Claims Analysis
Total Claims: 32
Claim 1
Independent Claim
165 words
A method of detecting the likelihood of the presence of any of a first set of known data traits in a data string, by use of a second set G of generic features and a third set S of signatures, wherein the generic features and the signatures are characteristic of said first set of data traits, said method comprising the steps of: a) loading the set G into a memory of a computer, b) locating occurrences within the data string of each generic feature in said set G, c) applying a first mapping from the occurrences located during step b) to obtain a subset S* of S, d) loading all signatures from the subset S* into a memory of said computer, e) locating occurrences within said data string of all signatures from the subset S*, and f) applying a second mapping from the occurrences located during step e) to identify a set of data traits that are likely to be present in the data string.
Claim 2
Independent Claim
165 words
A method of detecting the likelihood of the presence of any of a first set of known data traits in a data string, by use of a second set G of generic features and a third set S of signatures, wherein the generic features and the signatures are characteristic of said first set of data traits, said method comprising the steps of: a) loading the set G into a memory of a computer, b) locating occurrences within the data string of each generic feature in said set G, c) applying a first mapping from the occurrences located during step b) to obtain a subset S* of S, d) loading all signatures from the subset S* into a memory of said computer, e) locating occurrences within said data string of all signatures from the subset S*, and f) applying a second mapping from the occurrences located during step e) to identify a set of data traits that are likely to be present in the data string.
Claim 3
Dependent Claim
111 words
A method as set forth in claim 1, in which said first mapping comprises: c1) retrieving, for each generic feature occurring at least once in the data string, an associated list of signatures of said set S from a first lookup table, c2) concatenating all of the retrieved associated signature lists to form a concatenated signature list, c3) tallying the number of occurrences of each signature within the concatenated signature list, and c4) forming said subset S* from all signatures s for which the tallied number of occurrences in the concatenated signature list is not less than a threshold for s computed from a value obtained from a second lookup table.
Claim 4
Dependent Claim
141 words
A method as set forth in claim 2, in which the first lookup table is derived automatically from a collection of data strings, each data string possessing at least one of the data traits, comprising the steps of: L1a) locating all occurrences of each generic feature of set G and each signature of set S within each data string in said collection, L1b) defining an associated feature list for each signature s, consisting of all generic features that occur in every member of a defined subset of the set of said data strings in which said signature s is present, L1c) defining, for each generic feature g, an associated signature list of all signatures that include g among their associated feature lists, and L1d) forming said first lookup table by storing each generic feature g with the associated signature list thereof.
Claim 5
Dependent Claim
34 words
A method as set forth in claim 3, wherein the defined subset of the set of said data strings in which said signature s is present is the set of said data strings itself.
Claim 6
Dependent Claim
123 words
A method as set forth in claim 3, wherein the defined subset of the set of said data strings in which said signature s is present is derived from said set of data strings and a set of at most one supplied set of associated data traits for each data string, comprising the steps of: a) including each data string in said set of data strings in said subset of data strings, and b) for each data string in said set for which a set of associated data traits has been supplied, eliminating that data string from said subset if its supplied set of associated data traits and the data traits associated with s by said second mapping contain no common data traits.
Claim 7
Dependent Claim
149 words
A method as set forth in claim 2, in which the second lookup table is derived automatically from a collection of data strings, each data string possessing at least one of the data traits, comprising the steps of: L2a) locating all occurrences of each generic feature of set G and each signature of set S within each data string in the collection, L2b) for each signature s, i) defining an associated feature list for each signature s, consisting of all generic features that occur in every member of a defined subset of the set of said data strings in which said signature s is present, ii) tallying the number of distinct generic features within said associated feature list, and iii) computing a function of said tally for said signature s, and L2c) forming said second lookup table by storing each signature s with the function of said tally thereof.
Claim 8
Dependent Claim
19 words
A method as set forth in claim 6, in which the function of the tally is the tally itself.
Claim 9
Dependent Claim
31 words
A method as set forth in claim 6, in which the function of the tally is the greater of a first chosen constant or the tally minus a second chosen constant.
Claim 10
Dependent Claim
43 words
A method as set forth in claim 1, comprising the further step, in dependence upon whether any identified set of data traits is likely to be present in said data string, of signaling the identity of the data traits of said identified set.
Claim 11
Dependent Claim
38 words
A method as set forth in claim 1, comprising the further step, in dependence upon whether any signatures are loaded in to memory pursuant to step (d), of freeing said signatures from memory after carrying out step (e).
Claim 12
Dependent Claim
29 words
A method as set forth in claim 1, comprising the further step, in dependence upon whether any signatures are loaded in to memory, of caching said signatures in memory.
Claim 13
Dependent Claim
19 words
A method as set forth in claim 1, 2, 3, or 6, wherein the data traits are computer viruses.
Claim 14
Dependent Claim
27 words
A method as set forth in claim 1, 2, 3, or 6, wherein each data trait is a property of having been compiled by a specific compiler.
Claim 15
Dependent Claim
31 words
A method as set forth in claim 1, 2, 3, or 6, wherein each data trait is a computer virus identifiable by at least one signature of said third set S.
Claim 16
Dependent Claim
52 words
A method as set forth in claim 1, 2, 3, or 6, wherein each data trait is a computer virus identifiable by at least one signature of said third set S, said second set G of generic features requiring a smaller memory size for storage than said third set S of signatures.
