Distinct IP Research Articles

Fourth-Order Algebraic Diagrammatic Construction for Electron Detachment and Attachment: The IP- and EA-ADC(4) Methods.

We present a non-Dyson fourth-order algebraic diagrammatic construction formulation of the electron propagator, featuring the distinct IP- and EA-ADC(4) schemes for the treatment of ionization and electron attachment processes. The algebraic expressions have been derived automatically using the intermediate state representation approach and implemented in the Q-Chem quantum-chemical program package. The performance of the novel methods is assessed with respect to high-level reference data for ionization potentials and electron affinities of closed- and open-shell systems. While only minor improvements over the corresponding third-order methods are observed for one-hole ionization and one-particle electron attachment processes from closed-shell systems (MAEIP-ADC(4) = 0.27 eV and MAEEA-ADC(4) = 0.05 eV), a significantly enhanced performance is found in case of open-shell reference states (MAEIP-ADC(4) = 0.11 eV and MAEEA-ADC(4) = 0.02 eV). A particularly appealing feature of the novel methods is their accurate treatment of satellite transitions. For closed-shell reference states, we obtain accuracies of MAEIP-ADC(4) = 0.81 eV and MAEEA-ADC(4) = 0.27 eV, while in case of open-shell reference states, mean absolute errors of MAEIP-ADC(4) = 0.15 eV and MAEEA-ADC(4) = 0.27 eV are found.

Evaluation Method of IP Geolocation Database Based on City Delay Characteristics

Despite the widespread use of IP geolocation databases, a robust and precise method for evaluating their accuracy remains elusive. This study presents a novel algorithm designed to assess the reliability of IP geolocation databases, leveraging the congruence of delay distributions across network segments and cities. We developed a fusion reference database, termed CDCDB, to facilitate the evaluation of commercial IP geolocation databases. Remarkably, CDCDB achieves an average positioning accuracy at the city level of 94%, coupled with a city coverage of 99.99%. This allows for an effective and comprehensive evaluation of IP geolocation databases. When compared to IPUU, CDCDB demonstrates an increase in the number of network segments by 18.7%, an increase in the number of high-quality network segments by 13.2%, and an enhancement in the coverage of city-level network segments by 20.92%. The evaluation outcomes reveal that the reliability of IP geolocation databases is not uniform across different cities. Moreover, distinct IP geolocation databases display varying preferences for cities. Consequently, we advise online service providers to select suitable IP geolocation databases based on the cities they cater to, as this could significantly enhance service quality.

Long-lasting sequences of BGP updates

The Border Gateway Protocol (BGP) is the protocol that makes the various networks composing the Internet communicate to each other. Routers speaking BGP exchange updates to keep the routing up-to-date and allow such communication. This usually is done to reflect changes in the routing configurations or as a consequence of link failures. In the Internet as a whole it is normal that BGP updates are continuously exchanged, but for any specific IP prefix, these updates are supposed to be concentrated in a short time interval that is needed to react to a network change. On the contrary, in this paper we show that there are many IP prefixes involved in quite long sequences consisting of a large number of BGP updates. Namely, examining ∼30 billion updates collected by 172 observation points distributed worldwide, we estimate that almost 30% of them belong to sequences lasting more than one week. Such sequences involve 222285 distinct IP prefixes, approximately one fourth of the number of announced prefixes. We detect such sequences using a method based on the Discrete Wavelet Transform. We publish an online tool for the exploration and visualization of such sequences, which is open to the scientific community for further research. We group together sequences that exhibit common behaviours. For this purpose, we devise a clusterization algorithm able to group the sequences based on their similarity in time. We highlight four categories of clusters, which are attributable to different types of Internet events. Our online tool allows also to explore and to visualize the computed clusters.

