A SURVEY ON BIO-INSPIRED SECURITY IN WIRELESS SENSOR NETWORKS

International Journal of Mobile Computing and Multimedia Communications, 2012

Last year’s biologically inspired systems had received a great interest. Behavior of social insects, DNA computation, artificial neural networks, evolutionary computation, and artificial immune systems are some of the interests which can be highlighted. Wireless sensor networks have no clear line of defense and no fixed infrastructure; therefore, the known security techniques used for cabled networks might not work perfectly. While wireless sensor networks, node misbehavior can cause the packet dropping, packet modification, packet misrouting, selfish node behavior, and so on. A biologically-inspired algorithm for detecting misbehaving nodes in a wireless sensor network is presented. Such an algorithm, inspired by the behavior of some social spiders from Congo, a specially their strategy to collaborate for detecting an intrusion in their web.

2013 World Congress on Nature and Biologically Inspired Computing, 2013

Exploring the symbiotic nature of biological systems can result in valuable knowledge for computer networks. Biolog ically inspired approaches to security in networks are interesting to evaluate because of the analogies between network security and survival of human body under pathogenic attacks. Wireless Sensor Network (WSN) is a network based on multiple low cost, low-energy sensor nodes connected to physical signals. The network is made up of sensor nodes and gateways, where the server nodes acquire physical world data, while the gateway forwards the data to the end-user. While the spread of viruses in wired systems has been studied in-depth, applying trust in wireless sensor network nodes is an emerging area. This paper uses machine learning techniques to first dif1"erentiate between fraudulent and good nodes in the system. Next, it derives inspiration from the human immune system to present an idea of virtual antibodies in the system, to disable the fraudulent nodes in the system.

2008

The field of wireless sensor network (WSN) is an important and challenging research area today. Advancements in sensor networks enable a wide range of environmental monitoring and object tracking applications. Secure routing in sensor networks is a difficult problem due to the resources limitations in WSN. Moreover, multihop routing in WSN is affected by new nodes constantly entering/leaving the system. Therefore, biologically inspired algorithms are reviewed and enhanced to tackle problems arise in WSN. Ant routing and human security has shown an excellent performance for sensor networks. Certain parameters like energy level, link quality, lose rate are considered while making decisions. These decisions will come up with the optimal route and also to take best action against the security attacks. In this paper, the design and initial work on biological-inspired self-organized secure autonomous routing algorithm for sensor networks are presented. The proposed bio-inspired algorithm will also meet the enhanced sensor network requirements, including energy consumption, success rate and time delay.

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2019

Wireless sensor networks (WSNs) play a pivotal role in Cyber Physical Systems (CPSs), particularly for operations such as observing the location and monitoring it. To enhance the cyber security in WSN-enabled CPSs, various researchers have proposed a various category of algorithms, inspired by biological phenomena. These algorithm works on the basis of mobility of head node (Mobile Anchor Node). However, these WSNs mobile anchor node are subject to various types of optimization like Grey wolf optimizer (GWO) and Whale optimization Algorithm (WOA). Complexity is one of the limitation of these algorithm and also it is vulnerable to damage, theft, or destruction of sensitive data, in addition to that interference in services also occur in CPSs. To prevent these cyber-attack, we proposed generic bio-inspired model ie., enhanced Grey wolf optimizer path planning called Swarm Intelligence for WSN Cyber security that addresses drawbacks of prior bio-inspired approaches. In this model WSN enabled Cyber Physical Systems use ID-Based Aggregate Signature Scheme to detect the cyber-attack and keep data integrity

2011

In multihop wireless sensor networks users or nodes are constantly entering and leaving the network. Classical techniques for network management and control are not conceived to efficiently face such challenges. New mechanisms are required, to work in a self-organized manner. The techniques found in nature promises WSN, to self-adapt the environmental changes and also self-protect itself from the malicious stuff. This paper introduces a biological inspired self-organized secure autonomous routing protocol (BIOSARP). Our proposed protocol is based on ANT Colony System (ACS) for an optimal route decision. The self-optimized routing protocol is further enhanced with artificial Immune System (HIS) inspired autonomous security mechanism. It enhances WSN in securing itself from the abnormalities and most common WSN routing attacks. NS2 based simulation analysis and results of BIOSARP are presented. The comparison of our autonomous protocol with the most recent WSN security mechanisms is further exhibited, in terms of processing time, delivery ratio and energy consumption.