Claim 17
Dependent Claim
189 words
A program storage device readable by a computing machine, tangibly embodying a program of instructions executable by the machine to perform method steps of a method of detecting the likelihood of the presence of any of a first set of known data traits in a data string, by use of a second set G of generic features and a third set S of signatures, wherein the generic features and the signatures are characteristic of said first set of data traits, said method comprising the steps of: a) loading the set G into a memory of a computer, b) locating occurrences within the data string of each generic feature in said set G, c) applying a first mapping from the occurrences located during step b) to a subset S* of S, d) loading all signatures from the subset S* into a memory of said computer, e) locating all occurrences within said data string of all signatures from the subset S*, and f) applying a second mapping from the occurrences located during step e) to identify a set of data traits that are likely to be present in the data string.
Claim 18
Dependent Claim
189 words
A program storage device readable by a computing machine, tangibly embodying a program of instructions executable by the machine to perform method steps of a method of detecting the likelihood of the presence of any of a first set of known data traits in a data string, by use of a second set G of generic features and a third set S of signatures, wherein the generic features and the signatures are characteristic of said first set of data traits, said method comprising the steps of: a) loading the set G into a memory of a computer, b) locating occurrences within the data string of each generic feature in said set G, c) applying a first mapping from the occurrences located during step b) to a subset S* of S, d) loading all signatures from the subset S* into a memory of said computer, e) locating all occurrences within said data string of all signatures from the subset S*, and f) applying a second mapping from the occurrences located during step e) to identify a set of data traits that are likely to be present in the data string.
Claim 19
Dependent Claim
114 words
A program storage device as set forth in claim 16, in which said first mapping comprises: c1) retrieving, for each generic feature occurring at least once in the data string, an associated list of signatures of said set S from a first lookup table, c2) concatenating all of the retrieved associated signature lists to form a concatenated signature list, c3) tallying the number of occurrences of each signature present within the concatenated signature list, and c4) forming said subset S* from all signatures s for which the tallied number of occurrences in the concatenated signature list is not less than a threshold for s computed from a value obtained from a second lookup table.
Claim 20
Dependent Claim
144 words
A program storage device as set forth in claim 17, in which the first lookup table is derived automatically from a collection of data strings, each data string possessing at least one of the data traits, comprising the steps of: L1a) locating all occurrences of each generic feature of set G and each signature of set S within each data string in said collection, L1 b) defining an associated feature list for each signature s, consisting of all generic features that occur in every member of a defined subset of the set of said data strings in which said signature s is present, L1c) defining, for each generic feature g, an associated signature list of all signatures that include g among their associated feature lists, and L1d) forming said first lookup table by storing each generic feature g with the associated signature list thereof.
Claim 21
Dependent Claim
34 words
A method as set forth in claim 18, wherein the defined subset of the set of said data strings in which said signature s is present is the set of said data strings itself.
Claim 22
Dependent Claim
123 words
A method as set forth in claim 18, wherein the defined subset of the set of said data strings in which said signature s is present is derived from said set of data strings and a set of at most one supplied set of associated data traits for each data string, comprising the steps of: a) including each data string in said set of data strings in said subset of data strings, and b) for each data string in said set for which a set of associated data traits has been supplied, eliminating that data string from said subset if its supplied set of associated data traits and the data traits associated with s by said second mapping contain no common data traits.
Claim 23
Dependent Claim
151 words
A program storage device as set forth in claim 17, in which the second lookup table is derived automatically from a collection of data strings, each data string possessing at least one of the data traits, comprising the steps of: L2a) locating all occurrences of each generic feature of set G and each signature of set S within each data string in the collection, L2b) for each signature s, i) defining an associated feature list for each signature s, consisting of all generic features that occur in every member of a defined subset of the set of said data strings in which said signature s is present, ii) tallying the number of distinct generic features within said associated feature list, and iii) computing a function of said tally for said signature s, and L2c) forming said second lookup table by storing each signature s with the function of said tally thereof.
Claim 24
Dependent Claim
21 words
A program storage device as set forth in claim 19, in which the function of the tally is the tally itself.
Claim 25
Dependent Claim
33 words
A program storage device as set forth in claim 19, in which the function of the tally is the greater of a first chosen constant or the tally minus a second chosen constant.
Claim 26
Dependent Claim
45 words
A program storage device as set forth in claim 16, comprising the further step, in dependence upon whether any identified set of data traits is likely to be present in said data string, of signaling the identity of the data traits of said identified set.
Claim 27
Dependent Claim
40 words
A program storage device as set forth in claim 16, comprising the further step, in dependence upon whether any signatures are loaded in to memory pursuant to step (d), of freeing said signatures from memory after carrying out step (e).
Claim 28
Dependent Claim
31 words
A program storage device as set forth in claim 16, comprising the further step, in dependence upon whether any signatures are loaded in to memory, of caching said signatures in memory.
Claim 29
Dependent Claim
21 words
A program storage device as set forth in claim 16, 17, 18, or 19, wherein the data traits are computer viruses.
Claim 30
Dependent Claim
29 words
A program storage device as set forth in claim 16, 17, 18, or 19, wherein each data trait is a property of having been compiled by a specific compiler.
Claim 31
Dependent Claim
33 words
A program storage device as set forth in claim 16, 17, 18, or 19, wherein each data trait is a computer virus identifiable by at least one signature of said third set S.
Claim 32
Dependent Claim
54 words
A program storage device as set forth in claim 16, 17, 18, or 19, wherein each data trait is a computer virus identifiable by at least one signature of said third set S, said second set G of generic features requiring a smaller memory size for storage than said third set S of signatures.