Detection of sinkhole attack in wireless sensor networks

Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should be considered that the sensor nodes are mostly spread out in open areas and of weak computation and battery power. In order to detect the intruder in a sinkhole attack this paper suggests an algorithm which firstly finds a group of suspected nodes by analyzing the consistency of data. Then, the intruder is recognized efficiently in the group by checking the network flow information. The proposed algorithm's performance has been evaluated by using numerical analysis and simulations. Therefore, accuracy and efficiency of algorithm would be verified.

Parametric differences between a real-world distributed denial-of-service attack and a flash event

Distributed Denial-of-Service (DDoS) attacks continue to be one of the most pernicious threats to the delivery of services over the Internet. Not only are DDoS attacks present in many guises, they are also continuously evolving as new vulnerabilities are exploited. Hence accurate detection of these attacks still remains a challenging problem and a necessity for ensuring high-end network security. An intrinsic challenge in addressing this problem is to effectively distinguish these Denial-of-Service attacks from similar looking Flash Events (FEs) created by legitimate clients. A considerable overlap between the general characteristics of FEs and DDoS attacks makes it difficult to precisely separate these two classes of Internet activity. In this paper we propose parameters which can be used to explicitly distinguish FEs from DDoS attacks and analyse two real-world publicly available datasets to validate our proposal. Our analysis shows that even though FEs appear very similar to DDoS attacks, there are several subtle dissimilarities which can be exploited to separate these two classes of events.

Modeling and detection of complex attacks

A complex attack is a sequence of temporally and spatially separated legal and illegal actions each of which can be detected by various IDS but as a whole they constitute a powerful attack. IDS fall short of detecting and modeling complex attacks therefore new methods are required. This paper presents a formal methodology for modeling and detection of complex attacks in three phases: (1) we extend basic attack tree (AT) approach to capture temporal dependencies between components and expiration of an attack, (2) using enhanced AT we build a tree automaton which accepts a sequence of actions from input message streams from various sources if there is a traversal of an AT from leaves to root, and (3) we show how to construct an enhanced parallel automaton that has each tree automaton as a subroutine. We use simulation to test our methods, and provide a case study of representing attacks in WLANs.

A facile chemical screening method for the detection of stress corrosion cracking in 9 carat gold alloys

Stress corrosion cracking (SCC) is a well known form of environmental attack in low carat gold jewellery. It is desirable to have a quick, easy and cost effective way to detect SCC in alloys and prevent them from being used and later failing in their application. A facile chemical method to investigate SCC of 9 carat gold alloys is demonstrated. It involves a simple application of tensile stress to a wire sample in a corrosive environment such as 1–10 % FeCl3 which induces failure in less than 5 minutes. In this study three quaternary (Au, Ag, Cu and Zn) 9 carat gold alloy compositions were investigated for their resistance to SCC and the relationship between time to failure and processing conditions is studied. It is envisaged that the use of such a rapid and facile screening procedure at the production stage may readily identify alloy treatments that produce jewellery that will be susceptible to SCC in its lifetime.

Detection of elevated protein modification in human cerebellum in alcoholic cerebellar degeneration

Modification of proteins by reactive ethanol metabolites has been known for some time to occur in the liver, the main site of ethanol metabolism. In more recent studies of laboratory animals, similar modifications have been detected in organs with lesser ability to metabolize ethanol, such as skeletal and cardiac muscle and brain. Such modification may alter protein function or form a neoantigen, making it a target for immune attack. We now report an analysis of protein modification derived from ethanol metabolites in human brain tissue by ELISA using adduct-specific antibodies. We obtained autopsy cerebellum samples from 10 alcoholic cerebellar degeneration cases and 10 matched controls under informed written consent from the next of kin and clearance from the UQ Human Ethics Committee. Elevated levels of protein modifications derived from acetaldehyde (unreduced-acetaldehyde and acetaldehyde-advanced glycation end-product adducts), from malondialdehyde (malondialdehyde adducts) and from combined adducts (malondialdehydeacetaldehyde (MAA) adducts) were detected in alcoholic cerebellar degeneration samples when compared to controls. Other adduct types found in liver samples, such as reduced-acetaldehyde and those derived from hydroxyethyl radicals, were not detected in brain samples. This may reflect the different routes of ethanol metabolism in the two tissues. This is the first report of elevated protein modification in alcoholic cerebellar degeneration, and suggests that such modification may play a role in the pathogenesis of brain injury. Supported by NIAAA under grant NIH AA12404 and the NHMRC (Australia) under grant #981723.

Detection of elevated protein modification in alcoholic cerebellar degeneration

Modification of proteins by reactive ethanol metabolites has been known, for some time, to occur in the liver, the main site of ethanol metabolism. More recently, similar modifi cation has been detected in organs with lesser ability to metabolise ethanol such as skeletal and cardiac muscle, and brain. Such modifi cation may alter protein function or form a neoantigen, making it a target for immune attack.