The evolution of computing and computing communication capabilities has come with an evolution in security requirements. Computer intrusion detection is one aspect to computer security and an active area of research. Existing Intrusion Detection Systems (IDSs) are not sufficient, both because of their structure and because of their lack of scalability. Same as an immune system, an IDS should be distributed, made out of a number of components, each of which is in constant movement, carrying out a specific task. Underlying natural evolution, immune systems are both highly reliable and robust. This research aims at the development of a methodology to build robust, efficient, effective and highly adaptable intrusion detection systems. It rests upon the conjecture that a procedure inspired on an immune system is the key to fulfill computer intrusion detection using a multi-mobile-agent system.

Machine Learning for Computer and Cyber Security, 2019

Owing to a growing reliance on information, technology and connectivity, Cyberspace has become the lifeline and interactive place for modern life. As such, Cyber security challenges are a global phenomenon whose adverse implications are catastrophic. Cyberspace is complex and unpredictable; its global connectedness and an explosion of data increases the threat surface as cyber infrastructures become highly complex and dynamic. Managing, i.e. ensuring and assuring security in cyberspace requires inspiration from advanced complex systems. Through evolution, nature has developed natural propensities in complex systems (including animalia and plants) that enable survival through adaptation. Predation-avoidance and anti-predation techniques employed by non-extinct preys could be exploited/adopted as mechanisms for adaptation through their application in Cyber security. This chapter presents an overall review of the current state of the Cyber security landscape. In addition, it demonstrates through further review, significant trends towards bio-inspired approaches as unconventional solutions to problems in other fields. Drawing from survivable preys in nature, the chapter speculates solutions for Cyberspace and Cyber security as follows; given an old problem (Pold) with an old solutions (Sold), a new problem (Pnew) Computer and Cyber Security: Principles, Algorithm, Applications and Perspectives can be conceptualized with new partial and perhaps null solutions (Snew) in the solutions space Sold to Snew.

During the past few years, we have seen a tremendous increase in various kinds of anomalies in Wireless Sensor Network (WSN) communication. Recently, researchers have shown a lot of interest in applying biologically inspired systems for solving network intrusion detection problems. Several solutions have been proposed using Artificial Immune System (AIS), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) algorithm, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and so forth. In this paper, we propose a bioinspired solution using Negative Selection Algorithm (NSA) of the AIS for anomalies detection in WSNs. For this purpose, we implement the enhanced NSA and make a detector set that holds anomalous packets only. Then the random packets are tested and matched with the detector set and anomalies are identified. Anomalous data packets are used for further processing to identify specific anomalies. In this way, the number of wormholes, packets delayed, and packets dropped are calculated and identified. Simulations are performed on a large dataset and the results show high accuracy of the proposed algorithm in detecting anomalies. The proposed NSA is also compared with Clonal Selection Algorithm (CSA) for the same dataset. The results show significant improvement of the proposed NSA over CSA in most of the cases.

Security is the amount of resistance or safeguard from threats, this can be applied to many valuable asset. Security is the major concern for critical applications which are envisioned by wireless sensor networks (WSNs).These WSNs are vulnerable to malicious attacks and compromising them can have serious technical and economical problems. In this paper, we investigate the security related issues and challenges in wireless sensor networks. We also detect the various security threats and propose various security mechanisms for wireless sensor networks.

2015

In wireless sensor networks (WSNs), due to the restricted resources of the nodes, are highly vulnerable to attacks at all network layers; however, the so-called “wormhole attack” is particularly challenging because it resists selfprotective measures exclusively based on cryptographic protocols, this attack that not only diminishes the network capacity but also affects the reliability of information being transmitted. No emphasis was made towards the preventing the wormhole attack. In this paper a swarm-based framework that uses the security agents and security officer nodes. Preserving the legitimate packets coming from reserved route only, thereby discarding the contaminated packets has been proposed from another network.