The Deepfake algorithm allows its user to create fake images, audios, videos that gives very real impression but is fake in real sense. This degree of technology is achieved due to advancements in Deep Learning, Machine Learning, Artificial Intelligence and Neural Networking that is a combination of algorithms like generative adversarial network (GAN), autoencoders etc. Any technology has its positive and negative repercussions. Deep fake can come in use for helping people who have lost their speech to give them new improved voice, commercially deepfake can be used in improving animation or movie quality putting in creative imagination to work as well is therapeutic to people who have lost their dear once. Negative aspects of deep fake include creating fake images, videos, audios that look very real can cause threats to an individual’s privacy, organizations, democracy, and even national security. This review paper presents history on how deep fake emerged, will comprehend on how it works including various algorithms, major research works done on understanding deep fakes in the literature and most importantly discuss recent advancements in detection of deep fake methods and its robust preventive measures.

HIV is one of the most dreaded diseases of the century. Throughout the world efforts are underway to develop new vaccines and design new drugs so as to combat this viral menace. In an effort to probe deeper into the functioning of these viruses we present association based rules formulation so as to decipher the most frequently occurring amino acids in these viruses. This is a novel attempt of its kind since we are attempting to find put the most informative association rules using Apriori algorithm implemented through WEKA. The information generated can be of great use to molecular biologists and drug designers since the associated amino acids can be a very good drug targets.Our findings suggest that L-Selenocysteine and L-Pyrrolysine are most frequently associated amino acids in the 4 classes of virulent proteins analyzed for association rules and Cyteine and Arginine show the strongest association in one of the class analyzed i.e. Gp41. Hence these can be potential drug candidates.