Subrahmanian
Biographic Data
| ID | 203050 |
|---|---|
| NAME | Subrahmanian |
| FAMILY NAME | Subrahmanian |
| SIGNATURE | SUBRAHMANIAN |
| AFFILIATIONS | University of Maryland, College Park |
| ORCID | 0000-0001-7191-0296 |
| VERIFIED | Yes |
| TOTAL WORKS | 19 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 19 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2000 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Machine Learning Techniques to Predict Terrorist Attacks
The Impact of Strategic Communication in Coopetitive Multiagent Settings
We consider behavior of agents in a long-term multiagent coopetitive setting in which agents vary their cooperative and competitive stances over time. Using the game of Diplomacy as a testbed, we study how successful agents vary their coopetitive behavior, developing a new “style of play” (SoP) characterization of player behavior. We assess five novel SoP hypotheses about successful behavior. We propose two algorithms to automatically compute an …
SockDef
Fake reviews are having a devastating negative influence on online shopping sites. The proliferation of fake reviews is exacerbated by the presence of SockFarms, companies that create and operate huge sets of sockpuppet accounts to promote their customers’ products by posting fake reviews. Our proposed SockAttack algorithm allows such companies to optimize their actions to maximize profits. We show that SockAttack compromises the F1-score of four…
Linking Terrorist Network Structure to Lethality
Without measures of the lethality of terrorist networks, it is very difficult to assess if capturing or killing a terrorist is effective. We present the predictive lethality analysis of terrorist organization () algorithm, which merges machine learning with techniques from graph theory and social network analysis to predict the number of attacks that a terrorist network will carry out based on a network structure alone. We show that is highly acc…
A Machine Learning Based Model of Boko Haram
Understanding the timing of Chinese border incursions into India
Since the 1960s China and India have engaged in a dispute about the demarcation of their shared border. This territorial dispute led to a brief war in 1962, and recurring flare-ups over the following decades, including during the summer of 2020. The potential for further escalation of this dispute poses significant risks to Indian and Chinese civilians, US foreign policy objectives, and the stability of the international economic system. Despite …
Understanding Shifting Triadic Relationships in the Al-Qaeda/Isis Faction Ecosystem
We propose and investigate 14 hypotheses linking changes in the intensity of relationships between two factions in the Al-Qaeda/ISIS (AQ/ISIS) ecosystem to future changes in other relationships involving one of those two factions. Using a novel 28-year data set of relationships between factions of Al-Qaeda and the Islamic State (including their predecessor organizations) encoded as a time series of 267 signed weighted networks, we identify triang…
Pie
Although most game theory models assume that payoff matrices are provided as input, getting payoff matrices in strategic games (e.g., corporate negotiations and counter-terrorism operations) has proven difficult. To tackle this challenge, we propose a payoff inference engine (PIE) that finds payoffs assuming that players in a game follow a myopic best response or a regret minimization heuristic. This assumption yields a set of constraints (possib…
When Jihadist Factions Split
This article investigates group fragmentation in the al-Qaeda and Islamic State ecosystems, employing network analysis to examine the impact of specific network conditions on the probability of a faction splitting. Using new datasets of faction–faction (FF) and terrorist–terrorist (TT) relationships, the article tests 18 hypotheses exploring connections between factional splits and the number, polarity, and strength of FF and TT relationships, am…
Cyber Deception
Cyber Warfare
Scaling Subgraph Matching Queries in Huge Networks
Stun
Computational Analysis of Terrorist Groups
Computational Analysis of Terrorist Groups: Lashkar-e-Taiba provides an in-depth look at Web intelligence, and how advanced mathematics and modern computing technology can influence the insights we have on terrorist groups. This book primarily focuses on one famous terrorist group known as Lashkar-e-Taiba (or LeT), and how it operates. After 10 years of counter Al Qaeda operations, LeT is considered by many in the counter-terrorism community to b…
Handbook of Computational Approaches to Counterterrorism
Terrorist groups throughout the world have been studied primarily through the use of social science methods. However, major advances in IT during the past decade have led to significant new ways of studying terrorist groups, making forecasts, learning models of their behaviour, and shaping policies about their behaviour. Handbook of Computational Approaches to Counterterrorism provides the first in-depth look at how advanced mathematics and moder…
Indian Mujahideen
Advance Praise for Indian Mujahideen: Computational Analysis and Public Policy “This book presents a highly innovative computational approach to analyzing the strategic behavior of terrorist groups and formulating counter-terrorism policies. It would be very useful for international security analysts and policymakers.” Uzi Arad, National Security Advisor to the Prime Minister of Israel and Head, Israel National Security Council (2009-2011) “An im…
Betweenness computation in the single graph representation of hypergraphs
Cape
Applications Of Paraconsistency In Data And Knowledge Bases
When Jihadist Factions Split
