Protection in Visual Sensor Networks : A Survey

ion. This popular technique replaces sensitive image regions with, e.g., bounding boxes or, in case of persons, with avatars, stick-figures and silhouettes [Senior et al. 2005]. Another form of abstraction is meta-information attached to a video. This can be object properties such as position and dimensions, but also names of identified persons [Tansuriyavong and Hanaki 2001]. Depending on the type of abstraction, either behavior, identity or both can be preserved. Note that if identity is preserved, additional protection (e.g., by encryption) should be considered. Encryption. Data encryption is used by many systems to protect sensitive regions. When encrypted, regions of interest can no longer be viewed by persons who do not have the appropriate decryption keys. Simple encryption protects not only the identity of monitored persons but also their behavior. Upon decryption, both – identity and behavior – are revealed. By using multiple encryption keys or split keys as described in [Schaffer and Schartner 2007], a system can be designed that requires cooperation among multiple operators to decrypt the original data which provides some protection against operator misuse. A privacy protection system can support also multiple privacy levels at the same time where a video stream contains several sub-streams with different types of information. Depending on their sensitivity, these levels have to be separately encrypted with one or more individual encryption keys. A multi-level approach allows a privacy protection system to be designed that presents different types of information to observers depending on their security clearance. Low-privileged operators can only access the version of the stream where behavioral data is visible while supervisors or government agencies could get access to the original data that contains the identities of monitored persons. In our own work [Winkler and Rinner 2011] we have explored a multi-level approach where for especially sensitive video content a combination of two or more encryption keys is used to enforce the four-eyesprinciple for data access. Choosing a protection technique or a combination of various techniques depends on the application and the involved goals. Blanking protects both behavior and identity – only the presence of persons remains perceptible. Therefore it is usable only in basic surveillance and intruder detection scenarios. Obfuscation and scrambling allow to monitor the behavior of persons and are therefore more suitable for public safety applications where not only presence of persons but also detection of unusual behavior is of importance. Regardless of the chosen protection technique two key questions remain the same: (1) is privacy adequately protected by the chosen technique and (2) what is the impact on the utility of the visual sensor network. Work by Gross et al. [2006] indicates that the overall protection capabilities ob pixelation and blurring are relatively low. In more recent work, Dufaux and Ebrahimi [2010] present a framework for the evaluation of privacy protection mechanisms. Their results show also that simple pixelation and blurring offer only limited protection. Blurred or pixelated human faces can often still be identified with standard face recognition algorithms. In contrast to that, the evaluation results indicate that scrambling mechanisms perform much better. A study by Boyle et al. [2000] on the effects of filtered video on awareness and privacy shows that pixelation provides better privacy protection than blurring. Korshunov et al. [2012a] developed an evaluation framework to systematically investigate the privacy protection vs. system utility tradeoff. The framework consists of a ACM Computing Surveys, Vol. 0, No. 0, Article 0, Publication date: 2014. Security and Privacy Protection in Visual Sensor Networks: A Survey 0:15 set of standardized questions that are used to assess which information could be observed from a privacy-protected video. Questions cover, e.g., the gender and race of a person or properties such as worn glasses or scarfs. A set of video sequences was shown to subjects under controlled lab conditions. The subjects had only a limited amount of time to answer the given questions. The study results indicate that pixelation yields best performance in terms of balance between privacy protection and intelligibility of the video content. Best privacy protection and least intelligibility was achieved with masking filters. Blurring filters resulted in exactly the opposite performance – best intelligibility and least privacy protection. In successive work, Korshunov et al. [2012b] adopted a crowdsourcing approach to get feedback from a larger number of participants. A Facebook application called VideoRate2 allows users with a valid Facebook account to participate in the evaluation. Results obtained from VideoRate and the previous lab tests are largely consistent. Abstraction techniques can be tuned to preserve behavior, identity or both. Finally, encryption is the technique of choice in scenarios where strong but reversible identity protection is required. As with simple blanking, also behavior is fully protected and can no longer be monitored. If behavior monitoring is required, a multi-level approach must be chosen.