论文标题
智能密码猜测技术利用上下文信息和OSINT
Smarter Password Guessing Techniques Leveraging Contextual Information and OSINT
论文作者
论文摘要
近几十年来,犯罪分子越来越多地利用网络来研究,协助和实施犯罪行为。执法与这种不断增长的趋势作斗争的最重要方法之一是及时访问有关嫌疑人的相关信息。对此的重大障碍是访问怀疑嫌疑人使用的任何系统需要通过密码进行身份验证的系统的困难。密码猜测技术通常在生成密码时考虑常见的用户行为以及制定的密码策略。考虑到大/平均人口,这种技术可以提供适中的成功率。但是,当专注于一个目标时,它们往往会失败 - 尤其是当后者是受过教育的用户以预防措施作为精明的罪犯的用户时。为了获取有关嫌疑人的有用信息,开源智能越来越多地利用开源智能,但是目前几乎没有完成以自动化的方式集成这些知识,以在密码破解中。这项研究的目的是深入研究有关犯罪嫌疑人必要环境的技术,并找到在密码猜测技术中利用此信息的方法。
In recent decades, criminals have increasingly used the web to research, assist and perpetrate criminal behaviour. One of the most important ways in which law enforcement can battle this growing trend is through accessing pertinent information about suspects in a timely manner. A significant hindrance to this is the difficulty of accessing any system a suspect uses that requires authentication via password. Password guessing techniques generally consider common user behaviour while generating their passwords, as well as the password policy in place. Such techniques can offer a modest success rate considering a large/average population. However, they tend to fail when focusing on a single target -- especially when the latter is an educated user taking precautions as a savvy criminal would be expected to do. Open Source Intelligence is being increasingly leveraged by Law Enforcement in order to gain useful information about a suspect, but very little is currently being done to integrate this knowledge in an automated way within password cracking. The purpose of this research is to delve into the techniques that enable the gathering of the necessary context about a suspect and find ways to leverage this information within password guessing techniques.