{'fraction_non_alphanumeric': 0.03676470588235294, 'fraction_numerical': 0.0014705882352941176, 'mean_word_length': 5.330232558139535, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Analyzing Directional Modulation Techniques as Block Encryption Ciphers for Physical Layer Security

This paper presents a framework - PLR-Probe - consisting of two layers: (1) Mapping Layer and (2) Computing amp;amp; Decision Layer. In Mapping Layer (ML), the Directional Modulation Techniques (DMTs) are analyzed as block encryption ciphers by mapping their major components to the components of DMTs. The cryptographic strength of random stream of bits, received by eavesdropper in Physical Layer Security (PLS) techniques is explored and compared by Computing amp;amp; Decision Layer (CDL), with that of strong block ciphering algorithm (i.e. AES). To prove the effectiveness and relevance of the framework, we applied it on a recently proposed Antenna Subset Modulation (ASM) technique. We measured the cryptographic strength of the ASM technique by mapping it to a physical layer encryption method. The other major contribution is: using PLR-Probe, communication researchers can benchmark the cryptographic strength of any PLS technique with AES. In this paper, ASM is benchmarked against AES by using a novel metric (Physical Layer Randomness (PLR)). The analysis can be made comprehensive by considering PLR along with Symbol Error Rate (SER) and Secrecy Capacity (SC) as optimization parameters to improve the cryptographic strength of PLS techniques.