AI, Robotics and Cyber: How Much will They Change ...

4 downloads 0 Views 5MB Size Report
Google's DeepMind defeats reigning AlphaGo Champion (2016). Many products of AI research are so common they no longer perceived as AI by the users: ...

UNCLASSIFIED//APPROVED FOR UNCLASSIFIED//APPROVED FOR PUBLIC PUBLICRELEASE RELEASE

AI, Robotics and Cyber: How Much will They Change C2? Dr. Alexander Kott ARL Chief Scientist UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

B3 and C2 Command and Control BOTS (AI)

BITS (Cyber)

2

UNCLASSIFIED

BODIES (Human)

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

AI, Cyber, Humans in a Very Complex World

3

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Everything is Connected

• AI is making the world more intelligent • AI makes the world harder to manage • AI makes the world more vulnerable to cyber • Humans make C2 more vulnerable • Humans complicated things for AI • Humans can add resilience • Cyber thrives on attacking AI • Cyber and humans don’t mix well • Cyber defense will benefit from AI

4

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

AI and Cyber Make C2 Increasingly Complex

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Intelligent Things will be Diverse

Munitions

Sensors Weapons Wearable Devices

Robots

Vehicles

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

They will Perform a Variety of Tasks Sense

Attack

Collect & Process Information Fix

Sustain

Collaborate

Communicate

Defend

with each other & human Soldiers

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Managing and Adapting

Number of nodes for a future Army brigade might be several orders of magnitude greater than in current practice

Million Things per square kilometer is not an unreasonable expectation

Can be advantageous: availability of very large, densely-positioned number of Things, such as sensors

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Human Cognition will be Challenged The human cognition bandwidth will emerge as the most severe constraint. Humans seek infor mation that is: Well-formed Reasonably-sized Essential Highly relevant to their current situation and mission Unless information is useful, it is likely to do more harm than good

Similar concerns apply to all intelligent things

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Human Cognition will be Challenged - 2 Will far exceed advances predicted by Moore’s Law Will far exceed any likely improvements in bandwidth

Volume and complexity of information will be truly unprecedented in their extent

Similarly, trustworthiness and value of information arriving from different things will be highly variable Compression and fusion of data into information would have to be by a factor of 10^15

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Complexity of Intelligent Things: Use it as a Smoke Screen?

Friendly forces will be challenged to find, manage, aggregate information Any one device and its information is vulnerable to cyber or physical capture Use Intelligent Things to disperse friendly information, make any one device useless to the adversary Increase resiliency of C2, confuse and deceive the adversary Kott, A., Swami, A., and West, B., "The Fog of War in Cyberspace," IEEE Computer, November 2016

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

AI and Cyber Make C2 Increasingly Vulnerable

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

They will Have to Deal with the Adversary

Adversarial nature of the environment is the primary concern

Kinetic Directed Energy Electronic Attacks Against its Things Jamming RF Channels Destroying Fiber Channels Depriving Things of their Power Sources Electronic Eavesdropping Deploying Malware

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Humans are Especially Vulnerable Perhaps most importantly, the enemy attacks the cognition of human Soldiers Humans will be “Intelligent Things” that are most susceptible to deceptions Humans’ use of C2 will be handicapped when they are concerned (even if incorrectly) that the information is untrustworthy

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

AI will Fight Cyber Attacks

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Intelligent Cyber Agents

The battle of Cyber domain will continue to grow in significance Offense is stronger than defense Intelligent cyber agents are a possible answer 16

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Intelligent Cyber Agents

Stymie the enemy’s cyber intrusions by believable honeypots and honeynets

Fight back by anomaly detection that can highlight unexpected patterns

Use continuous learning process

Large-scale physical fingerprinting

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Can We Build Defensive Intelligent Agents?

Managing a variety of responses is error-prone Core machine intelligence must reside on-board

ADS is a prototype unified framework for on-board plug-in active defenses ELIDE is learning-based tool for extremely light, on-board intrusion detection

Chang, Raymond J., Richard E. Harang, and Garrett S. Payer; Extremely UNCLASSIFIED Lightweight Intrusion Detection (ELIDe); ARL, 2013

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Resilience will Replace Security

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Definition

Resilience is a property of a system defined by the National Academy of Sciences (NAS) as “the ability to prepare and plan for, absorb, recover from, and more successfully adapt to adverse events”.