This article investigates group fragmentation in the al-Qaeda and Islamic State ecosystems, employing network analysis to examine the impact of specific network conditions on the probability of a faction splitting. Using new datasets of faction–faction (FF) and terrorist–terrorist (TT) relationships, the article tests 18 hypotheses exploring connections between factional splits and the number, polarity, and strength of FF and TT relationships, am…
Applications Of Paraconsistency In Data And Knowledge Bases
Cape
Computational Analysis of Terrorist Groups
Computational Analysis of Terrorist Groups: Lashkar-e-Taiba provides an in-depth look at Web intelligence, and how advanced mathematics and modern computing technology can influence the insights we have on terrorist groups. This book primarily focuses on one famous terrorist group known as Lashkar-e-Taiba (or LeT), and how it operates. After 10 years of counter Al Qaeda operations, LeT is considered by many in the counter-terrorism community to b…
Handbook of Computational Approaches to Counterterrorism
Terrorist groups throughout the world have been studied primarily through the use of social science methods. However, major advances in IT during the past decade have led to significant new ways of studying terrorist groups, making forecasts, learning models of their behaviour, and shaping policies about their behaviour. Handbook of Computational Approaches to Counterterrorism provides the first in-depth look at how advanced mathematics and moder…
Indian Mujahideen
Advance Praise for Indian Mujahideen: Computational Analysis and Public Policy “This book presents a highly innovative computational approach to analyzing the strategic behavior of terrorist groups and formulating counter-terrorism policies. It would be very useful for international security analysts and policymakers.” Uzi Arad, National Security Advisor to the Prime Minister of Israel and Head, Israel National Security Council (2009-2011) “An im…
Betweenness computation in the single graph representation of hypergraphs
Scaling Subgraph Matching Queries in Huge Networks
Stun
Cyber Warfare
Cyber Deception
When Jihadist Factions Split
This article investigates group fragmentation in the al-Qaeda and Islamic State ecosystems, employing network analysis to examine the impact of specific network conditions on the probability of a faction splitting. Using new datasets of faction–faction (FF) and terrorist–terrorist (TT) relationships, the article tests 18 hypotheses exploring connections between factional splits and the number, polarity, and strength of FF and TT relationships, am…
Understanding Shifting Triadic Relationships in the Al-Qaeda/Isis Faction Ecosystem
We propose and investigate 14 hypotheses linking changes in the intensity of relationships between two factions in the Al-Qaeda/ISIS (AQ/ISIS) ecosystem to future changes in other relationships involving one of those two factions. Using a novel 28-year data set of relationships between factions of Al-Qaeda and the Islamic State (including their predecessor organizations) encoded as a time series of 267 signed weighted networks, we identify triang…
Pie
Although most game theory models assume that payoff matrices are provided as input, getting payoff matrices in strategic games (e.g., corporate negotiations and counter-terrorism operations) has proven difficult. To tackle this challenge, we propose a payoff inference engine (PIE) that finds payoffs assuming that players in a game follow a myopic best response or a regret minimization heuristic. This assumption yields a set of constraints (possib…
A Machine Learning Based Model of Boko Haram
Understanding the timing of Chinese border incursions into India
Since the 1960s China and India have engaged in a dispute about the demarcation of their shared border. This territorial dispute led to a brief war in 1962, and recurring flare-ups over the following decades, including during the summer of 2020. The potential for further escalation of this dispute poses significant risks to Indian and Chinese civilians, US foreign policy objectives, and the stability of the international economic system. Despite …
Linking Terrorist Network Structure to Lethality
Without measures of the lethality of terrorist networks, it is very difficult to assess if capturing or killing a terrorist is effective. We present the predictive lethality analysis of terrorist organization () algorithm, which merges machine learning with techniques from graph theory and social network analysis to predict the number of attacks that a terrorist network will carry out based on a network structure alone. We show that is highly acc…
SockDef
Fake reviews are having a devastating negative influence on online shopping sites. The proliferation of fake reviews is exacerbated by the presence of SockFarms, companies that create and operate huge sets of sockpuppet accounts to promote their customers’ products by posting fake reviews. Our proposed SockAttack algorithm allows such companies to optimize their actions to maximize profits. We show that SockAttack compromises the F1-score of four…
Machine Learning Techniques to Predict Terrorist Attacks
The Impact of Strategic Communication in Coopetitive Multiagent Settings
We consider behavior of agents in a long-term multiagent coopetitive setting in which agents vary their cooperative and competitive stances over time. Using the game of Diplomacy as a testbed, we study how successful agents vary their coopetitive behavior, developing a new “style of play” (SoP) characterization of player behavior. We assess five novel SoP hypotheses about successful behavior. We propose two algorithms to automatically compute an …
Computer Science (17 works) · Political science (11 works) · Law (10 works) · Terrorism (8 works) · Terrorism, Counterterrorism, and Political Violence (8 works) · Computer security (7 works) · Mathematics (7 works) · Psychology (7 works) · Complex Network Analysis Techniques (4 works) · Engineering (4 works)