15,468 research outputs found
Energy-efficient pipelined bloom filters for network intrusion detection
No full textSoftware-based detection techniques are commonly used to identify the predefined signatures in network streams. However, the software-based techniques can not keep up with the speeds that network bandwidth increases. Hence, hardware-based systems have started to emerge. Bloom filters are frequently used to identify malicious content like viruses in high speed networks. However, architectures proposed to implement Bloom filters are not power efficient. We propose a new Bloom filter architecture that exploits the well-known pipelining technique. Through extensive power analysis we show that pipelining can reduce the power consumption of Bloom filters up to 90%, which leads to the energy-efficient implementation of network intrusion detection system
MS 025 Guide to Samuel Bloom, PhD Papers (1935-2000)
No full textThe Samuel Bloom, Ph.D., collection consists of materials related to his career as Assistant Professor of Sociology, Department of Psychiatry, Baylor College of Medicine. See more at MS 025
Increasing the power efficiency of Bloom filters for network string matching
No full textAlthough software based techniques are widely accepted in computer security systems, there is a growing interest to utilize hardware opportunities in order to compensate for the network bandwidth increases. Recently, hardware based virus protection systems have started to emerge. This type of hardware systems work by identifying the malicious content and removing it from the network streams. In principle, they make use of string matching. Bit by bit, they compare the virus signatures with the bit strings in the network. The bloom filters are ideal data structures for string matching. Nonetheless, they consume large power when many of them used in parallel to match different virus signatures. In this paper, we propose a new type of Bloom filter architecture which exploits well-known pipelining techniqu
No. 661 Jo Tice Bloom
No full textTranscript (19 pages) of an interview by Greg Smoak with Jo Tice Bloom at Oakland, California, on 15 October 2011. Part of the Western History Association Oral History Project, Everett Cooley Collection tape no. U-3098Ms. Bloom talks about the history of and her involvement in the Western History Association (WHA), particularly the role and acceptance of women in the organization. She discusses the key people who were involved in the WHA and how their activities contribution to the development of the organization. She relates how her husband´s involvement in WHA leadership positions impacted her own involvement. Ms. Bloom notes changes in the WHA over the years and the impact of those changes on the association. Project: Western History Association. Interviewer: Greg Smoa
New Approach Based on LC-ESI-MS/MS for Identification of MicrocystinVariants During Cyanobacterial Bloom Events
No full textThe aim of this work was the development of a rapid and efficient approach based on LC-ESI-MS/MS for identification of MC variants in emergencies related to cyanobacterial bloom
Ms. Courtney Chartier, RWWL AUC, August 2011
No full textThis video is a conversation with Ms. Courtney Chartier. Ms. Chartier talks about her work on the "New Georgia Encyclopedia" and "Online Voter Education Project." Andrea Jackson, AUC Woodruff Library, is the interviewer
Ms. Neely Terrell, RWWL AUC, March 2012
No full textThis video is a conversation with Ms. Neely Terrell. Ms. Terrell talks about her book, "Super Singles Activate". Anthony Kinsey and Jahnesta Horney, AUC Woodruff Library, are the interviewers
Combined LC-MS/MS and Molecular Networking Approach Reveals New Cyanotoxins from the 2014 Cyanobacterial Bloom in Green Lake, Seattle
No full textCyanotoxins obtained from a freshwater cyanobacterial collection at Green Lake, Seattle during a cyanobacterial harmful algal bloom in the summer of 2014 were studied using a new approach based on molecular networking analysis of liquid chromatography tandem mass spectrometry (moleculrLC-MS/MS) data. This MS networking approach is particularly well-suited for the detection of new cyanotoxin variants and resulted in the discovery of three new cyclic peptides, namely microcystin-MhtyR (6), which comprised about half of the total microcystin content in the bloom, and ferintoic acids C (12) and D (13). Structure elucidation of 6 was aided by a new microscale methylation procedure. Metagenomic analysis of the bloom using the 16S-ITS rRNA region identified Microcystis aeruginosa as the predominant cyanobacterium in the sample. Fragments of the putative biosynthetic genes for the new cyanotoxins were also identified, and their sequences correlated to the structure of the isolated cyanotoxins
Chemical Composition of Fat Bloom on Chocolate Products Determined by Combining NMR and HPLC–MS
No full textTo reduce unwanted fat bloom in the manufacturing and storage of chocolates, detailed knowledge of the chemical composition and molecular mobility of the oils and fats contained is required. Although the formation of fat bloom on chocolate products has been studied for many decades with regard to its prevention and reduction, questions on the molecular level still remain to be answered. Chocolate products with nut-based fillings are especially prone to undesirable fat bloom. The chemical composition of fat bloom is thought to be dominated by the triacylglycerides of the chocolate matrix, which migrate to the chocolate’s surface and recrystallize there. Migration of oils from the fillings into the chocolate as driving force for fat bloom formation is an additional factor in the discussion. In this work, the migration was studied and confirmed by MRI, while the chemical composition of the fat bloom was measured by NMR spectroscopy and HPLC–MS, revealing the most important triacylglycerides in the fat bloom. The combination of HPLC–MS with NMR spectroscopy at 800 MHz allows for detailed chemical structure determination. A rapid routine was developed combining the two modalities, which was then applied to investigate the aging, the impact of chocolate composition, and the influence of hazelnut fillings processing parameters, such as the degree of roasting and grinding of the nuts or the mixing time, on fat bloom formation
Hardware acceleration for power efficient deep packet inspection
No full textThe rapid growth of the Internet leads to a massive spread of malicious attacks like viruses and malwares, making the safety of online activity a major concern. The use of Network Intrusion Detection Systems (NIDS) is an effective method to safeguard the Internet. One key procedure in NIDS is Deep Packet Inspection (DPI). DPI can examine the contents of a packet and take actions on the packets based on predefined rules. In this thesis, DPI is mainly discussed in the context of security applications. However, DPI can also be used for bandwidth management and network surveillance.
DPI inspects the whole packet payload, and due to this and the complexity of the inspection rules, DPI algorithms consume significant amounts of resources including time, memory and energy. The aim of this thesis is to design hardware accelerated methods for memory and energy efficient high-speed DPI.
The patterns in packet payloads, especially complex patterns, can be efficiently represented by regular expressions, which can be translated by the use of Deterministic Finite Automata (DFA). DFA algorithms are fast but consume very large amounts of memory with certain kinds of regular expressions. In this thesis, memory efficient algorithms are proposed based on the transition compressions of the DFAs.
In this work, Bloom filters are used to implement DPI on an FPGA for hardware acceleration with the design of a parallel architecture. Furthermore, devoted at a balance of power and performance, an energy efficient adaptive Bloom filter is designed with the capability of adjusting the number of active hash functions according to current workload. In addition, a method is given for implementation on both two-stage and multi-stage platforms. Nevertheless, false positive rates still prevents the Bloom filter from extensive utilization; a cache-based counting Bloom filter is presented in this work to get rid of the false positives for fast and precise matching.
Finally, in future work, in order to estimate the effect of power savings, models will be built for routers and DPI, which will also analyze the latency impact of dynamic frequency adaption to current traffic. Besides, a low power DPI system will be designed with a single or multiple DPI engines. Results and evaluation of the low power DPI model and system will be produced in future
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