Courtesy of: Igor Linkov, M. Bates, A. Ganin, A. Gutfraind, E. Massaro, A. Steen, N. Steen, and M. Wood (ERDC)

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Modeling Help is Needed

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Assessing Impact via Models restoreHost()

Create Alert

malwareDetected()

Between(1,3)h AvailabilityAlert

Restore Functionality

Malicious Activity Discovered ?

Making sense of C2 means relating it to mission impact

Yes Submit Alert

CyCS-deleteTicket() No getNextAlert()

Get Next Alert

Alert Type ?

takeHostOffline()

wipeHost()

5m

Between(1,3)h

5m

Take offline

Wipe and Restore

Put online

WipeAlert

CyCS-deleteTicket() CyCS-createTicket()

Submit Alert InfectedAlert IntegrityAlert ConfidentialityAlert getInfectionSource()

ForensicAlert

None

putHostOnline()

CyCS-deleteTicket()

Create Alert

submitAlert()

getAllInfected()

Between(1,3)h

0m

Between(2,6)h

Between(3,9)h

Trace Attack Source

Issue New Alert

Get Signature

Find other infections

No 0m Targets Available ?

Yes

Issue New Alerts

No alert present

Create Alert getWait()

submitAlert()

Wait to Issue Alert

Issue Alert

Release Resource

Mission is a nexus of a numerous physical assets, information, activities, friendly, enemy…

Start Defender

AMICA explored comprehensive models that cove infrastructure, missions, defenders and attackers Results are insightful but modeling is labor intensive S. Noel, J. Ludwig, P. Jain, D. Johnson, R. Thomas, J. McFarland, B. King, S. Webster and B. Tello, "Analyzing Mission Impacts of Cyber Actions," in Proceedings of the NATO IST-128 Workshop on Cyber Attack Detection, Forensics and Attribution for Assessment of Mission Impact, Istanbul, 2015.

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

AI Must Become Smarter

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Hypes & Successes AI was over-sold many times, but the last 10 years seen impressive achievements  Self-driving cars (DARPA Grand Challenge, 2004 no one finished, in 2005 5 teams finished)  Urban Challenge (2007 follow-up to previous Grand Challenge, 11 teams competed with 6 finishing, 3 in under 6 hour limit)  Spectrum Collaboration Challenge Calls for Contenders (2016)  Deep Blue decisively defeats any human chess player (1996 lost, 1997 won after HW upgrade)  Watson defeats Jeopardy! Champions (2011)  Apple’s Siri (2011), Google Now (2012), Microsoft’s Cortana (2014)  AI personal assistants with voice recognition Skype can translate your conversation in real-time (2015) Google’s DeepMind defeats reigning AlphaGo Champion (2016) Many products of AI research are so common they no longer perceived as AI by the users: route planning on Google Maps; Google Translate; facial recognition products; automated customer service; video games; etc. UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces 24

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Real-world C2 is Still Too Hard for AI Highly-dispersed team of human & robot agents accessing highly heterogeneous information sources Dynamic in-flight learning & re-planning at the Speed of the Fight

Learning in new environments with deception from advanced persistent threats

The Army AI and ML problems involve unique challenges: unstructured, unstable, rapidly changing, chaotic, rubble-filled adversarial environments; learning in real-time, under extreme time constraints, with only a few observations that are potentially erroneous, of uncertain accuracy and meaning, or even intentionally misleading and deceptive.

25

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Gaps Vision: Artificially intelligent agents (heterogeneous & distributed) that rapidly learn, adapt, reason & act in contested, austere & congested environments

Gaps  AI & ML with small samples, dirty data, high clutter  AI & ML with highly heterogeneous data  Adversarial AI & ML in contested, deceptive environment  Distributed AI & ML with limited communications  AI & ML computing with extremely low size, weight, and power, time available (SWaPT)  Explainability & programmability for AI & ML  AI & ML with integrated quantitative models

26

UNCLASSIFIED

Learning in Complex Data Environments

Resource-constrained AI Processing at the Point-of-Need Generalizable & Predictable AI

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

AI-enabled Capabilities

A Soldier supported by team of agents in complex environment

AI-enabled reasoning to provide possible course of actions

AI-enabled real-time estimates of enemy

UNCLASSIFIED

Tactically sensible decision making based on locally available information

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Humans and AI will Team

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Challenges of Teaming

A key challenge is to enable Intelligent Things and Soldiers to effectively and naturally interact across a broad range of warfighting functions, with trust and transparency, common understanding of shared perceptions, and human-agent dialog and collaboration.

