Distributed search by agents is an important topic of distributed AI and has not been treated thoroughly as such. While the scope of work on multi-agent systems has grown steadily over the last decade, very little of it has spilled into distributed search. In conrast, the constraints processing community has produced a sizable body of work on distributed constrained search. Parado- cally, a community that concentrates on search algorithms and heuristics has created a distributed model for agents that cooperate on solving hard search problems. Traditionally, this ?eld has been named Ditributed Constraints S- isfaction and lately also distributed constraints optimization. The present book attempts to prompt deeper response from the MAS community and hopefully to give rise to cooperative work on distributed search by agents. In order to achieve this high goal, the book presents the large body of work on distributed search by constrained agents. The presentation emphasizes many aspects of distributed computation that connect naturally to multi-agent systems, - pecially measures of performance for distributed search algorithms and the impact of delays in communication. Distributed Constraints Satisfaction Problems (DisCSPs) have been st- ied over the last decade, starting with the pioneering proposal by Makoto Yokoo [18]. The ?rst distributed search algorithm for DisCSPs - As- chronous Backtracking (ABT) - was ?rst published in complete format in 1998 [64]. The ?rst book on Distributed Constraints Satisfaction Problems has appeared as early as 2000 [61].

Distributed search by agents is an important topic of distributed AI and has not been treated thoroughly as such. While the scope of work on multi-agent systems has grown steadily over the last decade, very little of it has spilled into distributed search. In conrast, the constraints processing community has produced a sizable body of work on distributed constrained search. Parado- cally, a community that concentrates on search algorithms and heuristics has created a distributed model for agents that cooperate on solving hard search problems. Traditionally, this ?eld has been named Ditributed Constraints S- isfaction and lately also distributed constraints optimization. The present book attempts to prompt deeper response from the MAS community and hopefully to give rise to cooperative work on distributed search by agents. In order to achieve this high goal, the book presents the large body of work on distributed search by constrained agents. The presentation emphasizes many aspects of distributed computation that connect naturally to multi-agent systems, - pecially measures of performance for distributed search algorithms and the impact of delays in communication. Distributed Constraints Satisfaction Problems (DisCSPs) have been st- ied over the last decade, starting with the pioneering proposal by Makoto Yokoo [18]. The ?rst distributed search algorithm for DisCSPs - As- chronous Backtracking (ABT) - was ?rst published in complete format in 1998 [64]. The ?rst book on Distributed Constraints Satisfaction Problems has appeared as early as 2000 [61].

Distributed search by agents is an important topic of distributed AI and has not been treated thoroughly as such. While the scope of work on multi-agent systems has grown steadily over the last decade, very little of it has spilled into distributed search. In conrast, the constraints processing community has produced a sizable body of work on distributed constrained search. Parado- cally, a community that concentrates on search algorithms and heuristics has created a distributed model for agents that cooperate on solving hard search problems. Traditionally, this ?eld has been named Ditributed Constraints S- isfaction and lately also distributed constraints optimization. The present book attempts to prompt deeper response from the MAS community and hopefully to give rise to cooperative work on distributed search by agents. In order to achieve this high goal, the book presents the large body of work on distributed search by constrained agents. The presentation emphasizes many aspects of distributed computation that connect naturally to multi-agent systems, - pecially measures of performance for distributed search algorithms and the impact of delays in communication. Distributed Constraints Satisfaction Problems (DisCSPs) have been st- ied over the last decade, starting with the pioneering proposal by Makoto Yokoo [18]. The ?rst distributed search algorithm for DisCSPs - As- chronous Backtracking (ABT) - was ?rst published in complete format in 1998 [64]. The ?rst book on Distributed Constraints Satisfaction Problems has appeared as early as 2000 [61].

This book constitutes the refereed proceedings of the 6th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2022, held in Be'er Sheva, Israel, in June - July 2022.The 24 full and 11 short papers presented together with a keynote paper in this volume were carefully reviewed and selected from 53 submissions. They deal with the theory, design, analysis, implementation, or application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.

