Existing Detection Schemes Research Articles

An Efficient Energy based Detection of Malicious Node in Mobile Wireless Sensor Networks

Mobile wireless sensor networks (MWSN) are composed of a large number of wireless sensors and they require a careful consumption of available energy to prolong the life of the network. From the security point of view, existing detection schemes consumes node energy and thus reduces the life time of the network. This paper focuses on energy based scheme for detecting the malicious node in the forward routing path. This detection scheme suits any standard routing protocol. The forward route selection path is identified by using dynamic source routing protocol. The proposed scheme is simulated in glomosim and evaluated using packet throughput, percentage of byte overheads, energy consumption, and the accuracy of detection. The network with moderate mobility is used and the proposed scheme consumes 20 % of node energy.

Research on Selective Forwarding Attack Detection Scheme in Wireless Sensor Networks

Selective forwarding attacks in wireless sensor networks may corrupt some mission critical applications such as military surveillance and critical facilities monitoring. They are very difficult to be detected and distinguished from normal packet drops in wireless sensor networks. We propose an improved sequential mesh test based detection scheme in this paper. The scheme extracts a small quantity of samples to run the test, instead of regulating the total times of test in advance. We show through experiments that our scheme can provide higher detection accurate rate and lower false alarm rate than the existing detection schemes. Meanwhile, less communication and computation power are required to detect the selective forwarding attacks.

Single Hop Detection of Node Clone Attacks in Mobile Wireless Sensor Networks

Wireless sensor networks (WSNs) are often deployed in hostile and unattended environments; they are vulnerable to physical capture and compromise. In a node replication attack or a node clone attack, an adversary physically captures a sensor node, extracts cryptographic secrets from the node, and distributes a large number of replicas of captured node throughout the network, in order to launch a variety of insider attacks. Existing node clone attack detection schemes are mainly focused on stationary sensor networks. Also most existing detection schemes make unrealistic assumptions on the ability of replicas. In this paper, we propose a novel node clone attack detection protocol, namely the Single Hop Detection (SHD) protocol, which is fully distributed, highly robust against node colluding, specifically designed for mobile WSNs. We show analytically under popular mobility models that our protocol provides effective and robust node clone attack detection capability.

An Entropy-Based Approach to Detecting Covert Timing Channels

The detection of covert timing channels is of increasing interest in light of recent exploits of covert timing channels over the Internet. However, due to the high variation in legitimate network traffic, detecting covert timing channels is a challenging task. Existing detection schemes are ineffective at detecting most of the covert timing channels known to the security community. In this paper, we introduce a new entropy-based approach to detecting various covert timing channels. Our new approach is based on the observation that the creation of a covert timing channel has certain effects on the entropy of the original process, and hence, a change in the entropy of a process provides a critical clue for covert timing channel detection. Exploiting this observation, we investigate the use of entropy and conditional entropy in detecting covert timing channels. Our experimental results show that our entropy-based approach is sensitive to the current covert timing channels and is capable of detecting them in an accurate manner.

Sybil attack detection based on signature vectors in VANETs

Sybil attack is one of the serious threats in vehicular ad hoc networks (VANETs) because drivers may receive wrong information, which could lead to injury the lives of the drivers and passengers, when they are under Sybil attack. This paper, therefore, presents a novel solution named Sybil attack detection based on signature vectors (SADSIV) in VANETs. Each node gathers the digital signatures in their moving; then our algorithm detects Sybil attack by analysing and comparing vehicle nodes' signature vectors independently under the condition of inadequate infrastructures. We improve the feasibility of our approach through the limited infrastructures at the early deployment stages of VANETs. In addition, the independency and feasibility of our algorithm are more robust than the existing solutions which rely on collaboration of neighbouring nodes. Simulation results show that our method outperforms the existing detection schemes in terms of robustness, detection rate and lower system requirements.

