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The attacks within each group are similar with regard to their shared attack characteristics The two attacks in groups s1, S1 and Ls1, Apache Resource DoS and Fork Bomb, share 54 attack characteristics (see Table 85) including 46 attack characteristics in the Process object (eg, the mean increase characteristics in Process( System)\% Processor Time and Process( System)\IO Write Operations/sec) and 6 attack characteristics in the Cache object (eg, a mean increase characteristic in Cache\Copy Reads/sec) This re ects the fact that both attacks consume a large amount of processing and cache resources The two attacks in groups s2, S2 and Ls2, Rootkit and Vulnerability Scan, share 59 attack characteristics (see Table 85) including 58 attack characteristics in the Process object These 58 shared attack characteristics cover such variables as Virtual Bytes, Working Set, Working Set Peak, Page File Bytes, Private Bytes, and Pool Nonpaged Bytes of many system processes such as system, alg, csrss, smss, censtat, nvsvc32, svchost#2, winlogon, and CtiServ The FTP Buffer Over ow attack joins the Apache Resource DoS and Fork Bomb attacks in groups s1 and Ls1 due to 29 attack characteristics shared between Fork Bomb and FTP Buffer Over ow, most of which are the Process variables concerning working resources (eg, Virtual Bytes, page File Bytes, Private Bytes, Thread Count, and Pool Nonpaged Bytes), and 20 attack characteristics shared between Apache Resource DoS and FTP Buffer Over ow, many of which are the Process variables concerning IO operations (eg, IO Other Operations/sec and IO Other Bytes/sec) and Page Faults Hence, FTP Buffer Over ow is similar to Apache Resource DoS and Fork Bomb in different ways The Apache Resource DoS, Fork Bomb and FTP Buffer Over ow attacks also share the mean increase characteristics of ve Cache variables, Copy Reads/sec, Sync Copy Reads/sec, Copy Read Hits %, Fast Reads/sec, Sync Fast Reads/sec The Security Audit and Software Keylogger attacks in groups S3 and Ls2 share 23 attack characteristics (see Table 85) in various objects including 9 in Terminal Services Session, 6 in Process, and some others in LogicalDisk and PhysicalDisk Table 86 summarizes the number of the opposite attack characteristics between each pair of attacks Two attack characteristics for a given pair of attacks are opposite if the same variable has the mean increase characteristic under one attack and the mean decrease characteristic under another attack For example, the Apache Resource DoS attack has the mean increase characteristic in Process\(svchost#1)\Handle Count, whereas the ARP Poison attack has the mean decrease characteristic in the same variable This is one of the three opposite attack characteristics between Apache Resource DoS and ARP Poison The number of opposite attack characteristics between each pair of the ten attacks without Hardware Keylogger is taken as a dissimilarity value between the pair of attacks and is used to produce a hierarchical clustering of the ten attacks as shown in Figure 85, based on the average linkage method of the hierarchical clustering procedure in Statistica Figure 86 shows the hierarchical clustering of the ten attacks based on Ward s linkage method Considering the clusters with the linkage.

Figure 5.6 Relation between cold (c), pressure (p) and heat (h) denaturation of proteins and three-dimensional free energy landscape in response to pressure and temperature (18). Reprinted with kind permission of Springer Science and Business Media.

We use the subscript n when referring to certain markers collectively For example, RSTn means any of the restart markers RST0 to RST7; SOFn means any start of frame marker

2 G = G0 + V0 ( p p0 ) S0 (T T0 ) + ( 2) ( p p0 ) ( c p 2T0 ) (T T0 )2 + ( p p0 ) (T T0 )

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Table 86 The number of opposite characteristics (variables) among the attacks Attacks Distributed 2 0 1 0 17 2 0 11 13 2 16 25 10 22 8 3 12 5 7 6 17 26 9 8 49 31 Fork FTP Hardware Remote Rootkit Security Software 2 12 27 11 6 20 8 20 Vulnerability 1 3 6 0 1 25 3 18 2

(5.18)

where denotes the change of the corresponding parameter during unfolding This quadratic two-variable approximation of the difference in Gibbs free energy yields to an ellipsoidal phase transition line in the pressure and temperature landscape for equilibrium condition ( G = 0 in Fig 56) (47) This model can be treated as a general approach, where state A and state B could denote molecular or physicochemical states In the case of spore inactivation, state A could represent the recoverable and B the not recoverable spores, respectively The transition line would run along the equilibrium G = 0 as elliptical shape at various pressures and temperatures (18).

Figure 85 The hierarchical clustering of the attacks based on the opposite attack characteristics and the average linkage method

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