Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remain...Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.展开更多
针对传统硬件描述语言(Verilog/VHDL)实现密码算法时代码复杂性高、开发周期长且调试困难等问题,本文提出了一种基于Chisel语言的轻量级分组密码算法LBlock的硬件实现方案。利用Chisel的高级硬件构建能力,通过模块化设计和有限状态机控...针对传统硬件描述语言(Verilog/VHDL)实现密码算法时代码复杂性高、开发周期长且调试困难等问题,本文提出了一种基于Chisel语言的轻量级分组密码算法LBlock的硬件实现方案。利用Chisel的高级硬件构建能力,通过模块化设计和有限状态机控制,高效地实现了密钥扩展、加密和解密核心模块。通过在Xilinx ISE Design Suite 14.7上综合后,结果表明,基于Chisel的LBlock算法实现方案在逻辑资源消耗和工作频率上均表现出优势。最高工作频率达到250.197MHz,加密吞吐率为485.815 Mbps,与传统的Verilog实现相比,本设计在显著降低代码量的同时,吞吐率提升了55.7%,为资源受限环境下的密码硬件实现提供了一种更敏捷、高效的设计思路。展开更多
基金This study is financed by the European Union-NextGenerationEU,through the National Recovery and Resilience Plan of the Republic of Bulgaria,Project No.BG-RRP-2.013-0001.
文摘Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.
文摘针对传统硬件描述语言(Verilog/VHDL)实现密码算法时代码复杂性高、开发周期长且调试困难等问题,本文提出了一种基于Chisel语言的轻量级分组密码算法LBlock的硬件实现方案。利用Chisel的高级硬件构建能力,通过模块化设计和有限状态机控制,高效地实现了密钥扩展、加密和解密核心模块。通过在Xilinx ISE Design Suite 14.7上综合后,结果表明,基于Chisel的LBlock算法实现方案在逻辑资源消耗和工作频率上均表现出优势。最高工作频率达到250.197MHz,加密吞吐率为485.815 Mbps,与传统的Verilog实现相比,本设计在显著降低代码量的同时,吞吐率提升了55.7%,为资源受限环境下的密码硬件实现提供了一种更敏捷、高效的设计思路。