Robust P2P networking connectivity estimation engine for permissionless Bitcoin cryptocurrency

Blockchain relies on the underlying peer-to-peer (P2P) networking to broadcast and get up-to-date on the blocks and transactions. Because of the blockchain operations’ reliance on the information provided by P2P networking, it is imperative to have high P2P connectivity for the quality of the blockchain system operations and performances. High P2P networking connectivity ensures that a peer node is connected to multiple other peers providing a diverse set of observers of the current state of the blockchain and transactions. However, in a permissionless Bitcoin cryptocurrency network, using the peer identifiers – including the current approach of counting the number of distinct IP addresses and port numbers – can be ineffective in measuring the number of peer connections and estimating the networking connectivity. Such current approach is further challenged by the networking threats manipulating identities. We build a robust estimation engine for the P2P networking connectivity by sensing and processing the P2P networking traffic. We take a systematic approach to study our engine and analyze the followings: the different components of the connectivity estimation engine and how they affect the accuracy performances, the role and the effectiveness of an outlier detection to enhance the connectivity estimation, and the engine’s interplay with the Bitcoin protocol. We implement a working Bitcoin prototype connected to the Bitcoin mainnet to validate and improve our engine’s performances and evaluate the estimation accuracy and cost efficiency of our connectivity estimation engine. Our results show that our scheme effectively counters the identity-manipulations threats, achieves 96.4% estimation accuracy with a tolerance of one peer connection, and is lightweight in the overheads in the mining rate, thus making it appropriate for the miner deployment.

Exploring the Colombian digital divide using Moodle logs through supervised learning

PurposeThis study aims to explore the digital divide between students living in metropolitan and non-metropolitan areas in the Antioquia region of Colombia. This is achieved by collecting data about student interactions from the Moodle learning management system (LMS), and subsequently applying supervised machine learning models to infer the gap between students in metropolitan and non-metropolitan areas.Design/methodology/approachThis work uses the well-established Cross-Industry Standard Process for Data Mining methodology, which comprises six phases, viz., problem understanding, data understanding, data preparation, modelling, evaluation and implementation. In this case, student data was collected from the Moodle platform from the Antioquia campus of the UNAD distance learning university.FindingsThe digital divide is evident in the classification model when observing differences in variables such as the number of accesses to the LMS, the total time spent and the number of distinct IP addresses used, as well as the number of system modification events.Originality/valueThis study provides conclusions regarding the problems students in virtual education may face as a result of the digital divide in Colombia which have become increasingly visible since the implementation of machine learning methodologies on LMS such as Moodle. However, these practices may be replicated in any virtual educational context and furthermore be extended to enable personalisation of various aspects of the Moodle platform to meet the individual needs of students.

Investor Monitoring, Money-Likeness and Stability of Money Market Funds

An asset is money-like if investors have no incentives to acquire costly private information on the underlying collateral. However, privately provided money-like assets—like prime money market fund (MMF) shares—are prone to runs if investors suddenly start to question the value of the collateral. Therefore, for risky assets, lack of money-likeness is a necessary condition for lack of run incentives. But is it a sufficient one? This paper studies the effect of the U.S. money market fund reform of 2014--2016 on investor monitoring, money-likeness and stability of institutional prime MMFs. Using the number of distinct IP addresses accessing MMFs' regulatory reports as a proxy for investor monitoring, we find that the reform increased monitoring and thus decreased money-likeness of institutional prime funds. However, we also show that after the reform, institutional prime funds that are more likely to impose the newly introduced redemption restrictions are more monitored, suggesting that investors may monitor in order to avoid being hit by the restrictions. In line with this view, we find that a high probability of redemption restrictions amplifies the run on institutional prime MMFs during the Covid-19 related market panic in March 2020. Overall, our results indicate that despite decreased money-likeness, the reform has not made institutional prime MMFs run-free, and it may have actually created a new source of fragility for MMFs.

Core Communication Interface for FPGAs

The use of pre-designed and pre-verified hardware modules, also called IP cores, is an important part of the effort to design and implement complex systems. However, many aspects of IP core manipulation are still to be developed. This paper presents an approach to solve problems related to the dynamic interconnection of hard IP cores. The approach targets system-on-a-chip designs build in a single FPGA device. The paper proposes a communication interface that allows IP cores replacement during the FPGA normal operation. The same interface also allows the communication among distinct IP cores to take place.

