Survey on Security Management of Multiple Spoofing Attackers in Wireless Networks

Wireless spoofing attacks are simple to introduce and can importantly impact the performance of networks. In this paper, we propose to use spatial information a physical property related to every node, complex to mispresent and self reliant on cryptography, as the initializing for detecting spoofing attacks determining the number of attackers when multiple opponent masquerading as the same node identity and localizing multiple adversaries We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. For determining the number of attackers we are using cluster based mechanism. To localize the positions of multiple attackers, we have developed an integrated detection and localization system. The generated localization results with a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries. As the wireless networks are easily susceptible for various types of spoofing attacks, basically this paper focuses on Identity-based spoofing attacks and the enhanced and efficient techniques to secure from such attacks

Detection and Localization of Multiple Spoofing using GADE and IDOL in WSN

Abstract Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. Spatial information, a physical property associated with each node, that is hard to falsify, and not reliant on cryptography is used, as the basis for 1) detecting spoofing attacks; 2) determining the number of attackers when multiple adversaries masquerading as the same node identity; and 3) localizing multiple adversaries. Thus received signal strength (RSS) is inherited from wireless nodes to detect the spoofing attacks. Cluster-based mechanisms are developed to determine the number of attackers. In addition, an integrated detection and localization system is developed that can localize the positions of multiple attackers. Thus this detection and localization results provide strong evidence in detecting multiple adversaries

Cluster Based Intrusion Detection Technique for Wireless Networks

Wireless networks are vulnerable to spoofing attacks, which allows for many other forms of attacks on the networks. Although th e identity of a node can be verified through cryptographic authentication, authentication is not always possible because it requires key management and additional infrastructural overhead. In this paper we propose a method for both detect ing spoofing attacks, as well as locating the positions of adversaries performing the attacks. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. We then formulate the problem of determin ing the number of attackers as a multiclass detection problem. Cluster - based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve t he accuracy of determining the number of attackers. In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two test beds using both an 802.11 ( Wi - Fi ) network and an 802.15.4 network in two real office buildings. Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localizatio n results using a represen tative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries

A Study of Attack Detection and Localization Scheme Using Enhanced Hash Technique

Security plays an vital role in wireless sensor networks. The nodes are deployed in the physical environment. Hackers may easily access the data. In order to provide security, The Advanced Encryption Standard (AES) algorithm has developed into an option for various security services. Sensor nodes collect the data from the environment and send to sink. But attackers corrupt data while transmitting therefore data security is main concern of wireless sensor network (WSN). Owing to the increasing popularity of wireless sensor networks, they have become attractive targets for malicious attacks. Due to the ad-hoc nature and openness of wireless sensor networks, they are susceptible to the identity based attack. In this paper, we study on a process of named Attack Detection and Localization Scheme to detect and localize the identity based attacks. An improved algorithm for hashing has been proposed. We named it as Effective Hashing Technique (EHT).It generates the Hash keys to differentiate an attacker from a normal node and to reduce the occurrences of any false positives or negatives. Also, our localization algorithm efficiently finds out the position estimates for the nodes

A New MAC Address Spoofing Detection Technique Based on Random Forests

Media access control (MAC) addresses in wireless networks can be trivially spoofed using off-the-shelf devices. The aim of this research is to detect MAC address spoofing in wireless networks using a hard-to-spoof measurement that is correlated to the location of the wireless device, namely the received signal strength (RSS). We developed a passive solution that does not require modification for standards or protocols. The solution was tested in a live test-bed (i.e., a wireless local area network with the aid of two air monitors acting as sensors) and achieved 99.77%, 93.16% and 88.38% accuracy when the attacker is 8–13 m, 4–8 m and less than 4 m away from the victim device, respectively. We implemented three previous methods on the same test-bed and found that our solution outperforms existing solutions. Our solution is based on an ensemble method known as random forests.https://doi.org/10.3390/s1603028

A Study of IEEE 802.15.4 Security Framework for Wireless Body Area Network

A Wireless Body Area Network (WBAN) is a collection of low-power and lightweight wireless sensor nodes that are used to monitor the human body functions and the surrounding environment. It supports a number of innovative and interesting applications, including ubiquitous healthcare and Consumer Electronics (CE) applications. Since WBAN nodes are used to collect sensitive (life-critical) information and may operate in hostile environments, they require strict security mechanisms to prevent malicious interaction with the system. In this paper, we first highlight major security requirements and Denial of Service (DoS) attacks in WBAN at Physical, Medium Access Control (MAC), Network, and Transport layers. Then we discuss the IEEE 802.15.4 security framework and identify the security vulnerabilities and major attacks in the context of WBAN. Different types of attacks on the Contention Access Period (CAP) and Contention Free Period (CFP) parts of the superframe are analyzed and discussed. It is observed that a smart attacker can successfully corrupt an increasing number of GTS slots in the CFP period and can considerably affect the Quality of Service (QoS) in WBAN (since most of the data is carried in CFP period). As we increase the number of smart attackers the corrupted GTS slots are eventually increased, which prevents the legitimate nodes to utilize the bandwidth efficiently. This means that the direct adaptation of IEEE 802.15.4 security framework for WBAN is not totally secure for certain WBAN applications. New solutions are required to integrate high level security in WBAN.Comment: 14 pages, 7 figures, 2 table

A Survey on Spoofing and Selective Forwarding Attacks on Zigbee based WSN

The main focus of WSN is to gather data from the physical world. It is often deployed for sensing, processing as well as disseminating information of the targeted physical environments. The main objective of the WSN is to collect data from the target environment using sensors as well as transmit those data to the desired place of choice. In order to achieve an efficient performance, WSN should have efficient as well as reliable networking protocols. The most popular technology behind WSN is Zigbee. In this paper a pilot study is done on important security issues on spoofing and selective forwarding attack on Zigbee based WSN. This paper identifies the security vulnerabilities of Zigbee network and gaps in the existing methodologies to address the security issues and will help the future researchers to narrow down their research in WSN.Keywords: Zigbee, WSN, Protocol Stack, Spoofing and Selective Forwarding

Security of GPS/INS based On-road Location Tracking Systems

Location information is critical to a wide-variety of navigation and tracking applications. Today, GPS is the de-facto outdoor localization system but has been shown to be vulnerable to signal spoofing attacks. Inertial Navigation Systems (INS) are emerging as a popular complementary system, especially in road transportation systems as they enable improved navigation and tracking as well as offer resilience to wireless signals spoofing, and jamming attacks. In this paper, we evaluate the security guarantees of INS-aided GPS tracking and navigation for road transportation systems. We consider an adversary required to travel from a source location to a destination, and monitored by a INS-aided GPS system. The goal of the adversary is to travel to alternate locations without being detected. We developed and evaluated algorithms that achieve such goal, providing the adversary significant latitude. Our algorithms build a graph model for a given road network and enable us to derive potential destinations an attacker can reach without raising alarms even with the INS-aided GPS tracking and navigation system. The algorithms render the gyroscope and accelerometer sensors useless as they generate road trajectories indistinguishable from plausible paths (both in terms of turn angles and roads curvature). We also designed, built, and demonstrated that the magnetometer can be actively spoofed using a combination of carefully controlled coils. We implemented and evaluated the impact of the attack using both real-world and simulated driving traces in more than 10 cities located around the world. Our evaluations show that it is possible for an attacker to reach destinations that are as far as 30 km away from the true destination without being detected. We also show that it is possible for the adversary to reach almost 60-80% of possible points within the target region in some cities