Energy Efficient and Secure Wireless Sensor Networks Design

Wireless Sensor Networks (WSNs) are emerging technologies that have the ability to sense, process, communicate, and transmit information to a destination, and they are expected to have significant impact on the efficiency of many applications in various fields. The resource constraint such as limited battery power, is the greatest challenge in WSNs design as it affects the lifetime and performance of the network. An energy efficient, secure, and trustworthy system is vital when a WSN involves highly sensitive information. Thus, it is critical to design mechanisms that are energy efficient and secure while at the same time maintaining the desired level of quality of service. Inspired by these challenges, this dissertation is dedicated to exploiting optimization and game theoretic approaches/solutions to handle several important issues in WSN communication, including energy efficiency, latency, congestion, dynamic traffic load, and security. We present several novel mechanisms to improve the security and energy efficiency of WSNs. Two new schemes are proposed for the network layer stack to achieve the following: (a) to enhance energy efficiency through optimized sleep intervals, that also considers the underlying dynamic traffic load and (b) to develop the routing protocol in order to handle wasted energy, congestion, and clustering. We also propose efficient routing and energy-efficient clustering algorithms based on optimization and game theory. Furthermore, we propose a dynamic game theoretic framework (i.e., hyper defense) to analyze the interactions between attacker and defender as a non-cooperative security game that considers the resource limitation. All the proposed schemes are validated by extensive experimental analyses, obtained by running simulations depicting various situations in WSNs in order to represent real-world scenarios as realistically as possible. The results show that the proposed schemes achieve high performance in different terms, such as network lifetime, compared with the state-of-the-art schemes

Integrating Blockchain with Artificial Intelligence to Secure IoT Networks: Future Trends

Recently, the Internet of Things (IoT) has gained tremendous popularity in several realms such as smart cities, healthcare, industrial automation, etc. IoT networks are increasing rapidly, containing heterogeneous devices that offer easy and user-friendly services via the internet. With the big shift to IoT technology, the security of IoT networks has become a primary concern, especially with the lack of intrinsic security mechanisms regarding the limited capabilities of IoT devices. Therefore, many studies have been interested in enhancing the security of IoT networks. IoT networks need a scalable, decentralized, and adaptive defense system. Although the area of development provides advanced security solutions using AI and Blockchain, there is no systematic and comprehensive study talking about the convergence between AI and Blockchain to secure IoT networks. In this paper, we focus on reviewing and comparing recent studies that have been proposed for detecting cybersecurity attacks in IoT environments. This paper address three research questions and highlights the research gaps and future directions. This paper aims to increase the knowledge base for enhancing IoT security, recommend future research, and suggest directions for future research

A Game Theoretic Approach To Model Cyber Attack And Defense Strategies

Most of the cybersecurity research focus on either presenting a specific vulnerability %or hacking technique, or proposing a specific defense algorithm to defend against a well-defined attack scheme. Although such cybersecurity research is important, few have paid attention to the dynamic interactions between attackers and defenders, where both sides are intelligent and will dynamically change their attack or defense strategies in order to gain the upper hand over their opponents. This \u27cyberwar\u27 phenomenon exists among most cybersecurity incidents in the real world, which warrants special research and analysis. In this paper, we propose a dynamic game theoretic framework (i.e., hyper defense) to analyze the interactions between the attacker and the defender as a non-cooperative security game. The key idea is to model attackers/defenders to have multiple levels of attack/defense strategies that are different in terms of effectiveness, strategy costs, and attack gains/damages. Each player adjusts his strategy based on the strategy\u27s cost, potential attack gain/damage, and effectiveness in anticipating of the opponent\u27s strategy. We study the achievable Nash equilibrium for the attacker-defender security game where the players employ an efficient strategy according to the obtained equilibrium. Furthermore, we present case studies of three different types of network attacks and put forth how our hyper defense system can successfully model them. Simulation results show that the proposed game theoretical system achieves a better performance compared to two other fixed-strategy defense systems

A Game Theoretic Approach For Energy-Efficient Clustering In Wireless Sensor Networks

Selection of clusterheads using energy efficient clustering algorithms in a wireless sensor network (WSN) is very crucial as it affects the lifetime and performance of the network. As clusterheads and cluster members (i.e., non-clusterhead nodes) have a different energy consumption rates, it is necessary that all nodes resort to some rational scheme such that the connectivity and proper functioning of the network is not compromised. In this paper, we propose a Cost and Payment-based clustering Algorithm (CoPA) for achieving energy efficiency in wireless sensor networks under a game theoretical framework. The analysis is based on a non-cooperative, repeated general sum game, where each node behaves selfishly in order to maximize its lifespan (payoff). We demonstrate that the correlated equilibrium is a practical solution for clusterhead selection, which provides better performance than the Nash Equilibria. Correlated equilibrium provides a balance between the fully cooperative solution and the fully non-cooperative solution in terms of implementation overhead. CoPA produces a balanced distribution of responsibilities and energy consumption between the sensor nodes as well as maximizes the minimum payoff for every node. Results show that CoPA achieves better performance in terms of network lifetime and throughput compared to other popular clustering techniques

