Optimal Personalized Defense Strategy Against Man-In-The-Middle Attack
Authors: Xiaohong Li, Shuxin Li, Jianye Hao, Zhiyong Feng, Bo An
AAAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we empirically evaluate our optimal defense strategy by comparing it with non-strategic defense strategies. The results indicate that our game-theoretic defense strategy significantly outperforms other non-strategic defense strategies in terms of decreasing the total losses against MITM attacks. |
| Researcher Affiliation | Academia | School of Computer Science and Technology Tianjin University, China; School of Computer Software Tianjin University, China; School of Computer Engineering Nanyang Technological University, Singapore |
| Pseudocode | Yes | The output of the following algorithm is an optimal defense strategy. 1. Compute l N i for every port i as follows: if p N i vi < λ, then l N i = F(p N i )ci; otherwise, l N i = F( λ vi )ci. 2. Compute l A i for every port i as follows: if p A i vi > λ, then l A i = p A i vi + F(p A i )ci; otherwise, l A i = λ vi vi + F( λ vi )ci. 3. Compute Di for every port i as follows: Di = l A i l N i . 4. Select the set S of ports with the lowest Di values. 5. For every i S, if p A i vi > λ, then pi = p A i ; otherwise, pi = λ vi . 6. For every i S, if p N i vi < λ, then pi = p N i ; otherwise, pi = λ |
| Open Source Code | No | No concrete access to source code (e.g., repository link, explicit release statement, or code in supplementary materials) for the methodology was found. |
| Open Datasets | No | We first introduce how a set of 30 user profiles are generated. Recall that the value of vi can be determined by the user s relative social level and status among all users in the organization. To make it concrete, we consider the following two different cases. In the first case, we assume that the values of vi follow the power law distribution. In the simulation, the communication protocol that we adopt is the Hyper Text Transport Protocol(HTTP) and the contents of packets are stochastic words. |
| Dataset Splits | No | The paper does not describe specific training, validation, or test dataset splits (e.g., percentages, sample counts, or citations to predefined splits). |
| Hardware Specification | No | No specific hardware details (e.g., GPU/CPU models, processor types, or memory amounts) used for running experiments were found. |
| Software Dependencies | No | No specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate the experiment were found. |
| Experiment Setup | No | The paper describes aspects of the simulation for deriving F(p), such as 'the communication protocol that we adopt is the Hyper Text Transport Protocol(HTTP) and the contents of packets are stochastic words' and 'varying the probability p within the range of [0,1]'. However, it does not provide specific hyperparameters like learning rates, batch sizes, or optimizer settings for a typical model training setup. |