Robust Channel Estimation and Detection for Single-Carrier and Multicarrier Block Transmission Systems

Block transmission techniques, including single-carrier (SC) and multicarrier (MC) communication techniques, have received much research interest recently for their better ability to handle the intersymbol interference problem than continuous transmission. Numerous detection schemes for SC and MC communication systems have been proposed. While these schemes may be derived from different principles, they usually rely on some initial estimate of the communication channel and/or the covariance matrix of the received signal. However, such estimates usually contain inherent estimation errors to which most existing detection schemes are known to be sensitive. In this paper, we develop robust estimation and detection schemes that explicitly account for channel and covariance matrix estimation errors by optimizing the worst-case performance over properly selected bounded uncertainty sets. Although the prior channel and covariance matrix-estimation errors are generally not bounded, we show that it is beneficial to refine the channel and covariance matrix estimates over properly chosen bounded uncertainty sets centered on the prior channel and covariance matrix estimates. Numerical results show that an improved performance is achieved by using the proposed robust approaches over the ones that ignore the prior estimation errors.

Collaborative Defense Mechanism Using Statistical Detection Method against DDoS Attacks

Distributed Denial-of-Service attack (DDoS) is one of the most outstanding menaces on the Internet. A DDoS attack generally attempts to overwhelm the victim in order to deny their services to legitimate users. A number of approaches have been proposed for defending against DDoS attacks accurately in real time. However, existing schemes have limits in terms of detection accuracy and delay if the IDRS (Intrusion Detection and Response System) deployed only at a specific location detects and responds against attacks. As in this case, it is not able to catch the characteristic of the attack which is distributed in large-scale. Moreover, the existing detection schemes have vulnerabilities to intellectual DDoS attacks which are able to avoid its detection threshold or delay its detection time. This paper suggests the effective DDoS defense system which uses the collaborative scheme among distributed IDRSs located in the vicinity of the attack source or victim network. In proposed scheme, both victim and source-end IDRS work synergistically to identify the attack and avoid false alarm rate up to great extent. Additionally, we propose the duplicate detection window scheme to detect various attacks dynamics which increase the detection threshold gradually in early stage. The proposed scheme can effectively detect and respond against these diverse DDoS attack dynamics.

Detection of the Disease-Associated Isoform of the Prion Protein in Formalin-Fixed Tissues by Western Blot

Clinical signs of prion disease are not specific and include a variety of differential diagnoses. Serological tests and nucleic acid-based detection methods are not applicable to prion-disease-agent detection because of the unusual nature of the infectious agent. Prion-disease diagnosis is primarily conducted by means of immunodetection of the infectious agent, typically by at least 2 distinct procedures with immunohistochemistry and Western blot being the most informative. These approaches differ in the need for formalin-fixed and frozen or fresh tissue respectively. This work describes a method for the detection of the disease-associated isoform of the prion protein by Western blot using formalin-fixed tissues. The approach requires only minimal modification of existing Western-blot procedures and could readily be incorporated into existing detection schemes for confirmatory purposes when fresh or frozen tissues are unavailable.

A digital coherent receiver suitable for land-mobile satellite communications

Describes an advanced coherent demodulation technique suitable for land-mobile satellite communications. The proposed technique features a combined narrow/wide band dual open loop (DOL) carrier phase estimator, which effectively enables the coherent receiver to track fast phase fluctuations caused by fading, without degradation in phase slip characteristics. Additionally, an open loop phase estimator has inherent quick recovery performance. Its bit error rate (BER) performance is shown to be superior to that for existing detection schemes, achieving a 10/sup -2/ BER at 6.3 dB E/sub b//N/sub 0/ (0.9 dB greater than the theoretical E/sub b//N/sub 0/ condition for perfect carrier phase tracking) for QPSK over a Rician fading channel with the 10 dB Rician factor and the 1/16 baud rate fading pitch. The paper also describes a quick bit timing recovery scheme, with interpolation, featuring an open loop structure. Further, it presents an experimental digital modem developed through the use of digital signal processors.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>