Parallel Active Dictionary Attack On Wpa2-Psk Wi-Fi Networks

Wi-Fi network offers an inexpensive and convenient way to access the Internet. It becomes even more important nowadays as we are moving from the traditional computer age to the current mobile devices and Internet-of-Things age. Wi-Fi Protected Access II (WPA2) - Pre-shared key (PSK) is the current security standard used to protect small 802.11 wireless networks. Most of the available dictionary password-guessing attacks on WPA2-PSK are based on capturing the four-way handshaking frames between an authorized wireless client and the Access Point (AP). These attacks will fail if an attacker is unable to capture the four-way handshaking frames of a legitimate client. An attacker also can apply an active dictionary attack by sending a pass-phrase to the AP and waiting for the response. However, this attack approach could only achieve a low attack intensity of testing a few pass-phrases per minute. In this paper, we develop a new scheme to speed up the active pass-phrase guessing trials intensity based on two novel ideas: First, the scheme mimics multiple Wi-Fi clients connecting to the AP at the same time-each emulated Wi-Fi client has its own spoofed MAC address; Second, each emulated Wi-Fi client could try many pass-phrases using a single wireless session without the need to pass the 802.11 authentication and association stages for every pass-phrase guess. We have developed a working prototype and our experiments show that the proposed scheme can improve active dictionary pass-phrase guessing speed by 100-fold compared to the traditional single client attack

An Evolutionary Routing Game For Energy Balance In Wireless Sensor Networks

In a Wireless Sensor Network (WSN), the sensor nodes rely on each other to forward packets from the origin to the base station via some routes. Computation of a desirable route is challenging. Some of the routes can be better than others, which might lead to an imbalance in contention for disparate routes as one route may be congested more frequently or exhausted quicker than the others. Since each node self-interest is to save its own energy due to the limited energy resource, it can lead to congestion resulting in higher delays and additional packet collisions– which may eventually result in quicker energy depletion along such routes and shorten the lifespan of the network. In this paper, we analyze this issue from a game theoretic perspective and model the route selection problem in a WSN as an evolutionary anti-coordination routing game. We derive the evolutionary stable strategy (ESS) of the game and prove that the derived incumbent strategy cannot be invaded by a greedy strategy i.e., mutant strategy. Furthermore, we derive the replicator dynamic of the proposed game in order to show the behavior of the sensors in selecting the paths. The mechanism of the replicator dynamics also shows how the nodes learn from their strategic interactions and modify their strategies at every stage of the game until reaching a stable strategy (ESS). Furthermore, the evolutionary game can be implemented in a distributed manner. Finally, in order to achieve increased lifetime, we analyze the fairness of the proposed equilibrium solution under the selfish node behavior by utilizing Jain\u27s fairness index. The results show that the proposed system is successful in converging the strategy choices to ESS even under dynamic conditions

Towards Trustworthy Collaboration In Spectrum Sensing For Ad Hoc Cognitive Radio Networks

Cognitive radio networks (CRN) make use of dynamic spectrum access to communicate opportunistically in frequency bands otherwise licensed to incumbent primary users such as TV broadcast. To prevent interference to primary users it is vital for secondary users in CRNs to conduct accurate spectrum sensing, which is especially challenging when the transmission range of primary users is shorter compared to the size of the CRN. This task becomes even more challenging in the presence of malicious secondary users that launch spectrum sensing data falsification (SSDF) attacks by providing false spectrum reports. Existing solutions to detect such malicious behaviors cannot be utilized in scenarios where the transmission range of primary users is limited within a small sub-region of the CRN. In this paper, we present a framework for trustworthy collaboration in spectrum sensing for ad hoc CRNs. This framework incorporates a semi-supervised spatio-spectral anomaly/outlier detection system and a reputation system, both designed to detect byzantine attacks in the form of SSDF from malicious nodes within the CRN. The framework guarantees protection of incumbent primary users’ communication rights while at the same time making optimal use of the spectrum when it is not used by primary users. Simulation carried out under typical network conditions and attack scenarios shows that our proposed framework can achieve spectrum decision accuracy up to 99.3 % and detect malicious nodes up to 98 % of the time

Ee-Mac: Energy Efficient Sensor Mac Layer Protocol

Energy efficiency is of utmost importance for wireless sensor networks deployed without any possibility of battery replenishments. Thus, design of energy efficient algorithms and protocols must consider resource constraints while maintaining the desired level of QoS. In this paper, we present EE-MAC, an Energy Efficient medium access control (MAC) protocol for distributed wireless sensor networks. EE-MAC achieves a low-duty-cycle and hence low energy consumption through optimized sleep intervals while transitioning between sleep and active states. We consider a weighted linear combination of delay and energy saving as the performance metrics and through extensive simulations, we observe reduced energy consumption at the cost of increased delay. EE-MAC also improves the delay performance for fixed number of nodes compared to S-MAC. © 2013 IEEE

Adp: An Adaptive Feedback Approach For Energy-Efficient Wireless Sensor Networks

A broad range of applications has led to various wireless sensor networks (WSNs) with different design considerations. Limited battery power is one of the most challenging aspects of WSN protocol design, and, therefore, energy efficiency has long been the focus of research. One of the most common approaches for energy conservation is to alternate each sensor node between sleep and wake-up states. In this paper, we propose ADP, an adaptive energy efficient approach that meets the requirement of low energy consumption and, at the same time, considers the underlying dynamic traffic load. ADP enhances energy efficiency by dynamically adjusting sensor nodes\u27 sleep and wake-up cycles. ADP utilizes a cost function intended to strike a balance between the conflicting goals of conserving energy (waking up as rarely as possible) and at the same time minimizing sensed events\u27 reporting latency (waking up as frequently as possible). It also incorporates a feedback mechanism that constantly monitors residual energy level and the importance of the event to be reported, as well as predicts the next sensing event occurrence time. Simulation experiments with different traffic loads have shown that ADP improves energy efficiency while keeping latency low