Outlier detection in IP traffic modelled as a link stream using the stability of degree distributions over time

This paper aims at precisely detecting and identifying anomalous events in IP traffic. To this end, we adopt the link stream formalism which properly captures temporal and structural features of the data. Within this framework, we focus on finding anomalous behaviours with respect to the degree of IP addresses over time, i.e. the number of distinct IP addresses with which they interact over time. Due to diversity in IP profiles, this feature is typically distributed heterogeneously, preventing us to directly find anomalies. To deal with this challenge, we design a method to detect outliers as well as precisely identify their cause in a sequence of similar heterogeneous distributions. We apply it to several IP traffic captures and we show that it succeeds in detecting relevant patterns in terms of anomalous network activity.

An exponent based error detection mechanism against DXDOS attack for improving the security in cloud

Providing security to Cloud against the harmful attacks is an important and essential thing in recent days. Because, there are lot of attacks intend to affect the performance of data transmission in Cloud. Specifically, the extensible markup language-denial of service (XML-DoS) cause the severe damage to Cloud, which misuses the protocols for injecting the attack packets and disturbing the protocol handlers. So, this type of attack must be detected for enabling a reliable and secure service delivery in Cloud. For this purpose, the traditional works developed various attack detection mechanisms for identifying and blocking the XML-DoS attacks, but it lacks with the limitations of increased computation overhead, reduced detection accuracy, and inefficient classification. To solve these issues, this paper aims to develop a new attack detection framework based on the XML schema. The stages that involved in this work are, pattern validation, traffic extraction, error classification, and IP traceback. At first, the individual users transmit the packets to the routers, then the packet marking is performed based on the router IP. After that, the patterns of the packets are validated, if it is valid, the distinct IP is counted for IP matching. Consequently, the time sequence Tsallis entropy, source IP Tsallis entropy, and Lyapunov exponent are estimated. Based on the estimated exponent value, the error is classified as the chaotic or non-chaotic. Finally, the bee colony algorithm is implemented to perform the IP traceback, which takes the appropriate decision for blocking the attacker packets from the particular server. In experiments, the performance of the proposed method is evaluated by using various performance measures. Also, the superiority of the proposed system is proved by comparing it with the existing techniques.

Multifactorial Optimizations for Directing Endothelial Fate from Stem Cells.

Embryonic stem cells (ESC) and induced pluripotent stem (iPS) cells are attractive in vitro models of vascular development, therapeutic angiogenesis, and tissue engineering. However, distinct ESC and iPS cell lines respond differentially to the same microenvironmental factors. Developing improved/optimized differentiation methodologies tailored/applicable in a number of distinct iPS and ESC lines remains a challenge in the field. Currently published methods for deriving endothelial cells (EC) robustly generate high numbers of endothlelial progenitor cells (EPC) within a week, but their maturation to definitive EC is much more difficult, taking up to 2 months and requiring additional purification. Therefore, we set out to examine combinations/levels of putative EC induction factors—utilizing our stage-specific chemically-defined derivation methodology in 4 ESC lines including: kinetics, cell seeding density, matrix signaling, as well as medium treatment with vascular endothelial growth factor (VEGF), and basic fibroblast growth factor (bFGF). The results indicate that temporal development in both early and late stages is the most significant factor generating the desired cells. The generation of early Flk-1+/KDR+ vascular progenitor cells (VPC) from pluripotent ESC is directed predominantly by high cell seeding density and matrix signaling from fibronectin, while VEGF supplementation was NOT statistically significant in more than one cell line, especially with fibronectin matrix which sequesters autocrine VEGF production by the differentiating stem cells. Although some groups have shown that the GSK3-kinase inhibitor (CHIR) can facilitate EPC fate, it hindered the generation of KDR+ cells in our preoptimized medium formulations. The methods summarized here significantly increased the production of mature vascular endothelial (VE)-cadherin+ EC, with up to 93% and 57% purity from mouse and human ESC, respectively, before VE-cadherin+ EC purification.

