The World Wide Web is experiencing a daily increase in data transmission because of developments in multimedia technologies. Consequently, each user should prioritize preventing illegal access of this data by encrypting it before moving it over the Internet. Numerous color image encryption schemes have been developed to protect data security and privacy, indifferent to the computation cost. However, most of these schemes have high computational complexities. This research proposes a fast color image scrambling and encryption algorithm depending on different chaotic map types and an S-box that relies on a hyperchaotic map principle. The first step involves converting color image values from decimal representation to binary representation in the scrambling stage by changing the location of the bits according to a proposed swapping algorithm. Next, in the second scrambling stage, the same process occurs after returning color image values from binary representation to decimal representation and generating an S-box with the assistance of two types of chaotic map, namely, a 2D Zaslavsky map and a 3D Hénon map. Thus, this S-box is relied upon to swap the locations of the pixels in the color image. The encryption procedure begins with the production of three key matrices using a hybrid technique that employs two low-complexity types of chaotic map, namely, a 1D Logistic map and a 3D Hénon map, followed by an XORed as a lightweight process between each key generated for the three matrices and the corresponding red, green, and blue image channels. According to the findings, the proposed scheme demonstrates the most efficiency in terms of lowering the computational cost and shows its effectiveness against a wide range of cryptographic attacks.

The information obtained from external sources within the cloud and the resulting computations are not always reliable. This is attributed to the absence of tangible regulations and information management on the part of the information owners. Although numerous techniques for safeguarding and securing external information have been developed, security hazards in the cloud are still problematic. This could potentially pose a significant challenge to the effective adoption and utilization of cloud technology. In terms of performance, many of the existing solutions are affected by high computation costs, particularly in terms of auditing. In order to reduce the auditing expenses, this paper proposes a well-organised, lightweight system for safeguarding information through enhanced integrity checking. The proposed technique implements a cryptographic hash function with low-cost mathematic operations. In addition, this paper explores the role of a semi-trusted server with regard to smart device users. This facilitates the formal management of information prior to distribution through the IoT-cloud system. Essentially, this facilitates the validation of the information stored and exchanged in this environment. The results obtained show that the proposed system is lightweight and offers features such as a safeguarding capability, key management, privacy, decreased costs, sufficient security for smart device users, one-time key provision, and high degree of accuracy. In addition, the proposed method exhibits lower computation complexity and storage expenses compared with those of other techniques such as bilinear map-based systems.

Internet of Vehicles (IoV) has greatly improved safety and quality of services in intelligent transportation system (ITS). However, the deployed dedicated short-range communication (DSRC) protocol broadcasts messages after every 100–300 ms. This presents some challenges in message validation within this short duration. As such, most of the current authentication schemes which incur heavy computation and communication overheads are not suitable in this environment. In this article, an efficient authentication scheme is presented based on lightweight cryptographic primitives, such as collision-resistant one-way hashing functions and exclusive OR (XOR) operations. In our protocol, two-factor authentication is attained using physically unclonable function (PUF) generated identities and random nonces, as well as passwords. Extensive formal security verification using the Real or Random (RoR) model shows that it is provably secure. In addition, elaborate semantic security analysis shows that it offers anonymity, untraceability, and key secrecy as well as resilience against numerous IoV attack vectors. In terms of performance, comparative evaluations demonstrate that it reduces computation and energy consumptions by 42.31%. Moreover, it increases the supported security features by 26.67%.

Precision agriculture encompasses automation and application of a wide range of information technology devices to improve farm output. In this environment, smart devices collect and exchange a massive number of messages with other devices and servers over public channels. Consequently, smart farming is exposed to diverse attacks, which can have serious consequences since the sensed data are normally processed to help determine the agricultural field status and facilitate decision-making. Although a myriad of security schemes has been presented in the literature to curb these challenges, they either have poor performance or are susceptible to attacks. In this paper, an elliptic curve cryptography-based scheme is presented, which is shown to be formally secure under the Burrows–Abadi–Needham (BAN) logic. In addition, it is semantically demonstrated to offer user privacy, anonymity, unlinkability, untraceability, robust authentication, session key agreement, and key secrecy and does not require the deployment of verifier tables. In addition, it can withstand side-channeling, physical capture, eavesdropping, password guessing, spoofing, forgery, replay, session hijacking, impersonation, de-synchronization, man-in-the-middle, privileged insider, denial of service, stolen smart device, and known session-specific temporary information attacks. In terms of performance, the proposed protocol results in 14.67% and 18% reductions in computation and communication costs, respectively, and a 35.29% improvement in supported security features.

The Industrial Internet of Things (IIoT) has become a pivotal field of development that can increase the efficiency of real-time collection, recording, analysis, and control of the entire activities of various machines, and can actively enhance quality and reduce costs. The traditional IIoT depends on centralized architectures that are vulnerable to several kinds of cyber-attacks, such as bottlenecks and single points of failure. Blockchain technology has emerged to change these architectures to a decentralized form. In modern industrial settings, blockchain technology is utilized for its ability to provide high levels of security, low computational complexity, P2P communication, transparent logs, and decentralization. The present work proposes the use of a private blockchain mechanism for an industrial application in a cement factory, which offers low power consumption, scalability, and a lightweight security scheme; and which can play an efficient role in controlling access to valuable data generated by sensors and actuators. A low-power ARM Cortex-M processor is utilized due to its efficiency in terms of processing cryptographic algorithms, and this plays an important part in improving the computational execution of the proposed architecture. In addition, instead of proof of work (PoW), our blockchain network uses proof of authentication (PoAh) as a consensus mechanism to ensure secure authentication, scalability, speed, and energy efficiency. Our experimental results show that the proposed framework achieves high levels of security, scalability and ideal performance for smart industrial environments. Moreover, we successfully realized the integration of blockchain technology with the industrial internet of things devices, which provides the blockchain technology features and efficient resistance to common cyber-security attacks.

Patients’ data constitutes the vast majority of information exchanged over the Internet. The magnitude of maintaining its security and privacy directly correlates to the importance and privacy of the patients themselves. The manipulation of this data negatively impacts the patient's life and treatment, thus the researchers were inclined to find solutions for this confidentiality challenge by concealing the data to prevent unauthorized access. The process of data concealment is more complex when dealing with large amounts of data. Often, the proportions of the medical image are sizable, which creates challenges when compressing data while maintaining high accuracy. In this paper, a system for securing and compressing medical images based on the Compressive Sensing (CS) principle is presented. The medical image is divided into 8×4 sub-matrices that are multiplied by a 3×8 sensor matrix consisting of Gaussian random numbers. The proposed solution reduces the image's original size by about 30% and conceals it as a random distribution inside an audio (wav) file for more security, using the LSB technique for low complexity. For reconstruction, the sensed image is multiplied by the pseudo-inverse of Moore-Penrose. The statistical analysis proved the efficacy of the system in compression and recovery with reduced cost and time consumption, combined with reduced distortion of the cover file; it was also judged to be increasingly efficient compared to previous research.