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Intelligent Teams Creating Cohesive, Collaborative Teaming

Providing Agents Greater Capabilities

Accelerated Learning for a Ready Force Artificial Intelligence & Machine Learning MACHINE LEARNING

NATURAL LANGUAGE PROCESSING

PLANNING

Providing Humans Greater Capabilities

UNCLASSIFIED

KNOWLDEGE REASONING

COGNITIVE SYSTEMS

ARTIFICIAL INTELLIGENCE

PERCEPTION

ROBOTICS

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Joint Human Human-Intelligent Agent Decision Making Opportunity:

Plans:

 Conceptual & technological advancements in fields such as Human Computation are challenging typical approaches of human system integration

 Humans learning from intelligent agents.

 Recent dramatic advances in deep learning are changing perspectives on what intelligent agents can do in joint collaboration with humans  Enablers: Deductive reasoning using sparse data, hybrid supervised-unsupervised techniques for transfer learning, transfer learning for retraining neural networks, joint learning in unbounded environments



Human observation of intelligent agents can lead to novel understanding of the problem space & novel solution ideas



Intelligent agents can provide assistance with long-term training and decision making

 Explainable intelligence underlying efficient integration of cognitive-assist agents. 

Reconceive problems to support human cognition  Investigate human cognitive capabilities & recast computational problems into domains more amenable to those capabilities



Understandable explanations of “incomprehensible” intelligent agent behaviors

 Intelligent Agents Learning from Limited Data.

UNCLASSIFIED



Training deep networks from sparsely-labeled data under time constraints



Learning with statistically mismatched data  sparse/adversarial: statistics do not match reality

31 The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Teams Train

AI will be a key technology for building, realistic, intelligent entities in immersive training simulations. These should include realistic sociocultural interactions between trainees and simulated intelligent agents. UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Humans vs. Things in C2

Kott, A. and Alberts, D., “How Do You Command an Army of Intelligent Things?” IEEE Computer, 2017 (to appear)

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Humans vs. Things: Command Things are good at: • • • • •

setting goals and priorities, establishing rules, and setting constraints. assigning roles and responsibilities and defining relationships

Well defined goals and priorities Detect inconsistencies No personal agendas No group think No vague interpretations

Not so much: • • • • • •

Understanding the implied Handle lack of formal, specific Understandable to humans Establishing trust Negotiating goals and constraints Adjusting roles and responsibilities

Kott, A. and Alberts, D., “How Do You Command an Army of Intelligent Things?” IEEE Computer, 2017 (to appear)

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Humans vs. Things: Control

Things are good at: • • •

adjustments to actions, considering changes in the situation and the progress; agility in dynamic environments

Recognition and acceptance of new situation Speed of processing No barriers to overturning past decisions

Not so much: • •

Explaining the recommendations / decision Resolving disagreements

Kott, A. and Alberts, D., “How Do You Command an Army of Intelligent Things?” IEEE Computer, 2017 (to appear)

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

Summary •

C2 will be for and by the distributed society of humans and intelligent things



This C2 will be far more fluid and self-adaptive than today’s



Proliferation of intelligent things invites predation of malicious cyber agents



As well as great increase in overall complexity of C2



C2 of this society brings qualitatively new challenges



Humans will be both sources of vulnerability and resilience



AI both invites cyber-attacks, and enables their defeat



Complexity can be exploited for defensive purposes



Design of such C2 calls for novel types of modeling and simulation



AI for C2 will have to close gaps: adversity, complexity, resource constraints, explainability



