Enhancing Security and Privacy on Smart City’s Collected Data: A Fog Computing Perspective

Smart cities use information and communication technologies to deliver services to their citizens. Use of ICT makes them to be more intelligent and efficient in usage of resources, resulting in cost and energy savings, improved service delivery and quality of life. Smart cities are expected to be the fundamental pillars of continued economic growth and improved services delivery. Smart City technology is having ability to constantly gather information about the city, sharing the data with people, devices and technologies or borrowing relevant data from elsewhere, for analysis to enable informed decision making. For instance internet of things has emerged as a technological driving force in real time service delivery in smart cities. These applications provide new abilities, enhancing monitoring, and provision of action oriented process on control and device management. Smart devices are a major source of big data in smart cities. With expected increase of billions of smart devices and sensors in smart city by the year 2020, more data will be generated which will reduce efficiency of cloud access, due to increased volume. Security and privacy of data is a challenge in smart city, negligence in data security and privacy can be amplified in folds resulting to faulty applications, services along with paralyzing the entire city through Denial of Service (DDoS) attack, Spear Phishing Attacksand Brute-Force Attacks among others.Fog computing FC is a new paradigm that is intended to extend cloud computing CC through deployment of processing and localized units into the network edge, enabling low latency, offering location awareness and latency sensitiveness. Homomorphism for encryption, authorization, authentication, and classification are performed on collected data in smart cities to improve security and privacy. In this paper assimilation and analysis, is performed with fog computing aspects of decentralization, different policies for datacenter transferstrategies being analyzed.Processing time, access time, request time, response time and cost analysis show system efficiency