On the race of worms and patches: modeling the spread of information in wireless sensor networks

Sensor networks are a branch of distributed ad hoc networks with a broad range of applications in surveillance and environment monitoring. In these networks, message exchanges are carried out in a multi-hop manner. Due to resource constraints, security professionals often use lightweight protocols, which do not provide adequate security. Even in the absence of constraints, designing a foolproof set of protocols and codes is almost impossible. This leaves the door open to the worms that take advantage of the vulnerabilities to propagate via exploiting the multi-hop message exchange mechanism. This issue has drawn the attention of security researchers recently. In this paper, we investigate the propagation pattern of information in wireless sensor networks based on an extended theory of epidemiology. We develop a geographical susceptible-infective model for this purpose and analytically derive the dynamics of information propagation. Compared with the previous models, ours is more realistic and is distinguished by two key factors that had been neglected before: 1) the proposed model does not purely rely on epidemic theory but rather binds it with geometrical and spatial constraints of real-world sensor networks and 2) it extends to also model the spread dynamics of conflicting information (e.g., a worm and its patch). We do extensive simulations to show the accuracy of our model and compare it with the previous ones. The findings show the common intuition that the infection source is the best location to start patching from, which is not necessarily right. We show that this depends on many factors, including the time it takes for the patch to be developed, worm/patch characteristics as well as the shape of the network.

Eri silk fibre attributes and sliver preparation

Eri silk produced by Philosamia cynthia ricini silkworm is a fibre not well-known to the silk industry, in spite of the fact that Eri silk is finer, softer, and has better mechanical and thermal properties than most animal fibres. Eri silk has a high commercial potential, as the host plants of Eri silk worms are widespread in diverse geographical locations, and the worms also have a higher degree of disease resistance than most other silk worms. Mills are often not aware of the properties of Eri for designing appropriate end products. Thus, Eri silk yarn is traditionally produced by hand spinning, and Eri silk usually ends up as material for handwoven shawls. The potential for bulk fibre processing and the development of soft luxurious novel Eri silk products is yet to be discovered. To better understand the material and its processing behaviour, Eri silk was characterised and cocoons were processed into tops through degumming, opening, and cutting filaments into different lengths, followed by a worsted spun silk processing route. Fibre properties such as fineness, crimp, strength and length at different processing stages up to combed tops were measured. The results indicate that staple Eri silk can be processed via the worsted topmaking route, using a cut length of 200 mm or 150 mm for filament sheets prepared from degummed cocoons.

Annetocin and TCTP expressions in the earthworm Eisenia fetida exposed to PAHs in artificial soil

The toxicity of sublethal polycyclic aromatic hydrocarbons (PAHs) levels in soils was assessed by testing their impact on expression of annetocin, a reproduction regulating gene, and translationally controlled tumor protein (TCTP), a tumorigenic response gene, in the earthworm Eisenia fetida cultured in artificial soil spiked with, phenanthrene (Phe), pyrene (Pyr), fluoranthene (Flu), or benzo(a)pyrene (Bap). Annetocin and TCTP were both up-regulated by 0.1 and 1.0 mg kg−1 benzo(a)pyrene and TCTP was down-regulated by 10.0 mg kg−1 phenanthrene. Weight loss and cocoon production of the worms were also analyzed. Only 10.0 mg kg−1 phenanthrene impacted earthworm weight loss significantly and no significant differences on cocoon production were observed. Our study indicated that the potential ecotoxicity of sublethal PAHs in soil should not be neglected and mRNA transcription level in earthworms was a more sensitive indicator of PAHs exposure than traditional indexes using cocoon production as endpoints and/or using the whole-organism as the test materials.

Barriers to cross-fertilization between populations of a widely dispersed Polychaete species are unlikely to have arisen through gametic compatibility arms-races

Although there are theoretical reasons to suspect that gametic incompatibility may develop readily among populations of broadcast spawning marine invertebrates, there have been very few studies documenting geographic patterns of interpopulation incompatibility for any species. To address this we determined how successfully individuals of the intertidal serpulid polychaete, Galeolaria caespitosa, can cross-fertilize within and among populations from across temperate Australia. Fertilization assays revealed asymmetrical differences between very distantly located populations from different coasts, with near-complete incompatibility between eggs from Sydney with sperm from Adelaide, but the reverse cross (Adelaide eggs, Sydney sperm) was reasonably compatible. Although that pattern was congruent with a clear difference in Cytochrome B sequences between worms on the south and east coasts of Australia, we also detected some indication of interpopulation incompatibility within the genetic grouping on east coast, between two populations separated by only 220 km. We then assessed whether commonly proposed gametic compatibility arms-races could account for these patterns. Our results suggest reduced gametic compatibility may reduce a female's maximum fertilization potential, resulting in a cost to this potential mechanism for reducing polyspermy. Consequently, the apparently rapid development of reproductive barriers here seems unlikely to have been driven by arms-races involving sexual conflict over fertilization rate.

