No abstract

With the evolution of cybersecurity countermeasures, the threat landscape has also evolved, especially in malware from traditional file-based malware to sophisticated and multifarious fileless malware. Fileless malware does not use traditional executables to carry-out its activities. So, it does not use the file system, thereby evading signature-based detection system. The fileless malware attack is catastrophic for any enterprise because of its persistence, and power to evade any anti-virus solutions. The malware leverages the power of operating systems, trusted tools to accomplish its malicious intent. To analyze such malware, security professionals use forensic tools to trace the attacker, whereas the attacker might use anti-forensics tools to erase their traces. This survey makes a comprehensive analysis of fileless malware and their detection techniques that are available in the literature. We present a process model to handle fileless malware attacks in the incident response process. In the end, the specific research gaps present in the proposed process model are identified, and associated challenges are highlighted.

Abstract:Energy efficiency is a significant characteristic of battery-run devices such as sensors, RFID and mobile phones. In the present scenario, this is the most prominent requirement that must be served while introducing a communication protocol for an IoT environment. IoT network success and performance enhancement depend heavily on optimization of energy consumption that enhance the lifetime of IoT nodes and the network. In this context, this paper presents a comprehensive review on energy efficiency techniques used in IoT environments. The techniques proposed by researchers have been categorized based on five different layers of the energy architecture of IoT. These five layers are named as sensing, local processing and storage, network/communication, cloud processing and storage, and application. Specifically, the significance of energy efficiency in IoT environments is highlighted. A taxonomy is presented for the classification of related literature on energy efficient techniques in IoT environments. Following the taxonomy, a critical review of literature is performed focusing on major functional models, strengths and weaknesses. Open research challenges related to energy efficiency in IoT are identified as future research directions in the area. The survey should benefit IoT industry practitioners and researchers, in terms of augmenting the understanding of energy efficiency and its IoT-related trends and issues.

A Flying Ad-hoc Networks (FANETs) is an autonomous technology that creates a selforganized wireless network via Unmanned Arial Vehicles (UAVs). In this network, all UAVs can communicate within a restricted range of wireless communication in the absence of fixed infrastructure. As a result of high mobility, the limited energy, and the communication range of UAVs, network forming, and deformation between them are very frequent that causes packet delivery failure. Therefore, a stable route is always needed to ensure effective data dissemination between source and destination in FANETs. Since it has drastically changing network topology, therefore, to maintain the stable route during packet transmission, there is a need for a suitable routing protocol. This paper proposes an Optimized Location-Aided Routing (O-LAR) protocol which is the modified version of Location-Aided Routing (LAR) protocol. Our protocol's novelty comes from the fact that it established an optimal route between UAVs for information dissemination towards their respective destination UAV by considering weight function. A weighted function is used to decide the best next-hop node selection based on the parameters like residual energy, distance, and UAV movement direction. The performance of the O-LAR is evaluated mathematically and simulated through the NS-2 simulator. The empirical results attest that O-LAR improves the link duration, network lifetime, packet delivery ratio, and average throughput compared with the state-of-the-art protocols: LEPR, D-LAR, and LAR. Further, the proposed scheme reduces the number of next-hops, routing overhead and end-to-end delay compared to the state-of-the-art protocols.

No abstract

Postquantum cryptography for elevating security against attacks by quantum computers in the Internet of Everything (IoE) is still in its infancy. Most postquantum based cryptosystems have longer keys and signature sizes and require more computations that span several orders of magnitude in energy consumption and computation time, hence the sizes of the keys and signature are considered as another aspect of security by green design. To address these issues, the security solutions should migrate to the advanced and potent methods for protection against quantum attacks and offer energy efficient and faster cryptocomputations. In this context, a novel security framework Lightweight Postquantum ID-based Signature (LPQS) for secure communication in the IoE environment is presented. The proposed LPQS framework incorporates a supersingular isogeny curve to present a digital signature with small key sizes which is quantum-resistant. To reduce the size of the keys, compressed curves are used and the validation of the signature depends on the commutative property of the curves. The unforgeability of LPQS under an adaptively chosen message attack is proved. Security analysis and the experimental validation of LPQS are performed under a realistic software simulation environment to assess its lightweight performance considering embedded nodes. It is evident that the size of keys and the signature of LPQS is smaller than that of existing signature-based postquantum security techniques for IoE. It is robust in the postquantum environment and efficient in terms of energy and computations.

<p><span>Recent advancement in wireless sensor networks primarily depends upon energy constraint. Clustering is the most effective energy-efficient technique to provide robust, fault-tolerant and also enhance network lifetime and coverage. Selection of optimal number of cluster heads and balancing the load of cluster heads are most challenging issues. Evolutionary based approach and soft computing approach are best suitable for counter the above problems rather than mathematical approach. In this paper we propose hybrid technique where Genetic algorithm is used for the selection of optimal number of cluster heads and their fitness value of chromosome to give optimal number of cluster head and minimizing the energy consumption is provided with the help of fuzzy logic approach. Finally cluster heads uses multi-hop routing based on A*(A-star) algorithm to send aggregated data to base station which additionally balance the load. Comparative study among LEACH, CHEF, LEACH-ERE, GAEEP shows that our proposed algorithm outperform in the area of total energy consumption with various rounds and network lifetime, number of node alive versus rounds and packet delivery or packet drop ratio over the rounds, also able to balances the load at cluster head.</span></p>

No abstract