims SW/HW  Application of study / Usage
Author Type Aim Settings Problems Identified Scheme proposed Diagrams Techniques WLAN LAN Increase Data Security Issues
1 Lindross  et al., 2021 Qualitative Increase Security Finland. 720 WLANs Review of WLAN current landscape Use of wardriving Wardriving

Passive scanning

Yes
2 Li  et al., 2020

 

Qualitative Increase WLAN and data Security China wireless vulnerabilities VPN encryption network method to provide an encryption layer

Dynamic security model

RC4 encryption algorithm and the AES algorithm Yes Yes
3 Liu  et al., 2021 Qualitative Prototype  data security scheme China Open network security , E documents,

 

Fusion data security protection scheme ((FDSPSFSED) Figure 1 (page 3) use of encryption schemes Not mentioned Yes, data access
4 Yu  et al., 2021 Increase data privacy. Overview of WBAN security Current security threats and policy. Anonymous change protocol scheme. certificate-based group authentication scheme   Wireless networks WBANS Security and privacy
5 Nazir  et al., 2021 Qualitative Current WLAN security Pakistan / India Current WLAN and wireless security, architecture protocols issues threats and challenges. Future threats Security measures currently available for use (i.e. encryption, Securing WAP, minimise risk of DOS, Signal hiding,  Soft computing, Fuzzy logic) List of Threats to ETL (Table 1) n/a Yes
7 Tao  et al., 2021 Qualitative Propose a security scheme for wifi applications Problems/challenges with WLAN and wifi Add a decentralized wireless AP to an alliance of third parties.

Build a C/S model, the client-server model

different network authentication program yes n/a yes
8 Lu  et al., 2020 Qualitative Propose a scheme for ETA in WLANS Existing measures for ETA threats Multmodel mechanism scheme called BiRe (Bidirectional TCP SYN Reflection). ETA detection architecture (fig 4)   Yes Limit IPv4 network. Not IPv6
9 Yang  et al., 2020 Qualitative Review intrusion detection measures and propose  new mechanism China Cyber attacks in WLANS.

Current intrusion detection technology schemes

Detection scheme based on CDBN (Condition Deep belief Network) intrusion, in ‘real time FIGURE 1. Overview of the proposed detection mechanism.

 

SamSelect” algorithm, Stacked Contractive Auto-encoder (SCAE) algorithm Yes
10 de Sousa  et al., 2021 Quantitative Review of Malicious insiders  on-line survey questionnaires Australia, New Zealand Malicious insider threats and motivation.

Data Loss

Available security control methods Table 6 – Importance of determining malicious behaviour.   Yes – to a degree Yes Not Government organisation data, Not WLAN or LAN research
11 Tao  et al., 2020 Qualitative The imp importance of network assessment.” Identify problems with Current network assessment methods..

Accurate asses networks status

new network assessment approach  based on  using stack auto encoding network and back propagation neural networks.’

 

  NSSA technology.

SAE-BPNN tech

Not WLAN specific but applicable Yes Not WLAN specific
13 Ding  et al., 2020 Qualitative Review  eavesdropper risk in wireless  network and mufti mode application China Eavesdropper risk –in wireless communication.

Lack of research / attention has been paid to multi-terminal multi-mode wireless scenario

Proposed a TM-STS scheme for a wireless network, consisting of multiple smart terminals, communicating with two kinds of wireless modes

 

  Wireless network application Smart multi-mode terminals not in use atm
14 Hindy  et al., 2020 Qualitative Current detection tools based on outdated.

Challenges for networks.

Identification of network threats. (Network Hosts, software, physical, human threats)

Need to overcome old datasets.

Research gaps

Recommendation for next generation IDS Figure 4 – Taxonomy of threats (3 pages)

 

Network Intrusion Detection Systems (NIDS) and Intrusion Detection Systems (IDS) Yes

 

 

 

Diagrams  -To be added

 

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