Distributed search by agents is an important topic of distributed AI and has not been treated thoroughly as such. While the scope of work on multi-agent systems has grown steadily over the last decade, very little of it has spilled into distributed search. In conrast, the constraints processing community has produced a sizable body of work on distributed constrained search. Parado- cally, a community that concentrates on search algorithms and heuristics has created a distributed model for agents that cooperate on solving hard search problems. Traditionally, this ?eld has been named Ditributed Constraints S- isfaction and lately also distributed constraints optimization. The present book attempts to prompt deeper response from the MAS community and hopefully to give rise to cooperative work on distributed search by agents. In order to achieve this high goal, the book presents the large body of work on distributed search by constrained agents. The presentation emphasizes many aspects of distributed computation that connect naturally to multi-agent systems, - pecially measures of performance for distributed search algorithms and the impact of delays in communication. Distributed Constraints Satisfaction Problems (DisCSPs) have been st- ied over the last decade, starting with the pioneering proposal by Makoto Yokoo [18]. The ?rst distributed search algorithm for DisCSPs - As- chronous Backtracking (ABT) - was ?rst published in complete format in 1998 [64]. The ?rst book on Distributed Constraints Satisfaction Problems has appeared as early as 2000 [61].

Distributed search by agents is an important topic of distributed AI and has not been treated thoroughly as such. While the scope of work on multi-agent systems has grown steadily over the last decade, very little of it has spilled into distributed search. In conrast, the constraints processing community has produced a sizable body of work on distributed constrained search. Parado- cally, a community that concentrates on search algorithms and heuristics has created a distributed model for agents that cooperate on solving hard search problems. Traditionally, this ?eld has been named Ditributed Constraints S- isfaction and lately also distributed constraints optimization. The present book attempts to prompt deeper response from the MAS community and hopefully to give rise to cooperative work on distributed search by agents. In order to achieve this high goal, the book presents the large body of work on distributed search by constrained agents. The presentation emphasizes many aspects of distributed computation that connect naturally to multi-agent systems, - pecially measures of performance for distributed search algorithms and the impact of delays in communication. Distributed Constraints Satisfaction Problems (DisCSPs) have been st- ied over the last decade, starting with the pioneering proposal by Makoto Yokoo [18]. The ?rst distributed search algorithm for DisCSPs - As- chronous Backtracking (ABT) - was ?rst published in complete format in 1998 [64]. The ?rst book on Distributed Constraints Satisfaction Problems has appeared as early as 2000 [61].

Distributed search by agents is an important topic of distributed AI and has not been treated thoroughly as such. While the scope of work on multi-agent systems has grown steadily over the last decade, very little of it has spilled into distributed search. In conrast, the constraints processing community has produced a sizable body of work on distributed constrained search. Parado- cally, a community that concentrates on search algorithms and heuristics has created a distributed model for agents that cooperate on solving hard search problems. Traditionally, this ?eld has been named Ditributed Constraints S- isfaction and lately also distributed constraints optimization. The present book attempts to prompt deeper response from the MAS community and hopefully to give rise to cooperative work on distributed search by agents. In order to achieve this high goal, the book presents the large body of work on distributed search by constrained agents. The presentation emphasizes many aspects of distributed computation that connect naturally to multi-agent systems, - pecially measures of performance for distributed search algorithms and the impact of delays in communication. Distributed Constraints Satisfaction Problems (DisCSPs) have been st- ied over the last decade, starting with the pioneering proposal by Makoto Yokoo [18]. The ?rst distributed search algorithm for DisCSPs - As- chronous Backtracking (ABT) - was ?rst published in complete format in 1998 [64]. The ?rst book on Distributed Constraints Satisfaction Problems has appeared as early as 2000 [61].

This book constitutes the refereed proceedings of the 6th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2022, held in Be'er Sheva, Israel, in June - July 2022.The 24 full and 11 short papers presented together with a keynote paper in this volume were carefully reviewed and selected from 53 submissions. They deal with the theory, design, analysis, implementation, or application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.