1. A Study of the Geographic Spread and Security of Wireless Access Points Stuart Cunningham & Vic Grout Centre for Applied Internet Research (CAIR) University of Wales, NEWI Plas Coch Campus, Mold Road, Wrexham, LL11 2AW, UK contact@cair-uk.org www.cair-uk.org NEWI North East Wales Institute of Higher Education - Centre for Applied Internet Research

2. Introduction Large uptake of Wi-Fi Home (especially significant) Business / Industry Academic … everywhere! Increased scope for research Service utilisation Roaming Behavioural studies

3. Wi-Fi Studies: Security Less work done in determining implementation of secure services Nature of wireless means physical boundaries are (almost) insignificant Given large uptake, especially of non- technical, home users, poses questions: Just how big is the Wi-Fi uptake? What is the uptake / awareness of security? Are there any differences between areas?

4. Real-World Case Study 16km 2 representative area Residential, industrial, commercial sectors Equipment GPS to fix locations Wi-Fi enabled laptop Coverage of area via road network Carried out during ‘ working hours ’ ~10 hours total to cover area Detection of Access Points Secure and non-secure

5. Real-World Case Study Reflection of ‘ war driving ’ scenario ‘ Parking Lot Attack ’ (Arbaugh et al., 2002)

6. Mapping Results 1153 Access Points detected

7. Mapping Results (Secure Vs. Unsecure) Security Secure WAPs891 (77%) Unsecure WAPs262 (23%) Data Rates 54 Mbps1027 (89%) 11 Mbps126 (11%) Total WAPs1153

8. Cluster Analysis Attempt to identify any correlation between ‘ areas ’ and groups of Access Points Cluster# APs Red ● 308 (26.71%) Blue ● 561 (48.66%) Green ● 284 (24.63%) 3 clusters don ’ t identify areas in this case …

9. Cluster Analysis Cluster# APs Blue ● 418 (36.25%) Purple ● 288 (24.98%) Green ● 268 (23.24%) Red ● 179 (15.52%) Attempt to identify any correlation between ‘ areas ’ and groups of Access Points Broad identification achieved

10. Discussion of Results Majority of APs are secure (77%) Notional study in 2002 revealed ~66% unsecure (Ward, 2002) Still, almost a quarter not secure(!) Similar spread across area Large uptake within residential zones 89% using IEEE 802.11g (rest 802.11b) Clustering useful in zone identification High number of residential vs. other areas skew results Beyond 4 clusters proved ineffective

11. Security Indexing (ongoing work) Requires formal zone definition (Z 1, Z 2, …, Z m ) Recognition of Access Point a within a Zone (a  Z) Denote, by A j, set, {a : a  Zj }, of access points in zone Z j. For any set of access points, A, denote the set of secure points by S(A) and the set of unsecure points by U(A). Can then calculate security index, SI j, for zone Z j as:

12. Security Indexing (ongoing work) Then require scoring or ordering from features Of the Zone: Level of industrial activity, property value, etc. Or of the access points: Density, type, etc. Each such scoring or ordering will give a value, V j or rank, R j, for each zone, Z j Calculating coefficients of correlation or rank correlation across zones will show different levels of dependence between features

13. Security Configuration Physically Reducing threats Antenna positioning Aerial Footprint Not always practical / suitable … Software-based WEP Encryption Shown to have shortcomings (Arbaugh et al., 2002) Wi-Fi Protected Access (WPA) Smart cards, USB and software tokens Hiding SSID ACL ’ s based on MAC or IP addresses Hybrid mixtures of techniques is more robust Revisions to IEEE standards pertinent Omni-directionalUni-directional

14. Conclusions & Future Work Large uptake of Wi-Fi Awareness of security Reflection of zones / communities Data collection Mapping limited by road network Biased GPS accuracy Areas with no road access Future Work How to optimise data collection in future? (Route Inspection Problem) More detailed detection mechanisms Comparisons with other regions

15. Thank you … … Any questions? NEWI North East Wales Institute of Higher Education - Centre for Applied Internet Research Stuart Cunningham & Vic Grout Centre for Applied Internet Research (CAIR) University of Wales, NEWI Plas Coch Campus, Mold Road, Wrexham, LL11 2AW, UK contact@cair-uk.org www.cair-uk.org