Analysis of a “/0” Stealth Scan From a Botnet

Botnets are the most common vehicle of cyber-criminal activity. They are used for spamming, phishing, denial-of-service attacks, brute-force cracking, stealing private information, and cyber warfare. Botnets carry out network scans for several reasons, including searching for vulnerable machines to infect and recruit into the botnet, probing networks for enumeration or penetration, etc. We present the measurement and analysis of a horizontal scan of the entire IPv4 address space conducted by the Sality botnet in February 2011. This 12-day scan originated from approximately 3 million distinct IP addresses and used a heavily coordinated and unusually covert scanning strategy to try to discover and compromise VoIP-related (SIP server) infrastructure. We observed this event through the UCSD Network Telescope, a /8 darknet continuously receiving large amounts of unsolicited traffic, and we correlate this traffic data with other public sources of data to validate our inferences. Sality is one of the largest botnets ever identified by researchers. Its behavior represents ominous advances in the evolution of modern malware: the use of more sophisticated stealth scanning strategies by millions of coordinated bots, targeting critical voice communications infrastructure. This paper offers a detailed dissection of the botnet's scanning behavior, including general methods to correlate, visualize, and extrapolate botnet behavior across the global Internet.

Functional characterization of myrcene hydroxylases from two geographically distinct Ips pini populations

Ips pini bark beetles use myrcene hydroxylases to produce the aggregation pheromone component, ipsdienol, from myrcene. The enantiomeric ratio of pheromonal ipsdienol is an important prezygotic mating isolation mechanism of I. pini and differs among geographically distinct populations. We explored the substrate and product ranges of myrcene hydroxylases (CYP9T2 and CYP9T3) from reproductively-isolated western and eastern I. pini. The two cytochromes P450 share 94% amino acid identity. CYP9T2 mRNA levels were not induced in adults exposed to myrcene-saturated atmosphere. Functional assays of recombinant enzymes showed both hydroxylated myrcene, (+)- and (−)-α-pinene, 3-carene, and R-(+)-limonene, but not α-phellandrene, (−)-β-pinene, γ-terpinene, or terpinolene, with evidence that CYP9T2 strongly preferred myrcene over other substrates. They differed in the enantiomeric ratios of ipsdienol produced from myrcene, and in the products resulting from different α-pinene enantiomers. These data provide new information regarding bark beetle pheromone evolution and factors affecting cytochrome P450 structure–function relationships.

Distinct iPS Cells Show Different Cardiac Differentiation Efficiency

Patient-specific induced pluripotent stem (iPS) cells can be generated by introducing transcription factors that are highly expressed in embryonic stem (ES) cells into somatic cells. This opens up new possibilities for cell transplantation-based regenerative medicine by overcoming the ethical issues and immunological problems associated with ES cells. Despite the development of various methods for the generation of iPS cells that have resulted in increased efficiency, safety, and general versatility, it remains unknown which types of iPS cells are suitable for clinical use. Therefore, the aims of the present study were to assess (1) the differentiation potential, time course, and efficiency of different types of iPS cell lines to differentiate into cardiomyocytes in vitro and (2) the properties of the iPS cell-derived cardiomyocytes. We found that high-quality iPS cells exhibited better cardiomyocyte differentiation in terms of the time course and efficiency of differentiation than low-quality iPS cells, which hardly ever differentiated into cardiomyocytes. Because of the different properties of the various iPS cell lines such as cardiac differentiation efficiency and potential safety hazards, newly established iPS cell lines must be characterized prior to their use in cardiac regenerative medicine.

Fuzzy Based Approach for P2P File Sharing Detection

P2P file sharing is a very popular network application. Many studies have focused on the identification of P2P file sharing. In this paper, a fuzzy based approach was proposed to identify the P2P file sharing application. In this fuzzy based approach, four features are selected and normalized as the input parameters; these features are default P2P port, UDP packet count, traffic volume, and distinct IP connections. The fuzzification, rule evaluation, and defuzzification are three steps to obtain the final crisp value. Host running P2P file sharing application can be identified by thresholding on the crisp value. Experimental results show that this proposed fuzzy based approach can identify the P2P file sharing application more accuracy than other intelligent methods such as flexible neural tree and decision tree algorithms.

