941 research outputs found
Determination of Dark Matter Halo Mass from Dynamics of Satellite Galaxies
We show that the mass of a dark matter halo can be inferred from the
dynamical status of its satellite galaxies. Using 9 dark-matter simulations of
halos like the Milky Way (MW), we find that the present-day substructures in
each halo follow a characteristic distribution in the phase space of orbital
binding energy and angular momentum, and that this distribution is similar from
halo to halo but has an intrinsic dependence on the halo formation history. We
construct this distribution directly from the simulations for a specific halo
and extend the result to halos of similar formation history but different
masses by scaling. The mass of an observed halo can then be estimated by
maximizing the likelihood in comparing the measured kinematic parameters of its
satellite galaxies with these distributions. We test the validity and accuracy
of this method with mock samples taken from the simulations. Using the
positions, radial velocities, and proper motions of 9 tracers and assuming
observational uncertainties comparable to those of MW satellite galaxies, we
find that the halo mass can be recovered to within 40%. The accuracy can
be improved to within 25% if 30 tracers are used. However, the dependence
of the phase-space distribution on the halo formation history sets a minimum
uncertainty of 20% that cannot be reduced by using more tracers. We
believe that this minimum uncertainty also applies to any mass determination
for a halo when the phase space information of other kinematic tracers is used.Comment: Accepted for publication in ApJ, 18 pages, 13 figure
2-Nitro-N-(8-quinolyl)benzamide
In the title compound, C16H11N3O3, the amide group is twisted away from the quinoline ring system and nitroÂbenzene ring by 8.02 (1)° and 54.92 (1)°, respectively. The crystal packing is stabilized by interÂmolecular C—H⋯O hydrogen bonds, and π–π interÂactions between the quinoline ring systems of inversion-related molÂecules, with a centroid–centroid distance of 3.4802 (13) Å
Distinguishing DDoS attacks from flash crowds using probability metrics
Both Flash crowds and DDoS (Distributed Denial-of-Service) attacks have very similar properties in terms of internet traffic, however Flash crowds are legitimate flows and DDoS attacks are illegitimate flows, and DDoS attacks have been a serious threat to internet security and stability. In this paper we propose a set of novel methods using probability metrics to distinguish DDoS attacks from Flash crowds effectively, and our simulations show that the proposed methods work well. In particular, these mathods can not only distinguish DDoS attacks from Flash crowds clearly, but also can distinguish the anomaly flow being DDoS attacks flow or being Flash crowd flow from Normal network flow effectively. Furthermore, we show our proposed hybrid probability metrics can greatly reduce both false positive and false negative rates in detection.<br /
Source-based filtering scheme against DDOS attacks
IP address spoofing is employed by a lot of DDoS attack tools. Most of the current research on DDoS attack packet filtering depends on cooperation among routers, which is hard to achieve in real campaigns. Therefore, in the paper, we propose a novel filtering scheme based on source information in this paper to defend against various source IP address spoofing. The proposed method works independently at the potential victim side, and accumulates the source information of its clients, for instance, source IP addresses, hops from the server during attacks free period. When a DDoS attack alarm is raised, we can filter out the attack packets based on the accumulated knowledge of the legitimate clients. We divide the source IP addresses into n(1 ≤ n ≤ 32) segments in our proposed algorithm; as a result, we can therefore release the challenge storage and speed up the procedure of information retrieval. The system which is proposed by us and the experiments indicated that the proposed method works effectively and efficiently.<br /
- …