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Table 102 gives some examples of the attack characteristics in autocorrelation change In Table 102, A+ indicates an autocorrelation increase attack characteristic, and A indicates an autocorrelation decrease attack characteristic In the Apache Resource DoS attack, the variables, IP\Datagrams Sent/sec, which measures the rate of IP datagrams supplied to IP for transmission, and Network Interface\Packets/sec, which measures the rate of packets sent and received on the network interface, have the autocorrelation decrease characteristic from the high autocorrelation to the low autocorrelation (AH AL in Table 102) Figure 102 plots the data observations of both variables in the attack condition Both variables jump to and stay at a high value in the rst half of the attack and then drop to the value of zero when the server crashes in the second half of the attack A high value in the rst half, zero in the second half and the average value in the middle of this high value and zero produce a low autocorrelation coef cient according to Formula 101 In the ARP Poison attack, the variables, Network Interface\Bytes Received/sec and Network Interface\Packets Received/sec measuring the rate of bytes and packets respectively received on the network interface, have the autocorrelation increase characteristic from the low autocorrelation under the inactive condition to the medium autocorrelation under the attack condition Figure 103 plots the data observations of Network Interface\Packets Received/sec under the attack condition The data plot shows a cyclic pattern at a frequency corresponding to one of the ten lags but not all the ten lags, producing the medium autocorrelation The autocorrelation increase characteristic of Network Interface\Packets Received/sec also appears in the Security Scan attack due to a cyclic pattern of the time series data at a given lag caused by the repetitive network requests to the victim computer from the attacker The variable, Memory\Write Copies/sec, measures the number of page faults which are caused by the memory-write attempts but are satis ed by copying the page from elsewhere in the physical memory, that is, by sharing the data already in the memory This variable shows an autocorrelation decrease from the high autocorrelation under the inactive condition to the medium autocorrelation under the Fork Bomb attack Under the inactive condition, this variable has almost a constant value with a few exceptions, producing the average value different from the constant value, a large utocorrelation coef cient at all the ten lags, and thus the high autocorrelation However, the time series data under the Fork Bomb attack has a cyclic pattern at a given lag but not all the ten lags due to the repetitive creation of many processes of the same program, producing the medium autocorrelation. 38 Table 20: TBarCode/X Configuration Files 38 Table 21: Barcode Symbologies and Enumerators 59 . 65 Table 35: Overview Parameter Syntax of Version 1.x 67 .Related: Table 102 Examples of attack characteristics in autocorrelation change Attacks Distributed ork FTP Hardware Rootkit Security Software Vulnerability Barcode Generation In NET Framework Using Barcode Related: EAN-13 Generating NET , NET EAN 128 Generating , Generate UPC-A NET. 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