Structural Studies of Inositol 1,4,5-Trisphosphate Receptor: COUPLING LIGAND BINDING TO CHANNEL GATING

The three isoforms of the inositol 1,4,5-trisphosphate receptor (IP(3)R) exhibit distinct IP(3) sensitivities and cooperativities in calcium (Ca(2+)) channel function. The determinants underlying this isoform-specific channel gating mechanism have been localized to the N-terminal suppressor region of IP(3)R. We determined the 1.9 Å crystal structure of the suppressor domain from type 3 IP(3)R (IP(3)R3(SUP), amino acids 1-224) and revealed structural features contributing to isoform-specific functionality of IP(3)R by comparing it with our previously determined structure of the type 1 suppressor domain (IP(3)R1(SUP)). The molecular surface known to associate with the ligand binding domain (amino acids 224-604) showed marked differences between IP(3)R3(SUP) and IP(3)R1(SUP). Our NMR and biochemical studies showed that three spatially clustered residues (Glu-20, Tyr-167, and Ser-217 in IP(3)R1 and Glu-19, Trp-168, and Ser-218 in IP(3)R3) within the N-terminal suppressor domains of IP(3)R1(SUP) and IP(3)R3(SUP) interact directly with their respective C-terminal fragments. Together with the accompanying paper (Yamazaki, H., Chan, J., Ikura, M., Michikawa, T., and Mikoshiba, K. (2010) J. Biol. Chem. 285, 36081-36091), we demonstrate that the single aromatic residue in this region (Tyr-167 in IP(3)R1 and Trp-168 in IP(3)R3) plays a critical role in the coupling between ligand binding and channel gating.

The P2P war: Someone is monitoring your activities

In an effort to legally prosecute P2P users, the RIAA and MPAA have reportedly started to create decoy users: they participate in P2P networks in order to identify illegal sharing of content. This has reportedly scared some users who are afraid of being caught and prosecuted. The question we would like to answer is how prevalent is this phenomenon: how likely is it that a user will run into such a ''fake user'' and thus run the risk of a lawsuit? The first challenge is identifying these ''fake users''. We collect this information from a number of free open-source software projects which are trying to identify such addresses by forming the, so-called, blocklists. The second challenge is to quantify the probability of a user contacting such a fake user by conducting a large scale experiment in order to obtain reliable statistics. Using PlanetLab, we conduct active measurements, spanning a period of 90 days, from January to March 2006, spread over three continents. Analyzing over 100GB of TCP header data, we quantify the probability of a P2P user contacting fake users. We observe that 100% of our peers run into entities in these lists. In fact, 12-17% of all distinct IPs contacted by any node were listed on blocklists. Interestingly, a little caution can have significant effect: the top five most prevalent blocklisted IP ranges contribute to nearly 94% of all blocklisted IPs we ran into. Avoiding these can reduce the probability of a user being tracked to about 1%. In addition, we examine the identity of these blocklisted IPs. The majority of blocklisted IPs belong to the commercial and government domains and are nearly 2.5 times more than IPs belonging to educational, spyware or adware entities. Interestingly, less than 0.5% of all unique IPs contacted, belong explicitly to media companies. However, this may not be reassuring for P2P users, since the other blocklist users (government or commercial) could be collaborating with media companies.

Effects of the Selective Prostacyclin Receptor Antagonist RO3244019 on the Micturition Reflex in Rats

We investigated the role of prostacyclin on afferent modulation of the micturition reflex using the novel selective prostacyclin receptor antagonist RO3244019 in rat models of bladder function. The effects of RO3244019 on urodynamic parameters were evaluated in 3 rat models. In the anesthetized isovolumetric bladder contraction and the volume induced micturition reflex (Refill) models the effects of RO3244019 and chronic capsaicin desensitization were compared. In the citric acid induced detrusor overactivity model the effects of RO3244019 and the cyclooxygenase inhibitor indomethacin were evaluated. In the isovolumetric bladder contraction model RO3244019 dose dependently decreased bladder contraction frequency with a mean +/- SEM maximum decrease of 72.2% +/- 4.3% at 3.16 mg/kg. RO3244019 also dose dependently increased the micturition threshold in the Refill model with a maximum increase of 86.9% +/- 19.1% at 3.0 mg/kg. In animals that were chronically treated with capsaicin bladder contraction frequency was decreased by 88.9% in the isovolumetric bladder contraction model and micturition threshold was increased by 68.1% in the Refill model relative to sham treated rats. RO3244019 (3.0 mg/kg) further increased the micturition threshold in capsaicin treated animals by 53.7% +/- 18.1% from baseline. In the citric acid induced detrusor overactivity model citric acid decreased the voiding interval to 28.5% of baseline. This effect was reversed by RO3244019 (73.0% +/- 6.4%) and indomethacin (97.7% +/- 5.5%) at 3.0 mg/kg compared to vehicle (55.0% +/- 4.1%). The prostacyclin receptor antagonist RO3244019 decreased bladder contraction frequency and increased micturition threshold in the anesthetized isovolumetric bladder contraction and Refill models, respectively, and increased the micturition voiding interval in the conscious citric acid induced detrusor overactivity model. Additionally, RO3244019 remained effective for increasing the micturition threshold in the Refill model even following chronic capsaicin desensitization. Taken together these data suggest that prostacyclin may have a facilitory role in the micturition reflex by modulating the threshold for activation of capsaicin sensitive and insensitive bladder sensory afferents.

