// ------------ # Code for extracting traffic generated by a device within x seconds of a trigger # ------------
// Paths to input and output files (consider supplying these as arguments instead) and IP of the device for
// which traffic is to be extracted:
- String path = "/scratch/July-2018"; // Rahmadi
-// String path = "/Users/varmarken/temp/UCI IoT Project/experiments"; // Janus
- boolean verbose = false;
+// String path = "/scratch/July-2018"; // Rahmadi
+ String path = "/Users/varmarken/temp/UCI IoT Project/experiments"; // Janus
+ boolean verbose = true;
final String onPairsPath = "/scratch/July-2018/on.txt";
final String offPairsPath = "/scratch/July-2018/off.txt";
Map<String, Map<String, List<Conversation>>> ons = new HashMap<>();
// Contains all OFF events: hostname -> sequence identifier -> list of conversations with that sequence
Map<String, Map<String, List<Conversation>>> offs = new HashMap<>();
-
- if (verbose) {
- userActionsToConvsByHostname.forEach((ua, hostnameToConvs) -> {
- Map<String, Map<String, List<Conversation>>> outer = ua.getType() == Type.TOGGLE_ON ? ons : offs;
- hostnameToConvs.forEach((host, convs) -> {
- Map<String, List<Conversation>> seqsToConvs = TcpConversationUtils.
- groupConversationsByPacketSequenceVerbose(convs);
- outer.merge(host, seqsToConvs, (oldMap, newMap) -> {
- newMap.forEach((sequence, cs) -> oldMap.merge(sequence, cs, (list1, list2) -> {
- list1.addAll(list2);
- return list1;
- }));
- return oldMap;
- });
- });
- });
- } else {
- userActionsToConvsByHostname.forEach((ua, hostnameToConvs) -> {
- Map<String, Map<String, List<Conversation>>> outer = ua.getType() == Type.TOGGLE_ON ? ons : offs;
- hostnameToConvs.forEach((host, convs) -> {
- Map<String, List<Conversation>> seqsToConvs = TcpConversationUtils.
- groupConversationsByPacketSequence(convs);
- outer.merge(host, seqsToConvs, (oldMap, newMap) -> {
- newMap.forEach((sequence, cs) -> oldMap.merge(sequence, cs, (list1, list2) -> {
- list1.addAll(list2);
- return list1;
- }));
- return oldMap;
- });
+ userActionsToConvsByHostname.forEach((ua, hostnameToConvs) -> {
+ Map<String, Map<String, List<Conversation>>> outer = ua.getType() == Type.TOGGLE_ON ? ons : offs;
+ hostnameToConvs.forEach((host, convs) -> {
+ Map<String, List<Conversation>> seqsToConvs = TcpConversationUtils.
+ groupConversationsByPacketSequence(convs, verbose);
+ outer.merge(host, seqsToConvs, (oldMap, newMap) -> {
+ newMap.forEach((sequence, cs) -> oldMap.merge(sequence, cs, (list1, list2) -> {
+ list1.addAll(list2);
+ return list1;
+ }));
+ return oldMap;
});
});
- }
+ });
// Print out all the pairs into a file for ON events
// <<< Some work-in-progress/explorative code that extracts a "representative" sequence >>>
//
// Currently need to know relevant hostname in advance :(
-// String hostname = "events.tplinkra.com";
+ String hostname = "events.tplinkra.com";
// String hostname = "rfe-us-west-1.dch.dlink.com";
-// // Conversations with 'hostname' for ON events.
-// List<Conversation> onsForHostname = new ArrayList<>();
-// // Conversations with 'hostname' for OFF events.
-// List<Conversation> offsForHostname = new ArrayList<>();
-// // "Unwrap" sequence groupings in ons/offs maps.
-// ons.get(hostname).forEach((k,v) -> onsForHostname.addAll(v));
-// offs.get(hostname).forEach((k,v) -> offsForHostname.addAll(v));
-//
-//
-// Map<String, List<Conversation>> onsForHostnameGroupedByTlsAppDataSequence = TcpConversationUtils.groupConversationsByTlsApplicationDataPacketSequence(onsForHostname);
-//
-//
-// // Extract representative sequence for ON and OFF by providing the list of conversations with
-// // 'hostname' observed for each event type (the training data).
