Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review

Abstract

The world is experiencing a rapid growth of smart cities accelerated by Industry 4.0, including the Internet of Things (IoT), and enhanced by the application of emerging innovative technologies which in turn create highly fragile and complex cyber–physical–natural ecosystems. This paper systematically identifies peer-reviewed literature and explicitly investigates empirical primary studies that address cyber resilience and digital forensic incident response (DFIR) aspects of cyber–physical systems (CPSs) in smart cities. Our findings show that CPSs addressing cyber resilience and support for modern DFIR are a recent paradigm. Most of the primary studies are focused on a subset of the incident response process, the “detection and analysis” phase whilst attempts to address other parts of the DFIR process remain limited. Further analysis shows that research focused on smart healthcare and smart citizen were addressed only by a small number of primary studies. Additionally, our findings identify a lack of available real CPS-generated datasets limiting the experiments to mostly testbed type environments or in some cases authors relied on simulation software. Therefore, contributing this systematic literature review (SLR), we used a search protocol providing an evidence-based summary of the key themes and main focus domains investigating cyber resilience and DFIR addressed by CPS frameworks and systems. This SLR also provides scientific evidence of the gaps in the literature for possible future directions for research within the CPS cybersecurity realm. In total, 600 papers were surveyed from which 52 primary studies were included and analysed.

A Predictive Vehicle Ride Sharing Recommendation System for Smart Cities Commuting

“…In addition, |KB|, is the total number of instances and N is the number of recommended instances. It holds that ap@N ∈ [0, 1]. However, ap@N is referred to a single user's instance.…”

“…The dataset has a size of | | = |KB| = 2958 instances containing GPS location information [35]. The experimental dataset is produced by the concurrent movement trajectories of | | = 100 users for = 7 days per week, in a total period of ∈ [1,8] weeks, within the coverage area of the municipality of New Philadelphia. The adopted dataset is visualized in Figure 2.…”

“…It is found that for value m = 6 proposed system achieves more efficient accuracy than the other values of m. Prediction accuracy results for the optimal value of historic window size in presented in Figure 4. To define in which the value prediction accuracy reaches its optimal value, research effort is experimented with 10-fold cross validation evaluation method for 1000 iterations based on a user population of = 100 users for = 7 days per week, in a total period of ∈ [1,8] weeks, and dataset size of 2958 instances containing spatial GPS coordinates. It is observed that is incremental and converges to value = 0.9168 after To define in which the value prediction accuracy a reaches its optimal value, research effort is experimented with 10-fold cross validation evaluation method for 1000 iterations based on a user population of U = 100 users for d = 7 days per week, in a total period of w ∈ [1, 8] weeks, and dataset size of 2958 instances containing spatial GPS coordinates.…”

“…The prediction accuracy results for optimal system convergence on certain week are presented in Figure 5. To define in which the value prediction accuracy reaches its optimal value, research effort is experimented with 10-fold cross validation evaluation method for 1000 iterations based on a user population of = 100 users for = 7 days per week, in a total period of ∈ [1,8] weeks, and dataset size of 2958 instances containing spatial GPS coordinates. It is observed that is incremental and converges to value = 0.9168 after = 4 week, which means that the adopted system has achieved its higher level of efficiency after the fourth week of experimental evaluation.…”

“…Specifically, cyber resilience and incident response are emerging issues in SC. IoT can address cyber resilience and support digital forensic incident response aspects towards a green ecosystem [1]. Efficient and integrated SC is discussed in [2], where the authors present a research network for sustainable SC to develop a methodology for strategic planning.…”