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The DHT (Define Huffman Table) marker defines (or redefines) Huffman tables, which are identified by a class (AC or DC 3 ) and a number A single DHT marker can define multiple tables; however, baseline mode is limited to two of each type, and progressive and sequential modes are limited to four The only restriction on the placement of DHT markers is that if a scan requires a specific table identifier and class, it must have been defined by a DHT marker earlier in a file The structure of the DHT marker is shown in Table 53 Each Huffman table is 17 bytes of fixed data followed by a variable field of up to 256 additional bytes The first fixed byte contains the identifier for the table The next 16 form an array of unsigned 1-byte integers whose elements give the number of Huffman codes for each possible code length (1-16) The sum of the 16 code lengths is the number of values in the Huffman table The values are 1 byte each and follow, in order of Huffman code, the length counts The structure of Huffman tables is described in more detail in 6 The number of Huffman tables defined by the DHT marker is determined from the length field An application needs to maintain a counter that is initialized with the value of the length field minus 2 Each time you read a table you subtract its length from the counter When the counter reaches zero all the tables have been read No padding is allowed in a DHT marker, so if the counter becomes negative the file is invalid

120 100 80 60 40 20 0

Pressure [MPa]

r The Rootkit and Vulnerability Scan attacks in group S2 are also grouped together in group r The ARP Poison attack in S4 and O5 is different from the other attacks r The Distributed DoS attack in S5 and O4 is different from the other attacks r The Remote Dictionary attack in S6 and O2 is different from the other attacks

Figure 5.7 Speci c volumetric work w [kJ kg 1] in pure water as function of different pressure level at 20 C according to Equation 5.12. The isothermal lines of w would be interfered with each other. At high pressure level, the function has linear behavior because compressibility becomes less.

1400 1200 1400 1200

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Description The 4 high-order bits specify the table class A value of 0 means a DC table, a value of 1 means an AC table The 4 low-order bits specify the table identifier This value is 0 or 1 for baseline frames and 0, 1, 2, or 3 for progressive and extended frames The count of Huffman codes of length 1 to 16 Each count is stored in 1 byte The 1-byte symbols sorted by Huffman code The number of symbols is the sum of the 16 code counts

The two attacks of Security Audit and Software Keylogger are grouped in S3 based on the same attack characteristics, but are considered different in separate groups based on the opposite attack characteristics Considering the large cluster distance of the S3 cluster, the two attacks in S3 can reasonably be separated Hardware Keylogger is also different from the other attacks since this attack behaves differently from the other attacks by not having any mean shift attack characteristics Hence, the attack groups can be classi ed into the following categories based on both the same attack characteristics and the opposite attack characteristics among the attacks Attack groups of similar behavior: Group 1: Apache Resource DoS, Fork Bomb, and FTP Buffer Over ow Group 2: Rootkit and Vulnerability Scan Attack groups of different behavior from other attacks: Group 3: ARP Poison Group 4: Distributed DoS Group 5: Remote Dictionary Group 6: Security Audit Group 7: Software Keylogger Group 8: Hardware Keylogger O1

r [kg m 3]

Pressure [MPa]

Table 87 gives the number of the mean increase characteristics for each object that are unique to each attack For example, for the Cache object, the Apache Resource DoS attack has two unique mean increase characteristics in Cache\Pin Reads/sec and Cache\Sync Pin Reads/sec which appear only in this attack The attacks of Fork Bomb, FTP Buffer Over ow and Rootkit have unique mean increase characteristics only in the Process object The Remote Dictionary attack has unique mean increase characteristics only in the LogicalDisk object The other attacks have unique mean increase characteristics in multiple objects Table 88 gives the number of the mean decrease characteristics that are unique to each attack For example, for the Cache object, the Rootkit attack has two unique mean decrease characteristics in Cache\Data Flushes/sec and Cache\Data Flush Pages/sec which appear only in this attack Since the mean increase characteristics of these two variables appear in the Security Audit attack, the mean decrease characteristics of these two variables in the Rootkit

1000 800 600 400 200 0 30

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