Protocol State Machine Reverse Engineering with a Teaching-Learning Approach

In this work, we propose a novel solution to the problem of inferring the state machine of an unknown protocol. We extend and improve prior results on inferring Mealy machines, and present a new algorithm that accesses and interacts with a networked system that runs the unknown protocol in order to infer the Mealy machine representing the protocol's state machine. To demonstrate the viability of our approach, we provide an implementation and illustrate the operation of our algorithm on a simple example protocol, as well as on two real-world protocols, Modbus and MQTT.

Learning and Solving Regular Decision Processes

Regular Decision Processes (RDPs) are a recently introduced model that extends MDPs with non-Markovian dynamics and rewards. The non-Markovian behavior is restricted to depend on regular properties of the history. These can be specified using regular expressions or formulas in linear dynamic logic over finite traces. Fully specified RDPs can be solved by compiling them into an appropriate MDP. Learning RDPs from data is a challenging problem that has yet to be addressed, on which we focus in this paper. Our approach rests on a new representation for RDPs using Mealy Machines that emit a distribution and an expected reward for each state-action pair. Building on this representation, we combine automata learning techniques with history clustering to learn such a Mealy machine and solve it by adapting MCTS to it. We empirically evaluate this approach, demonstrating its feasibility.

A Novel Design of Mealy Machine Equivalence in Vlsi Technology

In this paper begin of a Novel Design of Mealy Machine Equivalence in VLSI Technology. The pattern in structure and assembling of extremely huge scale incorporated circuit shows a progressing move towards littler gadgets on expanding wafer measurements. CMOS has become a common innovation because of its rapid and pressing thickness combined with low power utilization. New advances have risen to additionally expand circuit speed and to lessen structure and innovation limitations. Models are joined bipolar-CMOS (BICMOS) and CMOS in silicon on the cover (SOI). Other than the mass delivered standard chips exclusively custom-fitted application explicit IC (ASICs) and framework approaches with on-chip coordinated sensors or high power actuators gain significance. These improvements present difficulties in the progression of pillar testing techniques, for example, rapid or high spatial goals on 200 mm width wafers. We have mapped this paper to the Mealy machine equivalence Verilog HDL Code in the Xilinx Vivado Compiler Version v2014.2 (64-bit) and find the Power, utilization report, and Area, Power in Table One, utilization report in Table Two and Area in Table Three.

An Algorithm for Forward Reduction in Sequence-Based Software Specification

Sequence-based software specification is a rigorous method for deriving a formal system model based on informal requirements, through a systematic process called sequence enumeration. Under this process, stimulus (input) sequences are considered in a breadth-first manner, with the expected system response to each sequence given. Not every sequence needs to be further extended by the enumeration rules. The completed specification encodes a Mealy machine and forms a basis for other activities including code development and testing. This paper presents a forward reduction algorithm for sequence-based specification. The need for such an algorithm has been identified by field applications. We used the state machine as an intermediate tool to comprehend and analyze all change impacts resulted from a forward reduction, and used an axiom system for its development. We present the algorithm both mathematically in functional form and procedurally in pseudocode, illustrate it with a symbolic example, and report a larger case study from the published literature in which the algorithm is applied. The algorithm will prove useful and effective in deriving a system-level specification as well as in merging and combining partial work products towards a formal system model in field applications.