Privacy is a serious concern related to sharing videos or images among people over the Internet. As a method to preserve images’ privacy, chaos-based image encryption algorithms have been used widely to fulfil such a requirement. However, these algorithms suffer from a low key-space, significant computational overhead, and a lag in resistance against differential attacks. This paper presents a novel chaos-based image encryption method based on permutation and substitution using a single Substitution Box (S-Box) to address issues in contemporary image encryption algorithms. The proposed encryption technique’s efficiency is validated through extensive experiments as compared to the state-of-the-art encryption algorithms using different measures and benchmarks. Precisely, the collected results demonstrate that the proposed technique is more resilient against well-known statistical attacks and performs well under plaintext attacks. Indeed, the proposed scheme exhibits very high sensitivity concerning the plaintext attack. A minor change in the encryption key or the plain text would result in a completely different encrypted image.

Driven by the special requirements of the Low-power and Lossy Networks (LLNs), the IPv6 Routing Protocol for LLNs (RPL) was standardized by the IETF some six years ago to tackle the routing issue in such networks. Since its introduction, however, numerous studies have pointed out that, in its current form, RPL suffers from issues that limit its efficiency and domain of applicability. Thus, several solutions have been proposed in the literature in an attempt to overcome these identified limitations. In this survey, we aim mainly to provide a comprehensive review of these research proposals assessing whether such proposals have succeeded in overcoming the standard reported limitations related to its core operations. Although some of RPL’s weaknesses have been addressed successfully, the study found that the proposed solutions remain deficient in overcoming several others. Hence, the study investigates where such proposals still fall short, the challenges and pitfalls to avoid, thus would help researchers formulate a clear foundation for the development of further successful extensions in future allowing the protocol to be applied more widely.

In RPL routing protocol, the DAO (Destination Advertisement Object) control messages are announced by the child nodes to their parents to build downward routes. A malicious insider node can exploit this feature to send fake DAOs to its parents periodically, triggering those parents, in turn, to forward the fake messages upward to the root node. In this study, we show how this behavior can have a detrimental side effect on the performance of the network, increasing power consumption, latency and reducing reliability. To address this problem, a new scheme is introduced to mitigate significantly the effect of the DAO attack on network performance.

The rapid advancement in consumer technology has led to an exponential increase in the connected devices, resulting in an enormous and continuous flow of data, particularly the image data. This data needs to be processed, managed, and secured efficiently, especially in the quantum-enabled consumer technology era. This paper, in this regards, presents a quantum image encryption scheme featuring a novel two-phase chaotic confusion-diffusion architecture. The proposed architecture consists of four distinct confusion-diffusion modules that perform a simultaneous qubit and pixel-level encryption on both the position and intensity of quantum encoded pixels. Moreover, quantum circuits for ’qubit-level chaotic transformation’ and ’chaos-based selective perfect shuffle operation’ have been implemented, which collectively enhance the encryption strength of the proposed scheme. Extensive evaluation has been performed based on various statistical security parameters, such as entropy and correlation. When subjected to differential attacks, the proposed scheme proved its resilience exhibiting ideal results of average 99.6% NPCR (Number of Pixels Change Rate) and 33.5% UACI (Unified Average Changing Intensity). Besides, the proposed scheme also demonstrated resilience against occlusion attacks. Tests involving 50% data occlusion from encrypted images validated the proposed scheme’s capability to successfully decrypt the tampered images, recovering maximum information.

In this paper, we introduce Drizzle, a new algorithm for maintaining routing information in the Low-power and Lossy Networks (LLNs). The aim is to address the limitations of the currently standardized routing maintenance (i.e. Trickle algorithm) in such networks. Unlike Trickle, Drizzle has an adaptive suppression mechanism that assigns the nodes different transmission probabilities based on their transmission history so to boost the fairness in the network. In addition, Drizzle removes the listen-only period presented in Trickle intervals leading to faster convergence time. Furthermore, a new scheme for setting the redundancy counter has been introduced with the goal to mitigate the negative side effect of the short-listen problem presented when removing the listen-only period and boost further the fairness in the network. The performance of the proposed algorithm is validated through extensive simulation experiments under different scenarios and operation conditions. In particular, Drizzle is compared to four routing maintenance algorithms in terms of control-plane overhead, power consumption, convergence time and packet delivery ratio (PDR) under uniform and random distributions and with lossless and lossy links. The results indicated that Drizzle reduces the control-plane overhead, power consumption and the convergence time by up to 76%, 20% and 34% respectively while maintaining approximately the same PDR rates.

LoRa networks represent a promising technology for Internet of Things applications due to their long range, low cost, and energy efficiency. However, their ALOHA-based access method and duty cycle restrictions can limit their scalability and reliability in high-density networks. To address such a challenge, this article proposes the autonomous time-slotted LoRa (ATS-LoRa), protocol that allows LoRaWAN nodes to autonomously determine their optimal transmission parameters without extensive downlink transmissions from the gateway. ATS-LoRa utilizes the geographical coordinates of the nodes and their gateway in a novel way to allow them to determine their appropriate transmission parameters, such as the spreading factor, the channel frequency, and the slot ID. ATS-LoRa performance is evaluated through extensive simulations under different operating conditions showing an average throughput of around 47 times better than the adaptive data rate algorithm of LoRaWAN protocol.