By: David Maimon, Tamar Berenblum and David Weisburd
The proposed project, supported by the Israel National Cyber Bureau in the Prime Minister's Office, seeks to develop an understanding regarding the ways in which computer users expose themselves to cybercrime victimization over public and private computer networks. Moreover, this project seeks to identify the unique configuration of computer environments that exacerbate victims' vulnerabilities and support WIFI trespassers’ illegal operations with these networks. Importantly, since both public and private computer networks are situated within a range of residential environments, we suspect that street segments’ demographic and social characteristics could play a significant role in influencing private WIFIs’ likelihood to be compromised by WIFI trespassers. Moreover, we believe that street segments demographic characteristics may shape public WIFI users online behaviors while employing these networks. Our interdisciplinary research team will seek to address the following research questions: first, how prevalent are vulnerable private WIFI networks across different street segments are, and could illegitimate users of these networks be deterred from infiltrating them? And second, do surveillance cues and situational attributes that are common in street segments influence the online behaviors of public WIFI users? Answering these research questions will allow us to develop a set of recommendations regarding effective security practices that could be employed by both private and public WIFI users to enhance their cyber security posture and reduce susceptibility to cybercrime victimization.
To assess the volume of vulnerable private WIFI networks, we will to record the location of private wireless networks, and assess their vulnerabilities to being compromised. In order to do so our research team will drive a vehicle around street segments in Tel-Aviv and listen to WIFI networks signals using a portable computer and a GPS device. Then, we will investigate whether private WIFI trespassers could be deterred from login and using a private WIFI network, we will run a randomized trial. Specifically, we plan to send our research team members to selected street segments in Tel-Aviv. The street segments will be selected from the list we will survey in the first phase of data collection, and would vary based on their residents’ socioeconomic status. Team members will be equipped with a private portable wireless router that simulates private WIFI network. The team members will sit in the selected location for a period of 7 hours (between 7am-7pm) and will record illegal login attempts to our network. Our routers will not require login credentials (i.e. password and user names) and will be named “DAVID_PRIVATE”. However, when attempting to login to some of the routers (treatment group) the following message will appear on the trespassers’ computer screen: “This network is a private network. Please disconnect from it immediately. Traffic on this network is closely monitored.” Other routers (control group) will be set to present no message on the WIFI trespassers’ computer screen. Using this approach we will be able to assess whether a warning message in the attacked private WIFI network is indeed effective in deterring WIFI trespassers login attempt to the network. Deployment of our private WIFI networks in different residential communities will reveal whether street segments characteristics condition private WIFI trespassers’ compliance with the warning message.
To determine whether public WIFI networks’ technical characteristics and surveillance means influence public WIFI users’ decision to engage in legitimate (for instance browsing news website) and illegitimate (for instance illegal downloading of copyright content from the Internet and attacking computers) online behaviors we will run additional experiments. In our planned experiment, the research team members will attend 102 public locations (restaurants, bars, hotels, coffee houses) in Tel Aviv and allow Internet users a free access to the Internet from a public WIFI network we will set. If internet users in these locations would want to use our free WIFI services they will need to agree to our terms of use. In line with the terms of use of many well known public WIFI network operators around the world, a key condition in our term of use policy will emphasize that all the traffic recorded on the public WIFI network is subject to scientific analysis and is owned by the public WIFI owners. Once agreeing to the terms of use, public WIFI users will be randomly assigned to one of three conditions. Under the first treatment condition the following banner will be presented on the public WIFI network users’ computer screens: “In order to protect the network security, traffic on this network is closely monitored.” Under the second treatment condition, public WIFI users will be required to feed in their email address in a special login page we will design before they will be allowed to use our network. Under the control condition, no surveillance cues will be presented to the user and they will be allowed to use the network freely. We will test how each of these conditions influence the volume of legitimate and illegitimate online behaviors over the network, as well as the volume of computer-focused crime transmitted on it.
In both experiments, the research team will collect relevant information on the physical environments within which the WIFI networks are situated using observations. Specifically, we will record the number of individuals that are present in each research site, the number of male and female in the location and the frequency of their movements in the premise. We will also collect data regarding the physical layout of the research sites and the ratio of employees to clients. The data collected from all experiments will be merged with census data for two purposes: first, to identify a sample of places where crime is high and low, and where other characteristics vary, like collective efficacy. Second, we will use the data as a variable in predicting the level of cyber security.