New forms of human-agent teaming will emerge



Humans and Intelligent Things bring complementary strengths to C2



Humans will learn to partner with Intelligent Things

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

References

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

References REFERENCES Cho, J.H., Swami, A. and Chen, R., 2011. A survey on trust management for mobile ad hoc networks. IEEE Communications Surveys & Tutorials, 13(4), pp.562-583. Colbert, E., A Kott (eds.), Cyber-security of SCADA and Other Industrial Control Systems, Springer 2016 Ganin, A. A., Massaro, E., Gutfraind, A., Steen, N., Keisler, J. M., Kott, A., & Linkov, I. (2016). Operational resilience: concepts, design and analysis. Scientific reports, 6. Gil, Santiago, Alexander Kott, and Albert-László Barabási. "A genetic epidemiology approach to cyber-security." Scientific reports 4 (2014). Gregory, J.M., Twigg, J.N. and Fink, J.R., 2016, October. Enabling autonomous information-gathering and selfrecovery behaviors in partially-known, communication-constrained environments. In Safety, Security, and Rescue Robotics (SSRR), 2016 IEEE International Symposium on (pp. 92-99). IEEE. Heckman, K., and F. Stech, Cyber Denial, Deception and Counter Deception: A Framework for Supporting Active Cyber Defense. Springer 2015 Kenma, S. Rogers, J. Nieto, C. Sukhatme, G. "A multi-robot coordination strategy for informative adaptive sampling in communications-constrained environments" ICRA 2017 (accepted, to appear) Kott, A. and C. Arnold, Promises and challenges of continuous monitoring and risk scoring. IEEE Security and Privacy, 11(1), 90–93 (2013) Kott, A., Swami, A. and McDaniel, P., 2014. Security outlook: six cyber game changers for the next 15 years. Computer, 47(12), pp.104-106. Kott, A., Swami, A. and West, B.J., 2016. The Fog of War in Cyberspace. Computer, 49(11), pp.84-87. Kott, A., Swami, A. and West, B.J., 2016. The Internet of Battle Things. Computer, 49(12), pp.70-75. Kott, Alexander, David S. Alberts, and Cliff Wang. "Will Cybersecurity Dictate the Outcome of Future Wars?" Computer 48.12 (2015): 98-101.

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

UNCLASSIFIED//APPROVED FOR PUBLIC RELEASE

References REFERENCES Kott, Alexander, Nikolai Stoianov, Nazife Baykal, Alfred Moller, Reginald Sawilla, Pram Jain, Mona Lange, and Cristian Vidu. "Assessing Mission Impact of Cyberattacks: Report of the NATO IST-128 Workshop." arXiv preprint arXiv:1601.00912 (2016). Kott, Alexander. "Towards fundamental science of cyber security." Network Science and Cybersecurity. Springer New York, 2014. 1-13. arXiv:1512.00407 Lange, M., R. Moeller, G. Lang and F. Kuhr, "Event Prioritization and Correlation based on Pattern Mining Techniques," in 14th International Conference on Machine Learning and Applications, Miami, 2015. Linkov, I., . Eisenberg, K. Plourde, T. Seager, J. Allen, and A. Kott. "Resilience metrics for cyber systems." Environment Systems and Decisions 33, no. 4 (2013): 471-476. Noel, S., J. Ludwig, P. Jain, D. Johnson, R. Thomas, J. McFarland, B. King, S. Webster and B. Tello, "Analyzing Mission Impacts of Cyber Actions," in Proceedings of the NATO IST-128 Workshop on Cyber Attack Detection, Forensics and Attribution for Assessment of Mission Impact, Istanbul, 2015. Rasch, R., Kott, A., & Forbus, K. D. (2003). Incorporating AI into military decision making: an experiment. IEEE Intelligent Systems, 18(4), 18-26. Summers-Stay, D., Teo, C.L., Yang, Y., Fermüller, C. and Aloimonos, Y., 2012, October. Using a minimal action grammar for activity understanding in the real world. In Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on (pp. 4104-4111). IEEE. Summers-Stay, D., Voss, C. and Cassidy, T., 2016. Using a distributional semantic vector space with a knowledge base for reasoning in uncertain conditions. Biologically Inspired Cognitive Architectures, 16, pp.34-44.

UNCLASSIFIED

The Nation’s Premier Laboratory for Land Forces

Suggest Documents