Successful participant recruitment strategies for an online smokeless tobacco cessation program

An estimated 22% of Americans currently use smokeless tobacco (ST). Most live in small towns and rural areas that offer few ST cessation resources. Approximately 94 million Americans use the Internet for health-related information, and on-line access is growing among lower-income and less-educated groups. As part of a randomized clinical trial to assess the reach and effectiveness of Web-based programs for delivering an ST cessation intervention, the authors developed and evaluated several methods for overcoming the recruitment challenges associated with Web-based research. This report describes and evaluates these methods. Participants were recruited through: (a) Thematic promotional "releases" to print and broadcast media, (b) Google ads, (c) placement of a link on other Web sites, (d) limited purchase of paid advertising, (e) direct mailings to ST users, and (f) targeted mailings to health care and tobacco control professionals. Combined recruitment activities resulted in more than 23,500 hits on our recruitment website from distinct IP addresses over 15 months, which yielded 2,523 eligible ST users who completed the registration process and enrolled in the study. Self-reports revealed that at least 1,276 (50.6%) of these participants were recruited via mailings, 874 (34.6%) from Google ads or via search engines or links on another Web site, and 373 (14.8%) from all other methods combined. The use of thematic mailings is novel in research settings. Recruitment of study participants went quickly and smoothly. Google ads and mailings to media outlets were the methods that recruited the highest number of participants.

SVision: A novel visual network-anomaly identification technique

We propose a novel graphical technique (SVision) for intrusion detection, which pictures the network as a community of hosts independently roaming in a 3D space defined by the set of services that they use. The aim of SVision is to graphically cluster the hosts into normal and abnormal ones, highlighting only the ones that are considered as a threat to the network. Our experimental results conducted on DARPA 1999 and 2000 intrusion detection and evaluation datasets as well as real network data captured between 2003 and 2005 from the University of New Brunswick main link, and also a private network, show the proposed technique as a good candidate for the detection of various network threats such as vertical and horizontal scanning attacks, Denial of Service (DoS) attacks, Distributed DoS (DDoS) attacks, as well as worm propagation attack. Finally, the visualization technique proves to cope with high number of hosts in the network, the experimental results using network data of up to 1,000,000 distinct IPs per time interval.

Inferring Internet denial-of-service activity

In this article, we seek to address a simple question: “How prevalent are denial-of-service attacks in the Internet?” Our motivation is to quantitatively understand the nature of the current threat as well as to enable longer-term analyses of trends and recurring patterns of attacks. We present a new technique, called “backscatter analysis,” that provides a conservative estimate of worldwide denial-of-service activity. We use this approach on 22 traces (each covering a week or more) gathered over three years from 2001 through 2004. Across this corpus we quantitatively assess the number, duration, and focus of attacks, and qualitatively characterize their behavior. In total, we observed over 68,000 attacks directed at over 34,000 distinct victim IP addresses---ranging from well-known e-commerce companies such as Amazon and Hotmail to small foreign ISPs and dial-up connections. We believe our technique is the first to provide quantitative estimates of Internet-wide denial-of-service activity and that this article describes the most comprehensive public measurements of such activity to date.