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Practical Steps for Securing RFID Systems
Published in Syed Ahson, Mohammad Ilyas, RFID Handbook, 2017
A. Karygiannis, Bernie Eydt, Ted S. Phillips
Control: Physical access controls include fences, gates, walls, locked doors, turnstiles, surveillance cameras, and security guards. When the objective is to limit radio communication over a short distance, room walls or partitioned stalls might provide adequate protection if they are opaque to the relevant radio frequencies that the RF subsystem uses.
Towards data fusion-based big data analytics for intrusion detection
Published in Journal of Information and Telecommunication, 2023
The previous works focused on various approaches to data fusion and its application in different domains, such as intrusion detection, traffic estimation, physical access control analysis, and employee activity monitoring. Other works focused on using data visualization: Geepalla and Asharif (2020) developed a Graph-based method for the analysis of Physical Access Control (PAC) log data to detect normal and abnormal behaviour. They have developed an Eclipse application (AC2Neo4j) that transforms PAC log data into Neo4j automatically, thus allowing for powerful analysis to take place using cypher queries. Velampalli S et al. (2019) used a graph-based approach that analyzes the data for suspicious employee activities. They focused on graph-based knowledge discovery in structural data to mine for interesting patterns and anomalies. They first reported the normative patterns in the data and then discovered any anomalous patterns associated with the previously discovered patterns. For visualizing the suspicious patterns, they used the enterprise graph database Neo4j.
Secure storage and accessing the data in cloud using optimized homomorphic encryption
Published in Journal of Control and Decision, 2023
S. Gnana Sophia, K. K. Thanammal, S. S. Sujatha
Cloud computing is a lengthy computing universe that provides vast amounts of storage (Mahendiran & Sairam, 2012). Because users outsource sensitive data to cloud providers, data storage security is a difficult and skilled task, and user data must be protected against security issues (Sandra Durcevic, 2020; Rajathi & Saravanan, 2013). Data privacy and network safety is one of the most complex continuing cloud computing research projects. Without requiring any hardware, Cloud-based access control may enable remote management of processes such as adding or revoking user access (Shah et al., 2008). Every organization is not prepared to invest in high local server and hardware infrastructure costs while a physical access control can give your organization security (Wang et al., 2009). Cloud storage refers to a set of tools that provide on-demand services as well as network access to resources (Xue & Zhang, 2010; Wobst, 2001). Data access refers to the on-demand, authorized ability to recapture, repair, copy, or move data from information technology systems (Joshi et al., 2018, July).
Modified Apriori Based Data Sanitization for Cloud Data Security: An Optimization Assisted Model
Published in Cybernetics and Systems, 2022
Shrikant D. Dhamdhere, M. Sivakkumar, V. Subramanian
The global environment benefits greatly from the cloud computing sector in a number of industries, including business, medical, and education. A key component of the services provided internationally is protection. Data security is critical in a cloud network context (Kumar and Rishiwal 2019; Xue and Ren 2019). Cloud data lists several sorts of security threats such as security apps, audit scheduling, encryption, key management, identity and access management, and user and physical access control. In recent times, data encryption has been carried out by a variety of encryption algorithms (Wang 2020; Rao and Rao 2019) that are capable of converting text into a new form referred to as ciphertext. Unauthorized users will be unable to access this encrypted result of the given input as plain text. Furthermore, encrypted data generates a technique for decoding, which could supply the authorized user with the regular text (Tahir et al. 2021; Mo 2019) using a separate key. Privacy protection in the cloud is divided into two parts: data processing security as well as data storage security. Additionally, when data is collected in a data center, it can be difficult to guarantee the privacy of customer data. Moreover, the data processing security concerns in virtualized cloud architecture to maintain user confidentiality during runtime (Hababeh et al. 2019; Kong et al. 2019).