杀软影响测试数据记录 Day1

markdown 虽然说是Day1,但是摸鱼的我明显不会一天搞完,暂且算作第一段吧( 本段包含: - Base Line - Windows Defender - Kaspersky Free Antivirus - GDATA Antivirus 数据结构定义: ``` name,round,time(10^-6s),usability ``` 其中「可用性」定义为`5 - ((排除所需的额外不自然操作 - 1) / 2)`。 ## Base Line ``` none,1,32238426,5 none,2,32719690,5 none,3,32866807,5 ``` 这是没有任何杀软情况下的基准线。 ## Windows Defender version: 20191201 ``` wd,1,41449415,5 wd,2,35426191,5 wd,3,35548786,5 wd,1,40973951,5 wd,2,36079794,5 wd,3,35698385,5 ``` WD的测试数据可以看出明显的,在第一次测试后的下降趋势 ## KFA version:2020(e) ``` kaspersky,1,44065458,4 kaspersky,2,44829224,5 kaspersky,3,35838571,5 kaspersky,1,38798133,5 kaspersky,2,34887663,5 kaspersky,3,35615266,5 ``` 卡巴的测试数据同样展现出了下降的趋势,不出意料的话是KSN发挥了作用,在恢复快照后的第二次测试中消耗了额外的3s用于请求网络数据。 ## GDATA version:25.5.5.40 ``` gd,1,47323123,4 gd,2,41108207,4 gd,3,41361050,4 gd,1,44900977,4 gd,2,47476211,4 gd,3,41713014,4 ``` gd的自有A引擎在测试时将我的自制自解压「可疑程序」误报了,第一次时加白后测试得到的成绩,第二次为直接使用测试脚本跑的。 ## Day1 Summary 为了便于阅读,这里的y轴单位是ms(10^-3 s)。 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)

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