Smartphone Data Protection Using Mobile Usage Pattern Matching

2011 ◽  
pp. 23-39
Author(s):  
Wen-Chen Hu ◽  
Naima Kaabouch ◽  
S. Hossein Mousavinezhad ◽  
Hung-Jen Yang
Keyword(s):  
Pattern Matching ◽  
Data Protection ◽  
Finite Automata ◽  
String Matching ◽  
Handheld Devices ◽  
Approximate String Matching ◽  
Usage Pattern ◽  
Usage Patterns ◽  
Novel Approaches

Handheld devices like smartphones must include rigorous and convenient handheld data protection in case the devices are lost or stolen. This research proposes a set of novel approaches to protecting handheld data by using mobile usage pattern matching, which compares the current handheld usage pattern to the stored usage patterns. If they are drastic different, a security action such as requiring a password entry is activated. Various algorithms of pattern matching can be used in this research. Two of them are discussed in this chapter: (i) approximate usage string matching and (ii) usage finite automata. The first method uses approximate string matching to check device usage and the second method converts the usage tree into a deterministic finite automaton (DFA). Experimental results show this method is effective and convenient for handheld data protection, but the accuracy may need to be improved.

Parallel Combining Different Approaches to Multi-pattern Matching for Fpga-based Security Systems

2017 ◽  
Vol 5 (1) ◽  
pp. 8-15
Author(s):  
Sergii Hilgurt ◽  
Keyword(s):  
Information Security ◽  
Pattern Matching ◽  
Intrusion Detection System ◽  
Detection System ◽  
Finite Automata ◽  
Network Intrusion Detection ◽  
Security Systems ◽  
Analytical Technique ◽  
Network Intrusion ◽  
Pros And Cons

The multi-pattern matching is a fundamental technique found in applications like a network intrusion detection system, anti-virus, anti-worms and other signature- based information security tools. Due to rising traffic rates, increasing number and sophistication of attacks and the collapse of Moore’s law, traditional software solutions can no longer keep up. Therefore, hardware approaches are frequently being used by developers to accelerate pattern matching. Reconfigurable FPGA-based devices, providing the flexibility of software and the near-ASIC performance, have become increasingly popular for this purpose. Hence, increasing the efficiency of reconfigurable information security tools is a scientific issue now. Many different approaches to constructing hardware matching circuits on FPGAs are known. The most widely used of them are based on discrete comparators, hash-functions and finite automata. Each approach possesses its own pros and cons. None of them still became the leading one. In this paper, a method to combine several different approaches to enforce their advantages has been developed. An analytical technique to quickly advance estimate the resource costs of each matching scheme without need to compile FPGA project has been proposed. It allows to apply optimization procedures to near-optimally split the set of pattern between different approaches in acceptable time.

BORDERS AND FINITE AUTOMATA

2007 ◽  
Vol 18 (04) ◽  
pp. 859-871
Author(s):  
MARTIN ŠIMŮNEK ◽  
BOŘIVOJ MELICHAR
Keyword(s):  
Pattern Matching ◽  
Hamming Distance ◽  
Finite Automata ◽  
Music Analysis ◽  
Theoretical Description ◽  
Specific Form ◽  
Distance Measures ◽  
Computer Assisted ◽  
Finite State ◽  
Finite State Transducer

A border of a string is a prefix of the string that is simultaneously its suffix. It is one of the basic stringology keystones used as a part of many algorithms in pattern matching, molecular biology, computer-assisted music analysis and others. The paper offers the automata-theoretical description of Iliopoulos's ALL_BORDERS algorithm. The algorithm finds all borders of a string with don't care symbols. We show that ALL_BORDERS algorithm is an implementation of a finite state transducer of specific form. We describe how such a transducer can be constructed and what should be the input string like. The described transducer finds a set of lengths of all borders. Last but not least, we define approximate borders and show how to find all approximate borders of a string when we concern Hamming distance definition. Our solution of this problem is based on transducers again. This allows us to use analogy with automata-based pattern matching methods. Finally we discuss conditions under which the same principle can be used for other distance measures.

Sublinear approximate string matching and biological applications

Algorithmica ◽  
1994 ◽  
Vol 12 (4-5) ◽  
pp. 327-344 ◽  
Author(s):  
W. I. Chang ◽  
E. L. Lawler
Keyword(s):  
String Matching ◽  
Approximate String Matching ◽  
Biological Applications

scholarly journals Weak factor automata: the failure of failure factor oracles?

2014 ◽  
Vol 53 ◽  
Author(s):  
Loek Cleophas ◽  
Derrick G. Kourie ◽  
Bruce W. Watson
Keyword(s):  
Pattern Matching ◽  
Dna Sequences ◽  
Finite Automata ◽  
Compact Representation ◽  
Data Sets ◽  
Matching Algorithm ◽  
Weak Factor ◽  
Ex Post ◽  
Ex Post Facto ◽  
Matching Performance

In indexing of, and pattern matching on, DNA and text sequences, it is often important to represent all factors of a sequence. One efficient, compact representation is the factor oracle (FO). At the same time, any classical deterministic finite automata (DFA) can be transformed to a so-called failure one (FDFA), which may use failure transitions to replace multiple symbol transitions, potentially yielding a more compact representation. We combine the two ideas and directly construct a failure factor oracle (FFO) from a given sequence, in contrast to ex post facto transformation to an FDFA. The algorithm is suitable for both short and long sequences. We empirically compared the resulting FFOs and FOs on number of transitions for many DNA sequences of lengths 4 − 512, showing gains of up to 10% in total number of transitions, with failure transitions also taking up less space than symbol transitions. The resulting FFOs can be used for indexing, as well as in a variant of the FO-using backward oracle matching algorithm. We discuss and classify this pattern matching algorithm in terms of the keyword pattern matching taxonomies of Watson, Cleophas and Zwaan. We also empirically compared the use of FOs and FFOs in such backward reading pattern matching algorithms, using both DNA and natural language (English) data sets. The results indicate that the decrease in pattern matching performance of an algorithm using an FFO instead of an FO may outweigh the gain in representation space by using an FFO instead of an FO.

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