Fog-Computing-Based Cyber–Physical System for Secure Food Traceability through the Twofish Algorithm

Exploring security threats and solutions Techniques for Internet of Things (IoT): from vulnerabilities to vigilance

The rapid proliferation of Internet of Things (IoT) devices across various industries has revolutionized the way we interact with technology. However, this widespread adoption has also brought about significant security challenges that must be addressed to ensure the integrity and confidentiality of data transmitted and processed by IoT systems. This survey paper delves into the diverse array of security threats faced by IoT devices and networks, ranging from data breaches and unauthorized access to physical tampering and denial-of-service attacks. By examining the vulnerabilities inherent in IoT ecosystems, we highlight the importance of implementing robust security measures to safeguard sensitive information and ensure the reliable operation of connected devices. Furthermore, we explore cutting-edge technologies such as blockchain, edge computing, and machine learning as potential solutions to enhance the security posture of IoT deployments. Through a comprehensive analysis of existing security frameworks and best practices, this paper aims to provide valuable insights for researchers, practitioners, and policymakers seeking to fortify the resilience of IoT systems in an increasingly interconnected world.

An enhanced encryption-based security framework in the CPS Cloud

The rapid advancement of computation techniques and cloud computing has led to substantial advancements in Cyber-Physical Systems (CPS), particularly in the field of health care. There are a variety of ways in which CPS is used in healthcare today, including delivering intelligent feedback systems, automatically updating patient data digitally, monitoring patients passively with biosensors, etc. In recent years, cyber-physical systems have become capable of making lifesaving decisions as they are becoming more connected to the cloud. However, healthcare has become one of the most critical issues for many. A CPS network uses the Internet of Medical Things (IoMT) to continuously monitor patients’ health metrics such as body temperature, heart rate, etc. Due to physical connectivity restrictions, networks are more susceptible to security threats. In spite of the fact that the data is stored in the cloud, it is necessary to provide security regardless of device security and network security. Several cyber-security vulnerabilities have been identified in cloud-based healthcare systems in particular. To give patients a reliable healthcare experience, security concerns with CPSs need to be addressed carefully. In this context, this paper proposes a Cross-Breed Blowfish and MD5 (CBM) approach to improve the security of health data in the CPS cloud. The proposed model uses the wireless sensor network, in which data acquired by the network is transmitted via the transmitting node. Using the fuzzified effective trust-based routing protocol (FET-RP), the most efficient path for data travel is selected. The best route is determined using Butter-Ant Optimization (BAO) algorithm. The proposed method conveys data throughput encryption and decryption in a decoded format. The encrypted data is then stored in the cloud database for security reasons. The route finding algorithm is the one which is sending the data from one end to other end. The data is encrypted based on the source and destination. We compare the performance metrics of our recommended technique to those of other existing techniques, such as RSA, Two fish, ICC, and FHEA, in order to ensure that it performs optimally. The values of Cross Breed Blowfish and MD5 and FET-RP with regard to the performance metrics in terms of encryption (60 ms), decryption (55 ms), latency (60 s), throughput (97 mbps), security level (98%), and execution time (57 ms) which outperforms the conventional methods by 10–15%. Also the proposed encryption shows the considerable improvement in the level of security making our model a real world solution.