Mutual authentication with malware protection for a RFID system

Radio Frequency Identification (RFID) system is a remote identification technology which is taking the place of barcodes to become electronic tags of an object. However, its radio transmission nature is making it vulnerable in terms of security. Recently, research proposed that an RFID tag can contain malicious code which might spread viruses, worms and other exploits to middleware and back-end systems. This paper is proposing a framework which will provide protection from malware and ensure the data privacy of a tag. The framework will use a sanitization technique with a mutual authentication in the reader level. This will ensure that any malicious code in the tag is identified. If the tag is infected by malicious code it will stop execution of the code in the RFIF system. Here shared unique parameters are used for authentication. It will be capable of protecting an RFID system from denial of service (DOS) attack, forward security and rogue reader better than existing protocols. The framework is introducing a layer concept on a smart reader to reduce coupling between different tasks. Using this framework, the RFID system will be protected from malware and also the privacy of the tag will be ensured.

The microcosmic model of worm propagation

Each year, large amounts of money and labor are spent on patching the vulnerabilities in operating systems and various popular software to prevent exploitation by worms. Modeling the propagation process can help us to devise effective strategies against those worms' spreading. This paper presents a microcosmic analysis of worm propagation procedures. Our proposed model is different from traditional methods and examines deep inside the propagation procedure among nodes in the network by concentrating on the propagation probability and time delay described by a complex matrix. Moreover, since the analysis gives a microcosmic insight into a worm's propagation, the proposed model can avoid errors that are usually concealed in the traditional macroscopic analytical models. The objectives of this paper are to address three practical aspects of preventing worm propagation: (i) where do we patch? (ii) how many nodes do we need to patch? (iii) when do we patch? We implement a series of experiments to evaluate the effects of each major component in our microcosmic model. Based on the results drawn from the experiments, for high-risk vulnerabilities, it is critical that networks reduce the number of vulnerable nodes to below 80%. We believe our microcosmic model can benefit the security industry by allowing them to save significant money in the deployment of their security patching schemes.

Discriminating DDoS attack traffic from flash crowd through packet arrival patterns

Current DDoS attacks are carried out by attack tools, worms and botnets using different packet-transmission strategies and various forms of attack packets to beat defense systems. These problems lead to defense systems requiring various detection methods in order to identify attacks. Moreover, DDoS attacks can mix their traffics during flash crowds. By doing this, the complex defense system cannot detect the attack traffic in time. In this paper, we propose a behavior based detection that can discriminate DDoS attack traffic from traffic generated by real users. By using Pearson's correlation coefficient, our comparable detection methods can extract the repeatable features of the packet arrivals. The extensive simulations were tested for the accuracy of detection. We then performed experiments with several datasets and our results affirm that the proposed method can differentiate traffic of an attack source from legitimate traffic with a quick response. We also discuss approaches to improve our proposed methods at the conclusion of this paper.

The probability model of peer-to-peer botnet propagation

Active Peer-to-Peer worms are great threat to the network security since they can propagate in automated ways and flood the Internet within a very short duration. Modeling a propagation process can help us to devise effective strategies against a worm's spread. This paper presents a study on modeling a worm's propagation probability in a P2P overlay network and proposes an optimized patch strategy for defenders. Firstly, we present a probability matrix model to construct the propagation of P2P worms. Our model involves three indispensible aspects for propagation: infected state, vulnerability distribution and patch strategy. Based on a fully connected graph, our comprehensive model is highly suited for real world cases like Code Red II. Finally, by inspecting the propagation procedure, we propose four basic tactics for defense of P2P botnets. The rationale is exposed by our simulated experiments and the results show these tactics are of effective and have considerable worth in being applied in real-world networks.

