Strategically-Motivated Advanced Persistent Threat – Computers & Security

Atif Ahmad (University of Melbourne), Jeb Webb (Oceania Cyber Security Centre), James Boorman (Oceania Cyber Security Centre), and I have a new article accepted for publication in Computers & Security.

Advanced persistent threat (APT) is widely acknowledged to be the most sophisticated and potent class of security threat. APT refers to knowledgeable human attackers that are organized, highly sophisticated and motivated to achieve their objectives against a targeted organization(s) over a prolonged period. Strategically-motivated APTs or S-APTs are distinct in that they draw their objectives from the broader strategic agenda of third parties such as criminal syndicates, nation-states, and rival corporations. In this paper we review the use of the term “advanced persistent threat,” and present a formal definition. We then draw on military science, the science of organized conflict, for a theoretical basis to develop a rigorous and holistic model of the stages of an APT operation which we subsequently use to explain how S-APTs execute their strategically motivated operations using tactics, techniques and procedures. Finally, we present a general disinformation model, derived from situation awareness theory, and explain how disinformation can be used to attack the situation awareness and decision making of not only S-APT operators, but also the entities that back them.

AI and India – Brookings #TechTank

As artificial intelligence technologies take over larger number of tasks, India will face unique impacts of automation relative to other countries. With its large and young population, advances in AI will affect India in aspects from jobs to quality of life. Incidentally, the Indian economy is currently ill-equipped to face the advent of automation and AI. To read more...

Spatial-Temporal Effect of Household Solid Waste on Illegal Dumping – Journal of Cleaner Production

Along with colleagues Wenting Yang and Bo Fan, at Shanghai Jiao Tong University, I have a paper accepted at Journal of Cleaner Production.

Spatial-Temporal Effect of Household Solid Waste on Illegal Dumping

Illegal dumping is an increasingly costly problem with profoundly negative consequences for the livability and sustainability of our communities. The problem of illegal dumping is particularly acute in the developing world. While the literature is rich in descriptive studies on illegal dumping, few studies leverage large-scale spatial-temporal data through innovative analytical tools to study the actual dynamics of household illegal waste dumping. Our study aims to fill this gap by developing a multilevel theoretical model with which to illustrate the impact of illegal dumping. We explore the spatial-temporal distribution of illegal dumping cases using data mining. Next, we integrate datasets reflecting different levels into a hierarchical data structure organized by membership function. We then use a hierarchical generalized linear model to validate our multilevel model. The results indicate that the spatial factors have a significant relationship with illegal dumping, whereas the direct influence of temporal and community-level factors on illegal dumping is insignificant. Furthermore, the moderating effect of management level and public order on the relationship between spatial features and illegal dumping is significant. Based on our results, we offer several suggestions for preventing illegal dumping.