-// SequenceExtraction seqExtraction = new SequenceExtraction();
-//// ExtractedSequence extractedSequenceForOn = seqExtraction.extract(onsForHostname);
-//// ExtractedSequence extractedSequenceForOff = seqExtraction.extract(offsForHostname);
-//
-// ExtractedSequence extractedSequenceForOn = seqExtraction.extractByTlsAppData(onsForHostname);
-// ExtractedSequence extractedSequenceForOff = seqExtraction.extractByTlsAppData(offsForHostname);
-//
-// // Let's check how many ONs align with OFFs and vice versa (that is, how many times an event is incorrectly
-// // labeled).
-// int onsLabeledAsOff = 0;
-// Integer[] representativeOnSeq = TcpConversationUtils.getPacketLengthSequence(extractedSequenceForOn.getRepresentativeSequence());
-// Integer[] representativeOffSeq = TcpConversationUtils.getPacketLengthSequence(extractedSequenceForOff.getRepresentativeSequence());
-// SequenceAlignment<Integer> seqAlg = seqExtraction.getAlignmentAlgorithm();
-// for (Conversation c : onsForHostname) {
-// Integer[] onSeq = TcpConversationUtils.getPacketLengthSequence(c);
-// if (seqAlg.calculateAlignment(representativeOffSeq, onSeq) <= extractedSequenceForOff.getMaxAlignmentCost()) {
-// onsLabeledAsOff++;
-// }
-// }
-// int offsLabeledAsOn = 0;
-// for (Conversation c : offsForHostname) {
-// Integer[] offSeq = TcpConversationUtils.getPacketLengthSequence(c);
-// if (seqAlg.calculateAlignment(representativeOnSeq, offSeq) <= extractedSequenceForOn.getMaxAlignmentCost()) {
-// offsLabeledAsOn++;
-// }
-// }
-// System.out.println("");
+ // Conversations with 'hostname' for ON events.
+ List<Conversation> onsForHostname = new ArrayList<>();
+ // Conversations with 'hostname' for OFF events.
+ List<Conversation> offsForHostname = new ArrayList<>();
+ // "Unwrap" sequence groupings in ons/offs maps.
+ ons.get(hostname).forEach((k,v) -> onsForHostname.addAll(v));
+ offs.get(hostname).forEach((k,v) -> offsForHostname.addAll(v));
+
+
+ Map<String, List<Conversation>> onsForHostnameGroupedByTlsAppDataSequence = TcpConversationUtils.groupConversationsByTlsApplicationDataPacketSequence(onsForHostname);
+
+
+ // Extract representative sequence for ON and OFF by providing the list of conversations with
+ // 'hostname' observed for each event type (the training data).
+ SequenceExtraction seqExtraction = new SequenceExtraction();
+// ExtractedSequence extractedSequenceForOn = seqExtraction.extract(onsForHostname);
+// ExtractedSequence extractedSequenceForOff = seqExtraction.extract(offsForHostname);
+
+ ExtractedSequence extractedSequenceForOn = seqExtraction.extractByTlsAppData(onsForHostname);
+ ExtractedSequence extractedSequenceForOff = seqExtraction.extractByTlsAppData(offsForHostname);
+
+ // Let's check how many ONs align with OFFs and vice versa (that is, how many times an event is incorrectly
+ // labeled).
+ int onsLabeledAsOff = 0;
+ Integer[] representativeOnSeq = TcpConversationUtils.getPacketLengthSequence(extractedSequenceForOn.getRepresentativeSequence());
+ Integer[] representativeOffSeq = TcpConversationUtils.getPacketLengthSequence(extractedSequenceForOff.getRepresentativeSequence());
+ SequenceAlignment<Integer> seqAlg = seqExtraction.getAlignmentAlgorithm();
+ for (Conversation c : onsForHostname) {
+ Integer[] onSeq = TcpConversationUtils.getPacketLengthSequence(c);
+ if (seqAlg.calculateAlignment(representativeOffSeq, onSeq) <= extractedSequenceForOff.getMaxAlignmentCost()) {
+ onsLabeledAsOff++;
+ }
+ }
+ int offsLabeledAsOn = 0;
+ for (Conversation c : offsForHostname) {
+ Integer[] offSeq = TcpConversationUtils.getPacketLengthSequence(c);
+ if (seqAlg.calculateAlignment(representativeOnSeq, offSeq) <= extractedSequenceForOn.getMaxAlignmentCost()) {
+ offsLabeledAsOn++;
+ }
+ }
+ System.out.println("");
// ================================================================================================
projects / pingpong.git / blobdiff