Effects of social characters in viral propagation seeding strategies in online social networks

Online social networks have not only become a point of aggregation and exchange of information, they have so radically rooted into our everyday behaviors that they have become the target of important network attacks. We have seen an increasing trend in Sybil based activity, such as in personification, fake profiling and attempts to maliciously subvert the community stability in order to illegally create benefits for some individuals, such as online voting, and also from more classic informatics assaults using specifically mutated worms. Not only these attacks, in the latest months, we have seen an increase in spam activities on social networks such as Facebook and RenRen, and most importantly, the first attempts at propagating worms within these communities. What differentiates these attacks from normal network attacks, is that compared to anonymous and stealthy activities, or by commonly untrusted emails, social networks regain the ability to propagate within consentient users, who willingly accept to partake. In this paper, we will demonstrate the effects of influential nodes against non-influential nodes through in simulated scenarios and provide an overview and analysis of the outcomes.

Distributed denial of service (DDoS) detection by traffic pattern analysis

In this paper, we propose a behavior-based detection that can discriminate Distributed Denial of Service (DDoS) attack traffic from legitimated traffic regardless to various types of the attack packets and methods. Current DDoS attacks are carried out by attack tools, worms and botnets using different packet-transmission rates and packet forms to beat defense systems. These various attack strategies lead to defense systems requiring various detection methods in order to identify the attacks. Moreover, DDoS attacks can craft the traffics like flash crowd events and fly under the radar through the victim. We notice that DDoS attacks have features of repeatable patterns which are different from legitimate flash crowd traffics. In this paper, we propose a comparable detection methods based on the Pearson’s correlation coefficient. Our methods can extract the repeatable features from the packet arrivals in the DDoS traffics but not in flash crowd traffics. The extensive simulations were tested for the optimization of the detection methods. We then performed experiments with several datasets and our results affirm that the proposed methods can differentiate DDoS attacks from legitimate traffics.

Expansion of congested railway capacity using triple-track line operation based on hourly passenger demand

This paper proposes a method of improving level of service in congested urban railways by means of a triple-track line operation for a highly dense urban area with special travel demand characteristics. Where the future travel demand forecasts show sluggish growth or no growth at all, there is little to no incentives for heavy railway investments like quadruple-track extension and construction of new railway routes to alleviate current railway congestion problems. In such a situation, triple-track line operation can be the best alternative due to its moderate investment cost and ease in land acquisition for just an additional single track along the existing tracks. Our simulation investigation in one of the congested railway lines in Tokyo showed that triple track line operation increases railway capacity by 26% and shortens travel time by 38% in peak direction during morning peak hours. These results are encouraging and are useful for removing current railways problems in Tokyo and in similar urban situations elsewhere.

Google hacking defence based on honey pages

 Many web servers contain some dangerous pages (we name them eigenpages) that can indicate their vulnerabilities. Therefore, some worms such as Santy locate their targets by searching for these eigenpages in search engines with well-crafted queries. In this paper, we focus on the modeling and containment of these special worms targeting web applications. We propose a containment system based on honey pots. We make search engines randomly insert a few honey pages that will induce visitors to the pre-established honey pots among the search results for the arriving queries. And then infectious can be detected and reported to the search engines when their malicious scans hit the honey pots. We find that the Santy worm can be well stopped by inserting no more than two honey pages in every one hundred search results. We also solve the challenging issue to dynamically generate matching honey pages for those dynamically arriving queries. Finally, a prototype is implemented to prove the technical feasibility of this system. © 2013 by CESER Publications.

Synthesis and mechanistic insights of macromolecular assemblies from ABA triblock copolymer blends

Macromolecular assembly of block copolymers into numerous nanostructures resembles self-organization of proteins and cellular components found in nature. In order to mimic nature’s assemblies either to cure a disease or construct functional devices, the organization principles underpinning the emergence of complex shapes need to be understood. In the same vein, this study aimed at understanding morphology evolution in a triblock copolymer blend in aqueous solution. An ABA type amphiphilic triblock copolymer (polystyrene-b-polyethylene oxide-b-polystyrene, PS-b-PEO-b-PS) was synthesized at different compositions via atom transfer radical polymerization (ATRP) and self-assembly behavior of a binary mixture in aqueous solution was studied. Block copolymers that form worms and vesicles in its pristine state was shown to form complex morphologies such as fused rings, “jellyfish”, toroid vesicles, large compound vesicles and large lamellae after blending. The tendency of vesicle-forming block copolymer to form bilayers may be responsible for triggering complex morphologies when mixed with a worm or micelle-forming polymer. In other words, the interplay between curvature effects produced by two distinct polymers with different hydrophobic block lengths results in complex morphologies due to chain segregation within the nanostructure.