A true positive is an outcome where the model correctly predicts the positive case. Ex: Downloaded file is malware, and the A.V. detected it as malware. A true negative is an outcome where the model correctly predicts the negative case. Ex: Downloaded file is NOT malware, and the A.V. did NOT detect it as malware. A false positive is an outcome where the model incorrectly predicts the positive case. Ex: Downloaded file is NOT malware, but the A.V. detected it as malware. A false negative is an outcome where the model incorrectly predicts the negative case. Ex: Downloaded file is a malware, AV did NOT detect it as malware. True…

Attack surface. First thing I start thinking is the surface area, or the exposed area that is susceptible to a cyber onslaught by threat actors, or bad people with malicious intent. According to Wikipedia: “The attack surface of a software environment is the sum of the different points (for “attack vectors”) where an unauthorized user (the “attacker”) can try to enter data to or extract data from an environment. Keeping the attack surface as small as possible is a basic security measure.” via Wikipedia “KEEPING THE ATTACK SURFACE AS SMALL AS POSSIBLE IS A BASIC SECURITY MEASURE.” **clap, clap** Does that last line stick out to anyone else?? It should.…